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%% Cell type:markdown id: tags:
This project is composed of several jupyter notebooks that explain how to use topological data analysis with different machine learning techniques.
While the notebooks are independent of one another, it might be beneficial if one reads through the notebook titled "TDA_Background," provides a general background on the theory. Additionally, it introduces the main TDA python functions.
The remaining notebooks provide different applications of TDA.
README.md
View file @ cd33c200
# Topological Machine Learning
The first 1/3 of this project will require the utilization of traditional machine learning methods on a dataset. The purpose of this portion of the project is promote the benefits of TDA. It is used to show data scientists that they can achieve very interesting results when using TDA. The second portion of this project will be incorporating TDA with machine learning. This portion of the project will be the most demanding due to lack of references. I will attempt to perform both a classification type project and prediction type project. Additionally, I may have to rely on HPCC to run my script (TDA is computationally expensive). The final portion of the project will be creating a Jupyter demo project for data scientists as well as a short semi-theoretical document that discusses the more important features of TDA.
This project provides an easy to follow introduction to Topological Data Analysis (TDA). TDA is a machine learning tool that borrows concepts from topology and applies them to datasets. While the theory behind TDA is quite complex (thought important and interesting!), this project will only focus on applications. There is, however, an introductory notebook which provides user with a brief introduction to the main concepts within TDA as well as the scikit learn TDA package. The remaining notebooks apply TDA with different machine learning methods such as prediction and classifying.
I hope to create a script that is easy for those who are not familiar with TDA to follow. Ideally, I would like to create a document that scikit-tda is willing to publish. Hence, the document needs to be constructed in a manner that is easy to interpret by anyone who is new to TDA.
Future improvements include:
1. Fixing the prediction notebook.
2. Using the Ripser function to classify data.
3. Providing deeper analysis on the results.
Thankfully, python is already has the libraries that I will need. They are as follows: scipy, numpy, matplotlib, pandas, seaborn, scikit-tda
## Prerequisites
## Getting Started
The environment file contains all of the required packages. You may either activate the environment file or install the required packages individually.
* Update
### Prerequisites
You may need to install the Python TDA library. The installation can be done in Pypi using just one command: pip install scikit-tda. Necessary installations include seaborn, pandas, numpy, matplotlib, scipy, jupyter, Cython, scikit-tda, Ripser, and persim. All can be installed using:
'''
conda install 'package'
'''
To run the Jupyter Notebooks sucessfully, you must them through the project's enviornment.
## Authors
......@@ -49,8 +44,4 @@ OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE,
ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
OTHER DEALINGS IN THE SOFTWARE.
For more information, please refer to <https://unlicense.org>
## Acknowledgments
* UPDATE
\ No newline at end of file
For more information, please refer to <https://unlicense.org>
\ No newline at end of file
Reports/0424-PROJECT-Final-Report.ipynb 0 → 100644
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%% Cell type:markdown id: tags:
# <center> Topological Machine Learning </center>
<center>By Shawk Macboob </center>
%% Cell type:markdown id: tags:
<img src="https://scikit-tda.org/_static/logo.png" width="20%">
Image from: https://scikit-tda.org/#
%% Cell type:markdown id: tags:
---
# Authors
Shawk Masboob
%% Cell type:markdown id: tags:
---
# Abstract
Topological Data Analysis i(TDA) s a relatively new field with many useful applications. Essentially, TDA borrows tools from topology in order to study data. That is, TDA seeks to determine whether a particular dataset has shape and what the shape of the dataset implies. It can be used independently or applied to other machine learning techniques. This particular projects aims at applying TDA to various machine learning methods in order to demonstrate its benefits. To do so, this project first presents the general theory of TDA as well as introducing the available TDA software. Then, several notebooks are illustrate how TDA can be applied to machine learning.
%% Cell type:markdown id: tags:
----
# Statement of Need
The purpose of this project is to introduce data scientists to Topological Data Analysis (TDA) through various examples. That is, this project aims to demonstrate applications of TDA to those who do not have a background in mathematics.
%% Cell type:markdown id: tags:
----
# Installation instructions
The environment.yml file constains all of the required dependices. To install the required moduels, run the following command in the terminal:
`make init`
%% Cell type:markdown id: tags:
----
# Unit Tests
Unit testing is done on the following two functions: `lens_1d` and `uniform_sampling`. These tests check to verify that the function takes in correct inputs.
To run a unit test, simply write `make test` in the terminal.
%% Cell type:markdown id: tags:
---
# Methodology
I was able to meet the majority of my initial goals. I created different notebooks that used TDA in different ways. Additionally, I created a background notebook that gave a basic introduction to TDA. While I was able to meet my general goals, I think I could have approach this project differently. For instance, Ripser and Mapper are the two most used libraries from the scikit-tda package. I think I should have introduced these libraries more thoroughly. Both of these libraries have many applications which my project did not highlight. For instance, Ripser can be used for nonlinear time series analysis, feature selection, classifying, etc. While it is impossible to demonstrate all of the possible applications for Ripser, I could have discussed them more and linked some articles - though the vast majority of the papers I’ve come across focus on the mathematical side of TDA rather than the application.
Mapper was incredibly challenging to use. I spent the vast majority of the semester trying to understand and apply it. I was able to do basic classification using Mapper, although I am still unsure what the best method is in order to improve the model. I also do not know how to get some sort of accuracy score. I am only able to look at the output graph and determine whether the data separated well. I have yet to figure out how topologists determine the overall accuracy of their classification. Additionally, I was not able to fully complete the prediction notebook. I know how to use Mapper in the sense that I was able to separate the data visually. The next task is to learn how to extract the data. After doing so, I can easily build a new predictive model. In general, I need to experiment more with Mapper in order to better understand how to implement it.
%% Cell type:markdown id: tags:
---
# Concluding Remarks
I have a much deeper understanding of TDA because of this project. Before this project, I thought Ripser was only used for persistence diagrams. That is, I thought you can only do an exploratory analysis with Ripser. I was unaware that Ripser is used in time series analysis or classification. As for Mapper, I had no idea how to work with it in general. I was not formally introduced to Mapper - everything I currently know comes from articles/papers I’ve read. My background in Mapper is still limited but I feel more confident using it and experimenting with the parameters.
For future work, I would like to expand my work with Mapper. I would like to create more wrapper functions that simplify the steps that go into building a graph. Additionally, I would like to learn how to color nodes so that I can gain more insight. For instance, I would like to learn how to color nodes based on proportions for y1 to y2. My current understanding of Mapper is shallow so I would like to expand it and add detail application to my project.Additionally, I would like to create more notebooks that do not use toy datasets. Toy datasets are easy to work with but do not add enough complexity. To full demonstrate the applications of Mapper, I need to work with more challenging data.
%% Cell type:markdown id: tags:
----
# References
Individual notebooks have their own reference section. However, all notebooks use the scikit-tda package.
Saul, Nathaniel and Tralie, Chris. (2019). Scikit-TDA: Topological Data Analysis for Python. Zenodo. http://doi.org/10.5281/zenodo.2533369
TDA_Background.ipynb
View file @ cd33c200
%% Cell type:markdown id: tags:
<h1><center>Topological Data Analysis</center></h1>
![Url](https://thumbs.gfycat.com/DisgustingBlandDromedary-size_restricted.gif)
<p style="text-align: center;">Gif from: https://gfycat.com/disgustingblanddromedary</p>
%% Cell type:markdown id: tags:
### Background
### Introduction
The tools from Topological Data Analysis (TDA) emerged in response to the issues in high-dimensional data. Essentially, TDA seeks to utilize tools from topology, a brach of mathematics “concerned with the properties of a geometric object that are preserved under continuous deformations, such as stretching, twisting, crumpling and bending, but not tearing or gluing,” [1] to analyze data. How does topology relate to data analysis? TDA seeks to utilize mathematical, statistical, and algorithmic methods to make inferences and analyze the topological structure and geometric structures of data [2].
This notebook (and the remaining notebooks) are designed to introduce data scientists to TDA without needing a background in math.
Before exploring TDA applications, this particular notebook will cover some of the most important topics in TDA.
%% Cell type:markdown id: tags:
### Simplicial Complex
Informally, a simplex is a generalization of the notion of a trigangle in _n_ dimensional space. Formally,
%% Cell type:code id: tags:
``` python
import numpy as np
import scipy as sp
import ripser
import matplotlib.pyplot as plt
import scipy.spatial.distance as distance
import scipy.io as sio
import time
import copy
from IPython.display import YouTubeVideo
YouTubeVideo("XfWibrh6stw",width=640,height=360)
```
from matplotlib.offsetbox import OffsetImage, AnnotationBbox
from scipy.sparse import csr_matrix
from scipy.sparse.csgraph import floyd_warshall
from sklearn.neighbors import kneighbors_graph
%% Output
from matplotlib.patches import Circle
from persim import plot_diagrams
from mpl_toolkits.mplot3d import Axes3D
<IPython.lib.display.YouTubeVideo at 0x123d124a8>
import matplotlib.pyplot as plt
import random
import numpy as np
%% Cell type:markdown id: tags:
from ripser import ripser
from ripser import Rips
from persim import plot_diagrams
### Simplicial Complex
from IPython.display import display, clear_output
import time
- Graph Theory
- Simplex
- Simplicial Complex
from ipywidgets import interact, widgets
In graph theory, graphs are mathematical tools used to represent relations between objects. Graphs are composed of nodes (or points or verticies) and edges (or links or lines). More formally,
%matplotlib inline
```
_A graph $G = (V, E)$ consists of $V$, a nonempty set of vertices (or nodes) and $E$, a set of edges. Each edge has either one or two vertices associated with it, called its endpoints. An edge is said to connect its endpoints."_ 4
%% Cell type:code id: tags:
Borrowing concepts from graph theory (i.e. nodes and edges), a simplex is a generalization of a what we refer to as a tetrahedron to some arbitrary dimensions. The image below provides the first few simplicies.
``` python
def maxmin(dist_matrix, n):
'''
Given a distance matrix retunrs a maxmin subsampling and the covering radious
corresponding to the subsampled set.
<img src="https://umap-learn.readthedocs.io/en/latest/_images/simplices.png" width="50%">
<p style="text-align: center;">Image from: https://umap-learn.readthedocs.io/en/latest/how_umap_works.html/</p>
:param dist_matrix: Distance matrix
:param n: Size of subsample set.
:returns L: List of indices corresponding to the subsample set.
:return cr: Covering radious for the subsample set.
'''
L = [np.random.randint(0,len(dist_matrix))]
The empty set, ${\displaystyle \emptyset }$, is the -1-simplex. A node is the 0-simplex. Two nodes connected by an edge is the 1-simplex. Three nodes connected by three edges that form a triangle is the 2-simplex. A tetrahedron is the 3-simplex, and so on. A simplex of n dimensions is referred to as an n-simplex. 4. Simplicies are the building blocks of a simplicial complex. If we were to "glue" simplicies together, we form a simplicial complex.
dist_to_L = dist_matrix[ L[-1] ,:]
<img src="https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0213679.g003&type=large" width="50%">
<p style="text-align: center;">Image from: https://journals.plos.org/plosone/article/figure?id=10.1371/journal.pone.0213679.g003</p>
<p style="text-align: center;">Caption: In (A), where ϵ is close to zero, each point is a discrete component. In (B), two points have come within ϵ and are joined by a 1-simplex. In (C), 2-simplices have formed where there are sets of three points pairwise within ϵ. Note that the upper 2-simplex connects three points whose ϵ/2-balls have no common intersection, a phenomenon possible in the Vietoris-Rips complex. At this scale a 1-dimensional hole (cycle) has formed among four of the data points. [5]</p>
for i in range(n-1):
ind = np.argmax( dist_to_L )
L.append(ind)
After selecting some distance measure, denoted by epsilon, you draw a ball with diameter epsilon around each point. As epsilon increases, some of the balls begin to merge, which we then connect using an edge. This creates a graph. To build a simplicial complex, i.e., move away from simple graphs, we locate sets of three points that are connect by edges that create a triangle, aka the 2-simplex, and fill them in. We then fill in the three simplex and so on. The resulting simplicial complex is referred to as the Rips Complex.
dist_to_L = np.minimum(dist_to_L, dist_matrix[L[-1], :])
%% Cell type:markdown id: tags:
cr = np.max(dist_to_L)
### Persistent Homology
return L, cr
- Homology
- Persistent Homology
def uniform_sampling(dist_matrix, n):
'''
Given a distance matrix retunrs an subsamplig that preserves the distribution of the original data set
and the covering radious corresponding to the subsampled set.
Homology, in simple terms, is how we count the connected components of our simplicial complex such as the number of holes or voids (note, there is a more technical definition).
:param dist_matrix: Distance matrix
:param n: Size of subsample set.
:returns L: List of indices corresponding to the subsample set.
:return cr: Covering radious for the subsample set.
'''
num_points = dist_matrix.shape[0]
<img src="https://storage.googleapis.com/groundai-web-prod/media/users/user_209956/project_331333/images/filtration.png" width="60%">
<p style="text-align: center;">Image from: https://www.groundai.com/project/persistent-homology-based-machine-learning-and-its-applications-a-survey/1</p>
L = np.random.choice(num_points, n)
If we apply homology to the above figure, we see that it has a central hole. Again, there is more to homology than merely counting the number of holes. However, it is not necessary to get into the techniqualites of homology in order to use TDA.
dist_to_L = np.min(dist_matrix[L,:], axis=0)
Persistent homology is how we measure the topological features of a dataset. Put differently, "Persistent homology then captures how the homology of the complexes changes as the parameter value increases, and it detects which features ‘persist’ across changes in the parameter value." [6] If we refer back to our example of growing balls, then a 0-dimensional persistent homology measures when the balls intersect with one another. The 1-dimensional keeps track of when loops begin to form. This same thought process continues to the $n-$dimensional persistent homology, where we count the number of multidimensional voids enclosed by the balls.
return L, np.max(dist_to_L)
```
The following video provides a very brief introduction to theory behind topological data analysis.
%% Cell type:code id: tags:
``` python
from IPython.display import YouTubeVideo
YouTubeVideo("2PSqWBIrn90",width=640,height=360)
```
n=200
theta = np.random.uniform(0, 2*np.pi, n)
%% Output
# Generate radii with Gaussian noise centered at 1
r = 1 + np.random.normal(0, 0.05, n)
r[0] = 0
# Use angles and radii to generate circle
X = r[:,np.newaxis]*np.concatenate((np.cos(theta)[:,np.newaxis], np.sin(theta)[:,np.newaxis]), axis=1)
# Compute the distance matrix for the data set X using auclidean distance.
dm_X = distance.cdist(X,X)
<IPython.lib.display.YouTubeVideo at 0x123d125f8>
ind_L, cover_r = uniform_sampling(dm_X, 20)
%% Cell type:markdown id: tags:
# scatter plot the landmark subset
fig, ax = plt.subplots()
#plt.scatter(X[:,0], X[:,1], c=theta, cmap='jet')
plt.scatter(X[ind_L,0], X[ind_L,1], c='black')
R=np.arange(0,1.5,0.1)
# Plot balls or radious defined by the covering radious of the landmark set
for point in range(len(ind_L)):
cir = Circle((X[ind_L[point],0], X[ind_L[point],1]),1, color=(.5,.5,.5,0.2))
ax.add_patch(cir)
### Scikit Learn TDA Package
Scikit-learn's Topological Data Analysis package, Scikit-TDA, is intended for non-topologists; that is, it is intended for all users. Scikit-TDA has five libraries:
- Ripser.py
- Kepler Mapper
- Persim
- CechMate
- TaDAsets
The two main libraries are `Ripser.py` and `Kepler Mapper`, although the remaining libraries are valuable.
### <center> Ripser</center>
fig = plt.figure(figsize = (12,7))
time.sleep(0.2)
clear_output(wait=True) # Clear output for dynamic display
display(fig) # Reset display
fig.clear() # Prevent overlapping and layered plots
plt.close();
<img src="http://ripser.scikit-tda.org/_static/logo.png" width="25%">
<p style="text-align: center;">Image from: http://ripser.scikit-tda.org/</p>
ax.set_ylim(-1-cover_r,1+cover_r)
ax.set_xlim(-1-cover_r,1+cover_r)
```
[Ripser](https://ripser.scikit-tda.org/) is a persistent homology package for Python. To quote Scikit-TDA,
%% Output
_Ripser.py is a lean persistent homology package for Python. Building on the blazing fast C++ Ripser package as the core computational engine, Ripser.py provides an intuitive interface for_
- computing persistence cohomology of sparse and dense data sets,
- visualizing persistence diagrams,
- computing lowerstar filtrations on images, and
- computing representative cochains.
(-1.922760288967155, 1.922760288967155)
#### Ripser Parameters:
- __X__: data array
- __maxdim__: maximum homology dimension
- __thresh__: maximum distances considered when constructing filtration
- __coeff__: compute homology with coefficients in the prime field
- __distance_matrix__: indicator that X is a distance matrix
- __do_cocycles__: indicator of whether to compute cocycles
- __metric__: metric to use when calculating distance between instances in a feature array
The following code allows users to experiment with Ripser. That is, it is written to allow people to visualize how the persistence diagram will look for a specific dataset as the radius increases.
%% Cell type:code id: tags:
``` python
cir = Circle((X[ind_L[point],0], X[ind_L[point],1]),.5, color=(.5,.5,.5,0.2))
dgms = ripser(X, maxdim=0, thresh=1)['dgms']
plot_diagrams(dgms, show=True)
from Topological_ML import tda_function as tda
import numpy as np
import scipy.spatial.distance as distance
import matplotlib.pyplot as plt
from matplotlib.patches import Circle
from IPython.display import display, clear_output
import time
from ipywidgets import interact, widgets
from ripser import ripser
from ripser import Rips
from persim import plot_diagrams
%matplotlib inline
```
%% Output
%% Cell type:code id: tags:
``` python
# cell to do interactive plotting
n=200
theta = np.random.uniform(0, 2*np.pi, n)
# Generate radii with Gaussian noise centered at 1
r = 1 + np.random.normal(0, 0.05, n)
r[0] = 0
# Use angles and radii to generate circle
X = r[:,np.newaxis]*np.concatenate((np.cos(theta)[:,np.newaxis], np.sin(theta)[:,np.newaxis]), axis=1)
# Compute the distance matrix for the data set X using auclidean distance.
dm_X = distance.cdist(X,X)
ind_L, cover_r = uniform_sampling(dm_X, 20)
ind_L, cover_r = tda.uniform_sampling(dm_X, 20)
# add slider
def persistance_interact(radius = 1):
"""Used to create an interactive plot of growing radius around point and the corresponding persistence diagram.
def update(radius = 0.25):
# scatter plot the landmark subset
# put circles on the left side; JK
Args:
radius: desired radius size.
"""
fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(9.5,4.5))
#plt.scatter(X[:,0], X[:,1], c=theta, cmap='jet')
ax1.scatter(X[ind_L,0], X[ind_L,1], c='black')
R=np.arange(0,1.5,0.1)
# Plot balls or radious defined by the covering radious of the landmark set
for point in range(len(ind_L)):
cir = Circle((X[ind_L[point],0], X[ind_L[point],1]),radius, color=(.5,.5,.5,0.2))
ax1.add_patch(cir)
ax1.set_ylim(-1-cover_r,1+cover_r)
ax1.set_xlim(-1-cover_r,1+cover_r)
# plot persistance diagram; JK
cir = Circle((X[ind_L[point],0], X[ind_L[point],1]),.5, color=(.5,.5,.5,0.2))
dgms = ripser(X, maxdim=0, thresh=1)['dgms']
dgms = ripser(X, maxdim=0, thresh=radius*0.5)['dgms']
plot_diagrams(dgms, show=True, ax=ax2)
# to reduce the margins inside plot; JK
plt.tight_layout()
return
# define range and step for radius: from 0.0 till 0.5 (inclusive) with step 0.01
interact(update, radius=(0.0, 0.5, 0.01));
interact(persistance_interact, radius=(0.0, 1, 0.01));
```
%% Output
%% Cell type:code id: tags:
``` python
# def animate_H0(data, radius):
# fig = plt.figure(figsize=(6,6))
# fig.suptitle('Persistent Homology of a Circle (H0)')
# plt.subplot(121)
# plt.scatter(X[ind_L,0], X[ind_L,1], c='red')
# for point in range(len(ind_L)):
# cir = Circle((X[ind_L[point],0], X[ind_L[point],1]), cover_r, color=(0.7,0.2,0.5,0.2))
# add_patch(cir)
# plt.subplot(122)
# dgms = ripser(X, maxdim=0, thresh=radius)['dgms']
# plt.plot_diagrams(dgms, show=True)
# plt.scatter(X[ind_L,0], X[ind_L,1], c='red')
# plt.subplot(121)
# plt.scatter(X[ind_L,0], X[ind_L,1], c='red')
# # Plot balls or radious defined by the covering radious of the landmark set
# for point in range(len(ind_L)):
# cir = Circle((X[ind_L[point],0], X[ind_L[point],1]), cover_r, color=(0.6,0.6,0.6,0.2))
# ax.add_patch(cir)
# plt.set_ylim(-1-cover_r,1+cover_r)
# plt.set_xlim(-1-cover_r,1+cover_r)
# plt.subplot(122)
# dgms = ripser(X, maxdim=0, thresh=1)['dgms']
# plot_diagrams(dgms, show=True)
```
%% Cell type:markdown id: tags:
### Homology
%% Cell type:markdown id: tags:
#### Betti Number
%% Cell type:markdown id: tags:
#### Euler Formula
%% Cell type:markdown id: tags:
### Persistent Homology
%% Cell type:markdown id: tags:
words
![Url](https://miro.medium.com/max/1400/1*9dqnnfbqz0WfjlhONkD2iQ.gif)
%% Cell type:markdown id: tags:
### <center> Ripser</center>
<img src="http://ripser.scikit-tda.org/_static/logo.png" width="25%">
<p style="text-align: center;">Image from: http://ripser.scikit-tda.org/</p>
### <center>Mapper</center>
%% Cell type:markdown id: tags:
<img src="https://kepler-mapper.scikit-tda.org/_static/logo.png" width="23%">
[Ripser](https://ripser.scikit-tda.org/) is a persistent homology package for Python.
<p style="text-align: center;">Image from: https://kepler-mapper.scikit-tda.org/</p>
#### Ripser Parameters:
- __X__: data array
- __maxdim__: maximum homology dimension
- __thresh__: maximum distances considered when constructing filtration
- __coeff__: compute homology with coefficients in the prime field
- __distance_matrix__: indicator that X is a distance matrix
- __do_cocycles__: indicator of whether to compute cocycles
- __metric__: metric to use when calculating distance between instances in a feature array
[Kelper Mapper](https://kepler-mapper.scikit-tda.org/) is the Python TDA Mapper package.
%% Cell type:markdown id: tags:
To quote scikit-TDA,
### <center>Mapper</center>
_Kepler Mapper is a library implementing the Mapper algorithm in Python. Mapper can be used for visualization of the topological structures in a high-dimensional data point cloud data. Kepler Mapper leverages Scikit-Learn API compatible cluster and scaling algorithms to streamline the construction of the algorithm._
<img src="https://kepler-mapper.scikit-tda.org/_static/logo.png" width="23%">
Mapper's general algorithm is as follows:
<p style="text-align: center;">Image from: https://kepler-mapper.scikit-tda.org/</p>
Project a dataset $\to$ Cover this projection with overlapping intervals/hypercubes $\to$ Cluster the points inside an interval $\to$ The clusters become nodes in a graph $\to$ When there is such a member intersection, draw an edge between these nodes $\to$ Visual exploration
%% Cell type:markdown id: tags:
A more detailed explaination is offered on scikit-TDA.
[Kelper Mapper](https://kepler-mapper.scikit-tda.org/) is the Python TDA Mapper package.
#### Mapper Parameters:
- __Data__: Point Cloud Data
- __Filter Function__: A filter function is a function on the data set, $f: X \to \mathbb{R}^2$
- Filter functions can help reveal possible geometric structures within the data [3].
- Some choices for [filter functions](http://danifold.net/mapper/filters.html) include _eccentricity,_ _Kernel Density Estimator,_ _k-th nearest neighbor,_ _k-th eigenvector,_ or the _Graph Laplacian._
- __Clustering Technique__:
- __Number of Interval__:
- __Percent Overlap__:
#### Mapper Method:
Unlike Ripser, which is a function, Mapper is composed of several functions.
- __init__: Constructor for KeplerMapper class
- __data_from_cluster_id__: Returns the original data of each cluster member for a given cluster ID
- __fit_transform__: Same as .project() but accepts lists for arguments so you can chain.
- __map__: Apply Mapper algorithm on this projection and build a simplicial complex.
- __project__: Creates the projection/lens from a dataset.
- __visualize__: Generate a visualization of the simplicial complex mapper output.
%% Cell type:markdown id: tags:
## Additional Resource
If one is intersted in seeking additional information about TDA or would like to understand the magic behind TDA, consider watching the following YouTube videos. They are provided by [Jose Perea](https://www.joperea.com/teaching/spring2020), a professor of Mathematics at Michigan State University.
%% Cell type:code id: tags:
``` python
from IPython.display import YouTubeVideo
YouTubeVideo("BDQDpdTc-A4",width=640,height=360)
```
%% Output
<IPython.lib.display.YouTubeVideo at 0x12988c780>
<IPython.lib.display.YouTubeVideo at 0x1044d2f98>
%% Cell type:markdown id: tags:
### References
[1] https://en.wikipedia.org/wiki/Topology
[2] https://arxiv.org/abs/1710.04019
[3] http://www.diva-portal.org/smash/get/diva2:900997/FULLTEXT01.pdf
%% Cell type:code id: tags:
[4] https://www.projectrhea.org/rhea/index.php/Walther375Spring2014_Simplicial_complexes:_higher_dimensional_versions_of_graphs
``` python
```
[5] https://journals.plos.org/plosone/article/figure?id=10.1371/journal.pone.0213679.g003
[6] https://epjdatascience.springeropen.com/articles/10.1140/epjds/s13688-017-0109-5
......
TDA_Classification.ipynb
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%% Cell type:markdown id: tags:
<h1><center>Classification using Topological Data Analysis</center></h1>
<img src="https://i.pinimg.com/564x/42/23/f5/4223f59e7e0a7e69e2b73118c7a69cbb.jpg" width="50%">
<p style="text-align: center;">Image from:https://www.pinterest.jp/pin/406942516319576339/</p>
<img src="https://cdn.vox-cdn.com/thumbor/GcZR8_tOztIDAiSlX47_5oyZ-js=/0x0:1599x1066/1200x800/filters:focal(834x375:1088x629)/cdn.vox-cdn.com/uploads/chorus_image/image/55588811/King_Estate_Winery_NEXT_Amazon_Wine.0.jpg" width="70%">
<p style="text-align: center;">Image from: https://www.vox.com/2017/7/6/15926476/amazon-next-wine-king-vintners-king-estate-winery</p>
%% Cell type:markdown id: tags:
Purpose of Notebook.
In this notebook, we will classify wine quality using topological data analysis with Mapper.
The general motivation of this notebook is to demonstrate how to use Mapper and how to apply TDA to classification related models.
%% Cell type:code id: tags:
``` python
init
# imports
from Topological_ML import tda_function as tda
import pandas as pd
import numpy as np
import sklearn
from sklearn import ensemble
import kmapper as km
from kmapper.plotlyviz import *
import matplotlib.pyplot as plt
import plotly.graph_objs as go
from ipywidgets import (HBox, VBox)
import warnings
warnings.filterwarnings("ignore")
```
%% Cell type:markdown id: tags:
First, we download the wine dataset from Scikit Learn.
%% Cell type:code id: tags:
``` python
# import wine dataset from scikit learn
from sklearn.datasets import load_wine
wine = load_wine()
df = pd.DataFrame(wine['data'],columns = wine['feature_names'])
df['quality'] = wine['target']
df.head()
```
%% Output
---------------------------------------------------------------------------
NameError Traceback (most recent call last)
<ipython-input-3-19f3d006bcd3> in <module>
----> 1 init
alcohol malic_acid ash alcalinity_of_ash magnesium total_phenols \
0 14.23 1.71 2.43 15.6 127.0 2.80
1 13.20 1.78 2.14 11.2 100.0 2.65
2 13.16 2.36 2.67 18.6 101.0 2.80
3 14.37 1.95 2.50 16.8 113.0 3.85
4 13.24 2.59 2.87 21.0 118.0 2.80
flavanoids nonflavanoid_phenols proanthocyanins color_intensity hue \
0 3.06 0.28 2.29 5.64 1.04
1 2.76 0.26 1.28 4.38 1.05
2 3.24 0.30 2.81 5.68 1.03
3 3.49 0.24 2.18 7.80 0.86
4 2.69 0.39 1.82 4.32 1.04
od280/od315_of_diluted_wines proline quality
0 3.92 1065.0 0
1 3.40 1050.0 0
2 3.17 1185.0 0
3 3.45 1480.0 0
4 2.93 735.0 0
%% Cell type:markdown id: tags:
NameError: name 'init' is not defined
Now that the data is downloaded, we seperate the reponse from the features and build a simplicial complex based on the features. The lens_1d function has other options that one can experiment with in order to build a better simplicial complex.
%% Cell type:code id: tags:
``` python
# seperate features and response
feature_names = [c for c in df.columns if c not in ["quality"]]
X = np.array(df[feature_names])
y = np.array(df["quality"])
# you may choose any lens type here
lens, mapper = tda.lens_1d(X,"max")
# Define the simplicial complex
scomplex = mapper.map(lens,
X,
nr_cubes=15,
overlap_perc=0.7,
clusterer=sklearn.cluster.KMeans(n_clusters=2,
random_state=3471))
```
%% Cell type:markdown id: tags:
The following code, borrowed from scikit-TDA, uses the simplicial complex that we just defined to build a graph. The majority of the code is building an interactive plot within a notebook.
%% Cell type:code id: tags:
``` python
# color scale
pl_brewer = [[0.0, '#006837'],
[0.1, '#1a9850'],
[0.2, '#66bd63'],
[0.3, '#a6d96a'],
[0.4, '#d9ef8b'],
[0.5, '#ffffbf'],
[0.6, '#fee08b'],
[0.7, '#fdae61'],
[0.8, '#f46d43'],
[0.9, '#d73027'],
[1.0, '#a50026']]
color_function = lens [:,0] - lens[:,0].min()
my_colorscale = pl_brewer
kmgraph, mapper_summary, colorf_distribution = get_mapper_graph(scomplex,
color_function,
color_function_name='Distance to x-max',
colorscale=my_colorscale)
# assign to node['custom_tooltips'] the node label: 0 - low quality, 1 - medium quality, 2 - high quality
for node in kmgraph['nodes']:
node['custom_tooltips'] = y[scomplex['nodes'][node['name']]]
bgcolor = 'rgba(10,10,10, 0.9)'
# on a black background the gridlines are set on grey
y_gridcolor = 'rgb(150,150,150)'
plotly_graph_data = plotly_graph(kmgraph, graph_layout='fr', colorscale=my_colorscale,
factor_size=2.5, edge_linewidth=0.5)
layout = plot_layout(title='Topological network representing the<br> wine quality dataset',
width=620, height=570,
annotation_text=get_kmgraph_meta(mapper_summary),
bgcolor=bgcolor)
fw_graph = go.FigureWidget(data=plotly_graph_data, layout=layout)
fw_hist = node_hist_fig(colorf_distribution, bgcolor=bgcolor,
y_gridcolor=y_gridcolor)
fw_summary = summary_fig(mapper_summary, height=300)
dashboard = hovering_widgets(kmgraph,
fw_graph,
ctooltips=True,
bgcolor=bgcolor,
y_gridcolor=y_gridcolor,
member_textbox_width=600)
#Update the fw_graph colorbar, setting its title:
fw_graph.data[1].marker.colorbar.title = 'dist to<br>x-min'
dashboard
```
%% Output
%% Cell type:markdown id: tags:
Several observations can be made:
1. The top half of the graph is composed of wine with quality 0
2. The middle region is composed of all wine types
3. The bottom region is composed of wine with quality 1 and 2
We attained some seperability however, this model can be improved by using different clustering methods or a different filter function. The current graph does note seperate quality 1 and 2 very well.
Further insight can be made (although it requires more coding). For instance, one can color the nodes so that they show the proportion of high quality wine to the rest.
......
TDA_EDA.ipynb 0 → 100644
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%% Cell type:markdown id: tags:
<h1><center>US Presidential Election Results</center></h1>
<img src="https://d3n8a8pro7vhmx.cloudfront.net/fairvote/pages/98/meta_images/original/iStock_000005814659_Large-cropped.jpg?1450044496" width="70%">
<p style="text-align: center;">Image from: https://www.fairvote.org/rcv#where_is_ranked_choice_voting_used</p>
%% Cell type:markdown id: tags:
The United States election results have been analyzed through several machine learning methods. In this notebook, we will use TDA to determine whether there is a natural pattern in pressidential elections results.
- Economic Indicators: https://apps.bea.gov/regional/downloadzip.cfm
- Election Votes: https://electionlab.mit.edu/data
- Population Data: https://www.census.gov/data/tables/time-series/demo/popest/2010s-counties-detail.html
Ripser is used in this notebook to detect persistent topological features within a dataset. Another purpose of this notebook is to demonstrate how to use the Ripser function and what a persistence diagram can reveal and how to apply it to research.
%% Cell type:code id: tags:
``` python
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from sklearn.preprocessing import StandardScaler
from ripser import ripser
from ripser import Rips
from persim import plot_diagrams
%matplotlib inline
```
%% Cell type:code id: tags:
``` python
# import data
MI_df = pd.read_csv('mi_df.csv')
# seperate data by year
MI_00 = MI_df.loc[MI_df['year'] == 2000]
MI_04 = MI_df.loc[MI_df['year'] == 2004]
MI_08 = MI_df.loc[MI_df['year'] == 2008]
MI_12 = MI_df.loc[MI_df['year'] == 2012]
MI_16 = MI_df.loc[MI_df['year'] == 2016]
```
%% Cell type:code id: tags:
``` python
MI_00.head()
```
%% Output
year county FIPS dem_votes White Male White Female Black Male \
0 2000 Alcona 26001 46.101231 5839 5711 19
1 2000 Alger 26003 49.157370 4483 4305 601
2 2000 Allegan 26005 35.464158 51388 51528 808
3 2000 Alpena 26007 51.027348 15043 15878 61
4 2000 Antrim 26009 38.968404 11402 11434 49
Black Female Native Male Native Female Asian Male Asian Female \
0 6 45 34 10 13
1 8 183 201 19 19
2 789 313 372 332 374
3 48 58 75 46 60
4 40 137 139 30 33
Age 18-44 Age 45-64 Age >=65 Income Per Capita
0 2977 3640 2842 21417
1 3524 2588 1703 22888
2 40130 23455 11753 26373
3 10691 7803 5377 30834
4 7343 6200 4051 30834
%% Cell type:code id: tags:
``` python
from urllib.request import urlopen
import json
with urlopen('https://raw.githubusercontent.com/plotly/datasets/master/geojson-counties-fips.json') as response:
counties = json.load(response)
import plotly.express as px
fig = px.choropleth_mapbox(MI_08, geojson=counties, locations='FIPS', color='dem_votes',
color_continuous_scale="Blues",
range_color=(0, 100),
mapbox_style="carto-positron",
zoom=3, center = {"lat": 37.0902, "lon": -95.7129},
opacity=0.5,
labels={'bbbunemp':'Percent of Democrate Votes'}
)
fig.update_layout(margin={"r":0,"t":0,"l":0,"b":0})
fig.show()
```
%% Cell type:markdown id: tags:
### Persistent Homology
Before exploring the election dataset, we will discuss some applications of the persistence diagram provided by the Ripser function.
- Classification
- Feature Extraction
- Nonlinear Time Series Analysis
- Computational Neuroscience
- Computer Vision
In this particular notebook, we are only examining the shape of the dataset. No further Ripser application is made, although it is very possible.
%% Cell type:code id: tags:
``` python
from sklearn import preprocessing
x = MI_00[['dem_votes','White Male', 'White Female', 'Black Male', 'Black Female', 'Native Male',
'Native Female', 'Asian Male', 'Asian Female', 'Age 18-44', 'Age 45-64',
'Age >=65', 'Income Per Capita']]
min_max_scaler = preprocessing.MinMaxScaler()
x_scaled = min_max_scaler.fit_transform(x)
dataset_00 = pd.DataFrame(x_scaled)
dataset_00['county'] = MI_00['county']
dataset_00.head()
```
%% Output
0 1 2 3 4 5 6 \
0 0.435827 0.008527 0.008218 0.000032 0.000010 0.007958 0.005700
1 0.506787 0.006066 0.005738 0.001455 0.000015 0.034104 0.034548
2 0.188848 0.091196 0.089033 0.001962 0.001654 0.058734 0.064087
3 0.550205 0.025232 0.026151 0.000135 0.000099 0.010421 0.012783
4 0.270212 0.018623 0.018312 0.000105 0.000082 0.025388 0.023838
7 8 9 10 11 12 county
0 0.000296 0.000418 0.002920 0.006897 0.009598 0.087966 Alcona
1 0.000629 0.000645 0.003603 0.004458 0.005003 0.157987 Alger
2 0.012202 0.014122 0.049340 0.052836 0.045548 0.323877 Allegan
3 0.001627 0.002202 0.012558 0.016549 0.019825 0.536224 Alpena
4 0.001035 0.001177 0.008375 0.012832 0.014475 0.536224 Antrim
%% Cell type:code id: tags:
``` python
df_00 = dataset_00[[0,1,2,3,4,5,6,7,8,9,10,11,12]]
df_00.shape
```
%% Output
(83, 13)
%% Cell type:markdown id: tags:
There is not one single "correct" default parameters one should use. However, when performing an exploratory analysis with no prior background on the dataset and one does not have an idea of what they should expect, it is reasonable to use various combinations of the following parameters:
- `maxdim` 1 and 2
- `coeff` 2, 3, 17, and 19
%% Cell type:code id: tags:
``` python
# build persistent homology
result = ripser(df_00, maxdim = 2, coeff=19, do_cocycles=True)
diagrams = result['dgms']
D = result['dperm2all']
# plot maximum persistence point in the diagram
dgm1 = diagrams[1]
idx = np.argmax(dgm1[:, 1] - dgm1[:, 0])
plot_diagrams(diagrams, show = False)
plt.scatter(dgm1[idx, 0], dgm1[idx, 1], 20, 'k', 'x')
plt.title("Max 1D birth = %.3g, death = %.3g"%(dgm1[idx, 0], dgm1[idx, 1]))
plt.show()
```
%% Output
%% Cell type:markdown id: tags:
Even after using different parameter combinations, the persistence diagram did not change. This indicates that the data may not have prominent topological structure. This is where my exploratory analysis ends. I can, however, use Ripser to perform classification. That is, I can attempt to classify varying demographics and voting results based on income per capita. In fact, my dataset might be perfect for TDA due to its structure: 83 x 13, i.e. too many features and not enough data points. In short, although my exploratory analysis was short lived, I can still use TDA methods on this dataset.
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Topological_ML/tda_function.py
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"""
This file contains all of the functions used within the notebooks.
Date:
Author:
Date: April 24, 2020
Author: Shawk Masboob
The function `uniform_sampling` was borrowed from Luis Polancocontreras,
a PhD candidate in the CMSE program at Michigan State University.
It was slightly tweaked to fit this project.
"""
import sklearn
from sklearn.linear_model import LinearRegression
from sklearn import ensemble
import kmapper as km
import pandas as pd
import numpy as np
import pandas as pd
def numpy_to_pandas(sklearn_data):
"""
Converts scikit-learn numpy data into pandas dataframe.
Input: name of dataframe
Output: pandas dataframe
"""Converts scikit-learn numpy data into pandas dataframe
Args:
sklearn_data (array): name of dataframe
Returns:
data: pandas dataframe
"""
data = pd.DataFrame(data=sklearn_data.data, columns=sklearn_data.feature_names)
data['target'] = pd.Series(sklearn_data.target)
return data
def linear_regression(feature, predictor):
"""
Ordinary least squares Linear Regression.
input: x = independent variables
y = dependent variable
output: R^2
"""
model = LinearRegression()
model.fit(feature, predictor)
return model.score(feature, predictor)
def lens_1d(x_array, proj='l2norm', random_num=1729, verbosity=0):
"""Creates a L^2-Norm for features. This lens highlights expected features in the data.
Args:
x_array (array): features of dataset </br>
proj (string): projection type </br>
random_num: random state </br>
verbosity: verbosity </br>
Returns:
lens: Isolation Forest, L^2-Norm </br>
mapper: projected features </br>
def lens_1d(features, random_num, verbosity):
"""
input:
output:
"""
model = sklearn.ensemble.IsolationForest(random_state=random_num)
model.fit(features)
lens1 = model.decision_function(features).reshape((features.shape[0], 1))
if not isinstance(x_array, np.ndarray):
print("your input is not an array")
return None, None
if isinstance(x_array, np.ndarray) and len(x_array.shape) != 2:
print('your input needs to be a 2d array')
return None, None
proj_type = ['sum', 'mean', 'median', 'max', 'min', 'std', 'dist_mean',
'l2norm', 'knn_distance_n']
if proj not in proj_type:
print("you may only use the following projections:", proj_type)
return None, None
# Create a custom 1-D lens with Isolation Forest
model = ensemble.IsolationForest(random_state=random_num)
model.fit(x_array)
lens1 = model.decision_function(x_array).reshape((x_array.shape[0], 1))
# Create another 1-D lens with L2-norm
mapper = km.KeplerMapper(verbose=verbosity)
lens2 = mapper.fit_transform(features, projection="l2norm")
lens2 = mapper.fit_transform(x_array, projection=proj)
# Combine lenses pairwise to get a 2-D lens i.e. [Isolation Forest, L^2-Norm] lens
lens = np.c_[lens1, lens2]
return lens
return lens, mapper
def uniform_sampling(dist_matrix, n_sample):
"""Given a distance matrix retunrs an subsamplig that preserves the distribution
of the original data set and the covering radious corresponding to
the subsampled set.
Args:
dist_matrix (array): Distance matrix </br>
n_sample (int): Size of subsample set </br>
Returns:
list_subsample (array): List of indices corresponding to the subsample set </br>
distance_to_l: Covering radious for the subsample set </br>
def county_crosstab(data, county, year, index, columns):
"""
input:
output:
"""
subset_df = data[data.year == year]
sub_df = subset_df[subset_df.county == county]
crosstab = pd.crosstab(index=sub_df[index], columns=sub_df[columns])
return crosstab
if not isinstance(dist_matrix, np.ndarray):
print("your input is not an array")
return None, None
if isinstance(dist_matrix, np.ndarray) and len(dist_matrix.shape) != 2:
print('your input needs to be a 2d array')
return None, None
n_subsample = int(n_sample)
if n_subsample <= 0:
print("Sampling size should be a positive integer.")
return None, None
num_points = dist_matrix.shape[0]
list_subsample = np.random.choice(num_points, n_subsample)
dist_to_l = np.min(dist_matrix[list_subsample, :], axis=0)
distance_to_l = np.max(dist_to_l)
return list_subsample, distance_to_l
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from Topological_ML import TDA_Prediction as tdap
from sklearn.datasets import fetch_california_housing
from sklearn.model_selection import train_test_split
from sklearn.linear_model import LinearRegression
import kmapper as km
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import sklearn
from sklearn import ensemble
def test_data_summary():
data = pd.DataFrame({"A": [1,2,3,4,5,6,7,8,9,10]})
correct_response = {"head": [1,2,3,4,5,6,7,8,9,10], "shape": [10, 1], "describe": 0}
values = tdap.data_summary(data, 5)
assert values == correct_response
return
def test_linear_regression():
a = pd.DataFrame({"A": [1,2,3,4,5,6,7,8,9,10]})
b = pd.DataFrame({"B": [2,4,6,8,10,12,14,16,18,20]})
correct_response = 1
values = tdap.linear_regression(a, b)
assert values == correct_response
return
def test_lens_1d():
a = pd.DataFrame({"A": [0,0]})
correct_response = np.array([[0., 0.],[0., 0.]])
values = tdap.lens_1d(a,123,1)
assert values == correct_response
return
Topological_ML/test/test_tda_functions.py 0 → 100644
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'''
This file contains the functions from tda_functions.py that will be tested.
'''
import numpy as np
import scipy.spatial.distance as distance
from Topological_ML import tda_function as tda
def test_lens_1d_pass():
'''
Testing whether the function works given correct parameters.
'''
data = np.ones((5, 2))
test, _ = tda.lens_1d(data, proj="sum")
assert isinstance(test, np.ndarray)
def test_lens_1d_fail_1():
'''
Testing whether the function fails given incorrect projection parameter.
'''
data = np.ones((5, 2))
test, _ = tda.lens_1d(data, proj="Sum")
assert test is None
def test_lens_1d_fail_2():
'''
Testing whether the function fails given incorrect feature (data) parameter.
'''
data = np.ones(5)
test, _ = tda.lens_1d(data, proj="sum")
assert test is None
def test_uniform_sampling_pass():
'''
Testing whether the function works given correct parameters.
'''
x_array = np.array([[1, 1], [1, 2], [2, 3]])
dm_x = distance.cdist(x_array, x_array)
test, _ = tda.uniform_sampling(dm_x, 1)
assert isinstance(test, np.ndarray)
def test_uniform_sampling_fail_1():
'''
Testing whether the function fails given incorrect distance matrix parameter.
'''
x_array = np.ones(5)
test, _ = tda.uniform_sampling(x_array, 1)
assert test is None
def test_uniform_sampling_fail_2():
'''
Testing whether the function fails given incorrect sampling size parameter.
'''
x_array = np.array([[1, 1], [1, 2], [2, 3]])
dm_x = distance.cdist(x_array, x_array)
test, _ = tda.uniform_sampling(dm_x, -2)
assert test is None
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environment.yml
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......@@ -6,7 +6,6 @@ dependencies:
- matplotlib
- jupyter
- cython
- pytest
- numpy
- selenium
- pandas
......@@ -15,6 +14,14 @@ dependencies:
- hypothesis
- requests
- plotly
- pdoc3
- pylint
- pytest
- autopep8
- pip:
- ripser
- kmapper
- persim
- python-igraph
- plotly
- ipywidgets
\ No newline at end of file
makefile
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......@@ -22,13 +22,13 @@ init:
conda env create --prefix ./envs --file environment.yml
doc:
pdoc --force --html --output-dir ./docs Topological_ML
pdoc3 --force --html --output-dir ./docs Topological_ML
lint:
pylint Topological_ML
pylint -v Topological_ML
test:
pytest Topological_ML
pytest -v --disable-warnings Topological_ML
.PHONY: init doc lint test
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year,county,FIPS,dem_votes,White Male,White Female,Black Male,Black Female,Native Male,Native Female,Asian Male,Asian Female,Age 18-44,Age 45-64,Age >=65,Income Per Capita
2000,Alcona,26001,46.10123119,5839,5711,19,6,45,34,10,13,2977,3640,2842,21417
2000,Alger,26003,49.15737005,4483,4305,601,8,183,201,19,19,3524,2588,1703,22888
2000,Allegan,26005,35.4641582,51388,51528,808,789,313,372,332,374,40130,23455,11753,26373
2000,Alpena,26007,51.02734771,15043,15878,61,48,58,75,46,60,10691,7803,5377,30834
2000,Antrim,26009,38.968404,11402,11434,49,40,137,139,30,33,7343,6200,4051,30834
2000,Arenac,26011,51.85758514,8435,8267,300,24,107,91,17,37,5942,4436,2867,19569
2000,Baraga,26013,43.26328801,3589,3528,529,16,569,611,21,12,3200,2232,1435,22839
2000,Barry,26015,38.33235236,28085,28130,131,87,166,162,61,109,20688,14056,6717,23381
2000,Bay,26017,56.05245928,51923,55158,927,828,405,349,265,337,40077,26941,16295,26999
2000,Benzie,26019,45.94454522,7775,7937,37,25,146,142,10,18,5344,4163,2817,26999
2000,Berrien,26021,44.09705362,64824,67616,12464,14557,444,419,1031,1116,58072,38734,23454,27694
2000,Branch,26023,43.35233899,22254,21792,703,612,154,119,120,121,17489,10657,6018,28156
2000,Calhoun,26025,50.95237207,57889,61173,7830,8345,549,515,843,870,51211,32112,18871,32720
2000,Cass,26027,45.51232367,23390,23374,1721,1741,290,308,152,170,17797,13339,6965,36244
2000,Charlevoix,26029,41.3994656,12644,12887,35,44,243,233,41,44,8861,6635,3908,36244
2000,Cheboygan,26031,44.58899097,12662,12869,61,44,396,435,30,33,8476,7029,4749,24922
2000,Chippewa,26033,45.84052965,16111,14063,2230,75,2988,2885,139,102,16843,8642,4893,26692
2000,Clare,26035,51.43160995,15221,15693,88,45,128,135,35,53,10015,8319,5410,31291
2000,Clinton,26037,42.59094378,31653,32101,323,217,159,162,180,225,23696,16028,7082,33724
2000,Crawford,26039,45.47677262,7012,6926,196,33,65,33,23,20,4694,3731,2388,33724
2000,Delta,26041,47.3249807,18322,19002,42,24,520,495,59,78,13000,9826,6547,25486
2000,Dickinson,26043,44.3882872,13347,13766,33,29,81,79,54,71,9161,6429,4963,26293
2000,Eaton,26045,48.34215021,46821,49350,2798,3171,279,274,667,640,39299,25701,11842,30678
2000,Emmet,26047,38.7888707,14719,15360,137,47,576,516,70,92,11044,7985,4511,35920
2000,Genesee,26049,64.26257816,163774,173116,42840,49867,1517,1744,1973,2134,168067,98449,50852,35920
2000,Gladwin,26051,49.24885118,12824,12990,38,29,77,84,35,50,7984,7281,4793,21504
2000,Gogebic,26053,50.85678549,8124,8335,281,13,218,200,23,25,5593,4204,3893,22485
2000,Grand Traverse,26055,39.12712026,37138,39120,283,152,398,438,224,251,29197,18812,10203,26856
2000,Gratiot,26057,44.02693603,20112,20117,1681,85,168,126,110,73,17411,9229,5751,30609
2000,Hillsdale,26059,38.25538933,22911,23175,149,98,99,99,72,95,17150,11041,6221,30609
2000,Houghton,26061,41.87587425,18317,16279,310,130,123,114,418,273,15053,7528,5561,20096
2000,Huron,26063,43.63693865,17656,18017,62,53,54,69,59,77,11339,8962,7009,22160
2000,Ingham,26065,59.40280578,112179,120371,16168,17632,978,1030,5699,5658,131713,56379,26321,26555
2000,Ionia,26067,40.5240212,29674,28286,2894,125,284,167,178,104,26163,12758,6198,29015
2000,Iosco,26069,50.62256809,13166,13648,82,67,108,111,62,90,7825,7485,5915,29015
2000,Iron,26071,50.39291088,6252,6517,146,14,73,78,9,17,3762,3347,3305,29285
2000,Isabella,26073,50.43143829,28032,30910,782,742,1012,990,486,490,33804,11067,5739,29026
2000,Jackson,26075,46.75721449,71593,71698,8444,5129,419,382,511,503,60901,36721,20412,32719
2000,Kalamazoo,26077,50.2848724,100284,107186,12173,13161,584,705,2563,2352,103697,50680,27227,36672
2000,Kalkaska,26079,41.9286578,8241,8148,34,26,81,61,23,26,6000,4099,2295,36672
2000,Kent,26081,39.10852141,248240,255122,27486,29371,1874,1969,5901,6215,239599,114174,59721,26570
2000,Keweenaw,26083,42.1875,1141,1052,72,1,3,1,2,2,640,665,463,28367
2000,Lake,26085,56.85368537,5034,4745,816,575,72,74,7,15,3488,3135,2237,32188
2000,Lapeer,26087,43.62603878,43599,43051,682,107,189,225,189,229,33984,21122,8468,35192
2000,Leelanau,26089,40.39215686,10150,10145,38,33,400,429,23,39,6332,6031,3696,35192
2000,Lenawee,26091,47.03426727,47294,48314,1778,640,259,239,236,309,37269,23555,12558,24757
2000,Livingston,26093,39.20073008,78415,77108,641,217,448,406,504,606,60445,39170,13202,26587
2000,Luce,26095,39.24466338,3052,2906,543,7,262,197,31,8,2730,1693,1080,29840
2000,Mackinac,26097,43.63479759,4954,4947,16,12,980,990,19,20,3718,3399,2180,33339
2000,Macomb,26099,51.24076108,364661,380664,11804,11535,1603,1647,9355,9577,311334,181419,107964,33339
2000,Manistee,26101,51.07789855,11809,11850,420,36,222,163,61,48,8103,6492,4440,27102
2000,Marquette,26103,55.21011396,30896,31215,823,149,579,592,139,213,26119,15922,8754,30586
2000,Mason,26105,44.12020561,13638,14075,187,94,138,133,34,51,9401,7339,4753,35920
2000,Mecosta,26107,43.83523518,19466,18750,778,909,163,181,205,205,17415,8761,5351,37777
2000,Menominee,26109,45.39798538,12201,12320,28,24,332,314,26,36,8538,6308,4388,37777
2000,Midland,26111,42.16826085,39311,40883,534,480,206,174,652,673,31329,19359,9944,21821
2000,Missaukee,26113,32.54419192,7200,7180,14,28,33,45,13,23,5037,3421,2148,23165
2000,Monroe,26115,52.16133565,70331,71548,1668,1488,276,257,343,453,55376,34630,16282,25467
2000,Montcalm,26117,43.12592393,29834,29464,1337,134,265,204,118,128,23594,13793,7457,29842
2000,Montmorency,26119,43.75127838,5057,5228,15,15,12,27,3,7,2758,3040,2477,29842
2000,Muskegon,26121,55.77158175,70546,71868,12545,12779,910,836,448,464,64069,37520,21897,25253
2000,Newaygo,26123,40.24428601,23326,23441,349,287,188,213,69,99,16719,11177,6141,27772
2000,Oakland,26125,50.61941964,498246,513869,58116,68009,2194,2342,27046,26343,473034,286955,135282,31387
2000,Oceana,26127,43.73929591,13283,13047,65,54,171,186,41,55,9191,6376,3772,33887
2000,Ogemaw,26129,50.98937721,10628,10783,31,16,69,88,48,47,6653,5873,4095,33887
2000,Ontonagon,26131,37.98294029,3924,3793,6,1,43,42,4,12,2182,2358,1715,25710
2000,Osceola,26133,41.35866199,11327,11604,73,50,71,68,21,34,7995,5649,3303,28273
2000,Oscoda,26135,43.17713697,4571,4728,7,6,34,38,3,5,2657,2643,1911,30947
2000,Otsego,26137,39.77519227,11471,11637,35,31,102,80,33,54,8304,5645,3226,34954
2000,Ottawa,26139,27.33072953,113067,116693,1673,1507,551,537,2687,2844,98492,48135,24210,34954
2000,Presque Isle,26141,46.97189221,7092,7118,29,28,37,48,9,17,4135,4006,3233,27565
2000,Roscommon,26143,50.96252872,12384,12775,52,49,84,88,24,38,6839,7488,6090,32765
2000,Saginaw,26145,55.25837981,80338,85690,19025,21757,550,569,962,1008,76764,49023,28383,37395
2000,St. Clair,26147,49.57264957,78223,80587,2006,1968,511,518,364,444,62166,38267,20167,40577
2000,St. Joseph,26149,39.91620112,29625,30322,908,908,161,150,199,207,23041,14161,8100,40577
2000,Sanilac,26151,39.47789613,21806,22215,120,49,86,108,64,68,15368,10311,6875,22438
2000,Schoolcraft,26153,49.36954413,3994,4106,146,6,297,325,24,17,2919,2314,1660,24432
2000,Shiawassee,26155,49.52769977,34777,36051,124,100,225,209,99,129,26862,17019,8606,27766
2000,Tuscola,26157,45.07856015,28258,28657,516,181,233,202,84,120,21071,14107,7487,31287
2000,Van Buren,26159,48.25801035,35153,35505,2126,2291,422,439,142,164,27369,18167,9371,31287
2000,Washtenaw,26161,62.28847066,128186,129766,20961,21577,784,837,11372,10889,159176,67182,26430,20202
2000,Wayne,26163,70.39943724,552118,567990,408849,476397,5281,5790,20657,20173,801006,431996,248334,22940
2000,Wexford,26165,42.46870266,14881,15148,62,55,123,125,61,82,10883,7177,4295,26119
2004,Alcona,26001,44.422095,5744,5598,15,8,38,32,9,15,2595,3861,3072,29651
2004,Alger,26003,50.81688945,4373,4225,605,12,202,225,20,18,3180,2917,1814,29651
2004,Allegan,26005,36.26093636,53201,53573,952,871,379,380,392,477,39525,27624,12344,19874
2004,Alpena,26007,49.14410828,14794,15545,68,56,58,85,61,68,9755,8664,5389,21560
2004,Antrim,26009,37.70723366,11855,11969,53,42,139,146,27,32,7193,7039,4459,24639
2004,Arenac,26011,50.03068614,8439,8171,235,28,107,97,15,36,5439,4870,3059,28020
2004,Baraga,26013,45.64201265,3548,3457,599,18,590,639,21,12,3084,2465,1451,28020
2004,Barry,26015,37.76961603,29165,29001,178,111,164,169,91,126,20237,16002,7311,29805
2004,Bay,26017,54.95690037,51678,54335,1069,973,395,367,280,356,37539,29522,16473,28418
2004,Benzie,26019,45.33981587,8468,8536,42,39,147,157,10,21,5403,4872,3184,34136
2004,Berrien,26021,44.43332161,63755,66439,12084,14075,475,470,1174,1270,54154,41930,23597,37249
2004,Branch,26023,39.37485946,22855,21921,1056,436,162,118,118,125,16949,11850,6334,37249
2004,Calhoun,26025,48.22373516,58181,61285,8202,8479,590,551,1071,1084,49794,35165,19201,20631
2004,Cass,26027,42.3847829,23939,23923,1734,1692,309,335,163,195,16988,14763,7834,20971
2004,Charlevoix,26029,41.08871835,12854,13045,51,51,260,250,40,50,8237,7711,4207,23153
2004,Cheboygan,26031,43.24186622,13004,13103,70,65,438,482,29,37,8299,7891,5008,27292
2004,Chippewa,26033,44.12251149,15900,13949,2371,96,3174,3055,147,111,15960,9809,5054,27292
2004,Clare,26035,49.63047186,15547,15777,100,59,124,126,38,50,9787,8983,5873,24039
2004,Clinton,26037,41.31885141,33733,34441,682,634,184,192,335,404,25758,18253,7822,26504
2004,Crawford,26039,43.76312474,7192,7093,132,36,58,32,21,27,4352,4406,2600,30608
2004,Delta,26041,49.21567599,18106,18662,54,42,560,552,61,86,12017,10901,6668,33708
2004,Dickinson,26043,42.21458458,13183,13675,43,38,93,79,51,69,8370,7389,5095,33708
2004,Eaton,26045,46.04109291,47806,50201,3360,3861,287,298,878,842,38690,29065,12875,26075
2004,Emmet,26047,39.85330073,15226,15962,133,72,627,625,80,99,10775,9263,4696,29667
2004,Genesee,26049,60.47671109,166111,174684,43624,50413,1527,1690,2132,2353,161521,109531,52773,34688
2004,Gladwin,26051,48.37184473,13321,13341,50,31,68,83,32,45,7819,7941,5277,38950
2004,Gogebic,26053,52.90809,8084,7891,506,15,214,217,22,27,5490,4603,3764,38950
2004,Grand Traverse,26055,39.94573542,39211,41094,670,239,465,489,276,324,29363,22540,11143,27900
2004,Gratiot,26057,42.86212306,20106,20039,1878,111,141,118,97,93,16786,10099,5809,29971
2004,Hillsdale,26059,35.74547097,23226,23499,163,113,93,113,74,111,16475,12404,6495,32912
2004,Houghton,26061,43.0921895,18520,16124,251,121,124,116,561,337,15185,8060,5421,34478
2004,Huron,26063,44.0982659,17208,17418,71,56,49,67,63,82,10380,9716,7007,34478
2004,Ingham,26065,58.41229077,112291,119379,17345,18760,1051,1151,6794,6815,132204,62553,26614,29119
2004,Ionia,26067,39.04576793,31193,29174,3292,168,274,164,167,130,26335,15041,6603,34155
2004,Iosco,26069,47.31562996,12957,13360,87,89,116,104,54,93,6993,8193,6297,40374
2004,Iron,26071,49.93011337,6025,6145,110,16,67,69,8,20,3268,3706,3191,44081
2004,Isabella,26073,51.20391896,29550,32159,924,951,1155,1165,552,611,36086,12434,5862,44081
2004,Jackson,26075,43.66397388,73241,72963,8604,5325,439,367,593,608,59616,41369,20828,26887
2004,Kalamazoo,26077,51.81900193,101385,106906,13226,13987,673,767,2861,2700,101963,56148,27672,27983
2004,Kalkaska,26079,38.54708087,8620,8493,45,32,88,75,18,29,5788,4812,2479,30302
2004,Kent,26081,40.57790427,250902,258555,29781,31865,2096,2159,6875,7321,234969,131657,60754,33167
2004,Keweenaw,26083,44.64918498,1068,1011,41,1,1,1,0,2,582,718,412,33167
2004,Lake,26085,51.66087292,5257,5061,682,599,66,70,8,14,3325,3563,2485,20421
2004,Lapeer,26087,41.44173044,44895,44320,839,182,212,231,178,268,32489,24637,9459,23477
2004,Leelanau,26089,43.88651041,10350,10462,43,43,416,472,29,44,5721,7059,4176,28965
2004,Lenawee,26091,44.73978735,48400,48942,1903,781,290,274,275,351,36440,26345,12938,29647
2004,Livingston,26093,36.60811408,86471,85130,747,422,495,439,716,825,62499,47676,15971,29647
2004,Luce,26095,37.4015748,3005,2835,592,8,223,199,22,10,2553,1901,1089,21304
2004,Mackinac,26097,43.20306513,4803,4718,22,17,1024,1023,19,21,3358,3554,2263,23930
2004,Macomb,26099,49.24609491,368338,384821,20316,21611,1735,1775,12185,12637,308687,206540,110460,27938
2004,Manistee,26101,49.90849049,11990,12002,431,40,268,221,45,51,7715,7300,4598,31746
2004,Marquette,26103,54.23961124,31268,31545,917,203,657,649,160,221,25915,17739,9022,31746
2004,Mason,26105,43.80576883,13875,14254,188,114,146,165,39,61,8915,8194,5027,30164
2004,Mecosta,26107,44.3233945,20423,19864,712,817,176,195,178,188,17899,9703,5770,30377
2004,Menominee,26109,47.26659567,12064,12094,38,32,352,347,22,38,7751,7151,4334,35395
2004,Midland,26111,42.96180133,39762,41285,595,530,213,194,708,771,29781,21621,10855,39778
2004,Missaukee,26113,31.44833198,7534,7406,21,32,40,53,14,27,4860,4038,2348,39778
2004,Monroe,26115,49.06129773,72261,73638,1909,1743,294,288,425,559,54035,39723,17504,21127
2004,Montcalm,26117,43.38666364,30827,30425,1351,156,247,209,122,145,23161,15798,7962,23446
2004,Montmorency,26119,39.95633188,5117,5124,16,16,14,27,4,8,2603,3322,2518,27008
2004,Muskegon,26121,55.64183756,71315,72644,13049,12866,908,906,530,553,62733,42318,21983,31905
2004,Newaygo,26123,39.9602912,24019,23934,393,309,203,233,70,111,16358,12735,6603,31905
2004,Oakland,26125,50.21650263,488253,502856,65817,77781,2290,2422,32447,31946,444014,321276,139181,23492
2004,Oceana,26127,44.90014854,13545,13372,74,85,168,208,49,55,8984,7209,4017,25378
2004,Ogemaw,26129,48.87993251,10820,10919,39,20,72,89,46,48,6360,6574,4254,27532
2004,Ontonagon,26131,45.16363636,3795,3598,7,2,37,44,4,10,1936,2499,1742,29290
2004,Osceola,26133,40.36688957,11787,11830,101,63,76,74,26,33,7783,6369,3583,29290
2004,Oscoda,26135,41.08207244,4566,4647,10,6,30,32,2,6,2410,2898,1986,20813
2004,Otsego,26137,38.48814229,12007,12202,47,46,106,86,36,56,8232,6526,3628,24145
2004,Ottawa,26139,27.86206897,118491,122334,2119,2021,639,673,3271,3500,99635,56341,26337,27528
2004,Presque Isle,26141,46.29080119,7006,6975,32,30,42,46,10,22,3747,4337,3342,30565
2004,Roscommon,26143,48.04571751,12607,12813,56,58,88,82,26,41,6397,8299,6295,30565
2004,Saginaw,26145,53.78336534,79347,84094,19599,22176,545,566,1019,1143,73311,53092,28665,25698
2004,St. Clair,26147,45.83977494,80093,81937,2295,2135,527,505,427,538,60084,43904,20883,28563
2004,St. Joseph,26149,38.61053306,29519,30015,997,974,172,171,183,234,21745,15469,8360,35341
2004,Sanilac,26151,38.42554229,21853,22522,136,58,100,120,72,78,14552,11606,7246,40032
2004,Schoolcraft,26153,48.52406903,4040,4064,128,7,324,363,21,15,2689,2605,1766,40032
2004,Shiawassee,26155,46.51951058,35438,36497,242,147,226,210,112,162,25981,18953,8986,27694
2004,Tuscola,26157,45.07851535,28296,28611,525,222,205,177,77,117,19782,15608,7898,29345
2004,Van Buren,26159,47.80523901,35709,36070,1975,2144,496,485,168,194,26331,20625,9489,32329
2004,Washtenaw,26161,64.14694763,131939,133865,22253,22972,823,866,13532,13172,159997,77084,28571,34429
2004,Wayne,26163,69.95209822,529566,543041,393067,458327,5359,5920,24441,24109,735688,465577,235073,34429
2004,Wexford,26165,40.22666667,15515,15670,87,76,117,138,78,97,10821,8270,4555,21856
2008,Alcona,26001,45.96825397,5679,5488,11,10,39,33,6,20,2308,3859,3360,24015
2008,Alger,26003,53.0472103,4397,4150,595,20,219,230,20,16,2953,3111,1947,25773
2008,Allegan,26005,44.56349353,53743,54256,994,933,410,407,353,493,36761,31061,13877,28242
2008,Alpena,26007,51.95549562,14510,15149,81,52,63,96,83,85,8882,9172,5661,28242
2008,Antrim,26009,44.7478837,11695,11906,54,37,153,144,24,34,6439,7409,5016,20848
2008,Arenac,26011,52.18538056,8216,7897,152,31,91,118,11,31,4680,5194,3334,23309
2008,Baraga,26013,48.3057967,3508,3296,643,21,635,705,7,7,2940,2571,1486,26969
2008,Barry,26015,45.01004016,29546,29263,226,172,171,190,97,123,18973,17585,8181,30385
2008,Bay,26017,57.79831158,50992,53567,1254,1111,385,360,302,349,35375,31048,17243,30385
2008,Benzie,26019,53.76800158,8637,8669,59,54,132,136,16,30,5030,5338,3514,21651
2008,Berrien,26021,52.77803192,62701,65137,11971,13646,536,564,1350,1475,50828,44160,24830,25376
2008,Branch,26023,46.87691536,22650,21471,1456,237,140,112,113,126,15823,12763,6577,29639
2008,Calhoun,26025,54.75964128,56954,59916,8291,8516,579,579,1207,1271,46627,37097,19724,34950
2008,Cass,26027,52.08863215,23973,24222,1780,1707,340,300,157,205,16220,15693,8184,34950
2008,Charlevoix,26029,48.26878142,12534,12983,75,53,244,275,43,73,7449,8166,4624,21816
2008,Cheboygan,26031,49.26686217,12709,12804,94,82,468,491,34,56,7469,8204,5472,23112
2008,Chippewa,26033,49.7477357,15703,13636,2870,109,3334,3302,154,139,15482,10687,5429,26680
2008,Clare,26035,52.45993422,15154,15330,144,89,134,115,43,55,9045,9350,6082,28917
2008,Clinton,26037,50.35111122,34900,36075,894,908,179,204,538,604,25929,20386,9135,28917
2008,Crawford,26039,49.14310197,7098,7028,71,47,42,41,18,34,3923,4648,2844,25543
2008,Delta,26041,53.23157389,17802,18215,83,69,559,531,62,88,11022,11567,6945,27000
2008,Dickinson,26043,45.95982827,12886,13325,68,65,87,72,49,70,7582,8095,5102,29827
2008,Eaton,26045,54.27421348,47700,50258,3613,3880,309,324,950,987,36835,31375,14187,32261
2008,Emmet,26047,47.75926861,15253,15797,122,96,708,700,80,96,10053,9979,5236,32261
2008,Genesee,26049,66.51646655,161476,170275,43451,50043,1521,1672,2216,2428,149128,116047,56506,28748
2008,Gladwin,26051,50.76650489,12842,12801,61,34,66,72,33,47,7031,7956,5620,31842
2008,Gogebic,26053,58.82280203,7878,7507,624,37,190,223,12,28,5092,4990,3588,36803
2008,Grand Traverse,26055,48.4804269,40603,42600,917,303,549,573,314,350,28823,25420,12389,39662
2008,Gratiot,26057,52.24651403,20224,19746,2270,110,139,116,65,104,16232,10973,6161,39662
2008,Hillsdale,26059,43.85569899,23007,23218,192,134,90,112,87,111,15371,13167,7035,18798
2008,Houghton,26061,47.99383707,18657,16055,183,112,129,121,659,376,14936,8509,5349,20919
2008,Huron,26063,49.80060711,16440,16628,89,77,54,59,69,88,9229,10076,7132,26103
2008,Ingham,26065,66.91059746,109793,116531,18323,19424,1063,1148,7435,7598,127086,66077,28252,28884
2008,Ionia,26067,47.02294076,31441,29262,3565,184,252,176,147,140,25139,16885,7075,28884
2008,Iosco,26069,52.61301468,12829,13174,99,93,107,98,52,90,6379,8610,6645,31888
2008,Iron,26071,51.10336818,5854,5979,59,17,66,73,9,24,2914,3957,3132,34689
2008,Isabella,26073,59.78350479,30572,32701,1021,1044,1427,1363,575,625,36523,13717,6486,40985
2008,Jackson,26075,51.22177882,72259,72177,8664,5559,472,379,619,696,55987,44695,21879,45591
2008,Kalamazoo,26077,59.91291163,102395,107440,14420,15176,782,840,2899,2910,100145,60524,29703,45591
2008,Kalkaska,26079,45.50379198,8728,8517,54,39,88,75,15,30,5333,5301,2763,22358
2008,Kent,26081,50.26370937,251688,261050,32056,34024,2475,2431,7387,8123,227476,147116,64654,26173
2008,Keweenaw,26083,44.65592972,1060,1030,19,6,2,1,0,1,499,753,470,32201
2008,Lake,26085,56.26445644,5257,5009,618,604,57,62,5,17,2941,3900,2646,37441
2008,Lapeer,26087,48.44878974,44104,43790,896,229,237,244,165,249,29132,27077,11006,37441
2008,Leelanau,26089,51.45875603,10209,10376,48,56,434,514,43,51,5059,7423,4739,19421
2008,Lenawee,26091,52.57654966,48287,48565,2207,836,324,281,293,376,34694,28236,14083,20963
2008,Livingston,26093,43.23929713,88866,88441,647,468,516,452,800,981,58613,54810,19861,22972
2008,Luce,26095,44.42372249,2908,2677,666,10,209,190,10,10,2325,1968,1144,26190
2008,Mackinac,26097,48.08578237,4531,4477,40,38,1081,1052,11,18,2934,3692,2457,26190
2008,Macomb,26099,54.38950825,361733,378281,31450,35309,1782,1858,13322,14122,296389,227924,116873,28493
2008,Manistee,26101,56.76735975,11861,11713,676,52,302,275,29,52,7185,7901,4957,28758
2008,Marquette,26103,60.33926431,31667,31803,1013,261,706,675,154,260,25445,18988,9623,31415
2008,Mason,26105,52.23870623,13755,14118,185,129,181,183,48,69,8202,8832,5278,34953
2008,Mecosta,26107,49.62647909,20493,20077,698,695,187,201,164,168,17415,10205,6348,34953
2008,Menominee,26109,55.19564415,11737,11633,70,45,371,383,32,46,6854,7751,4472,29144
2008,Midland,26111,48.18219905,39309,40948,746,553,198,206,788,857,27876,23314,11918,37214
2008,Missaukee,26113,39.33758653,7513,7287,39,37,51,52,18,31,4473,4335,2477,42179
2008,Monroe,26115,52.21354514,72710,74355,2128,1919,329,327,454,584,51109,44074,19624,51748
2008,Montcalm,26117,49.84339032,31030,30271,1490,153,236,206,113,136,21966,17140,8571,51748
2008,Montmorency,26119,45.82379863,4918,4905,19,17,20,26,5,12,2312,3351,2583,26330
2008,Muskegon,26121,64.87115204,71331,72572,13564,13269,922,964,546,678,60139,46518,22913,28185
2008,Newaygo,26123,47.63376302,24032,23735,406,305,225,244,72,134,15251,13865,7234,29995
2008,Oakland,26125,57.36002784,471838,488734,73232,89058,2374,2517,35940,35852,413988,345666,152263,32964
2008,Oceana,26127,52.22176926,13308,13120,107,108,184,202,38,53,8145,7652,4420,32964
2008,Ogemaw,26129,51.22576967,10705,10854,50,28,72,92,37,47,5798,6910,4621,36054
2008,Ontonagon,26131,51.88704144,3499,3315,9,6,34,46,4,9,1528,2524,1754,36030
2008,Osceola,26133,44.83745844,11570,11669,132,90,63,83,25,30,7035,6795,3910,40653
2008,Oscoda,26135,44.85381507,4488,4382,12,12,30,27,3,9,2113,2906,2076,45322
2008,Otsego,26137,45.48683998,11795,12123,86,64,110,88,47,65,7462,7168,3968,45322
2008,Ottawa,26139,37.88667094,121700,126256,2469,2446,770,808,3494,3963,98950,63756,29248,18531
2008,Presque Isle,26141,50.79148472,6754,6732,40,36,52,41,17,29,3158,4581,3488,20976
2008,Roscommon,26143,51.28539358,12186,12290,65,62,92,87,27,47,5554,8460,6650,23011
2008,Saginaw,26145,58.80527995,76611,80944,19179,21644,599,617,1130,1242,68012,55168,29993,26079
2008,St. Clair,26147,51.35141959,78618,80424,2522,2300,510,510,465,610,54885,47732,22771,26079
2008,St. Joseph,26149,48.88130752,29276,29865,1058,1039,184,205,198,258,20332,16619,8851,26556
2008,Sanilac,26151,45.86332759,21579,21990,151,85,108,110,69,85,13351,12550,7529,27818
2008,Schoolcraft,26153,51.48514851,3819,3836,26,9,373,394,6,8,2238,2772,1714,31158
2008,Shiawassee,26155,54.38665358,34704,35614,301,200,212,208,125,159,23754,20155,9687,35716
2008,Tuscola,26157,49.56502588,27570,27612,505,255,188,183,72,127,17888,16360,8457,35716
2008,Van Buren,26159,54.47511869,35432,35723,1868,1982,518,532,186,260,24616,22049,10092,33164
2008,Washtenaw,26161,70.76477857,130826,133445,22771,24184,867,907,14233,14362,152802,83356,32705,33575
2008,Wayne,26163,75.03805417,501227,515624,362573,422073,5441,6047,25705,26368,663209,482521,230170,36037
2008,Wexford,26165,47.8441289,16011,16082,127,97,114,139,85,110,10493,9118,5018,37898
2012,Alcona,26001,40.90683435,5292,5135,19,23,35,35,7,24,1991,3607,3522,37898
2012,Alger,26003,48.70101277,4275,3980,652,45,229,216,26,19,2733,3108,2073,23098
2012,Allegan,26005,40.0662443,53614,53948,1032,974,476,483,390,531,35029,32563,15449,25195
2012,Alpena,26007,47.29544306,14075,14521,116,93,75,95,92,94,8228,9161,5934,29579
2012,Antrim,26009,39.21222359,11307,11440,66,65,145,144,33,46,5747,7376,5501,31835
2012,Arenac,26011,47.48899819,7726,7396,56,57,98,107,19,38,4209,5018,3304,31835
2012,Baraga,26013,45.75581395,3442,3186,659,55,674,682,12,11,2847,2581,1581,24166
2012,Barry,26015,40.82640517,29121,28789,266,197,189,189,117,143,17697,17993,9358,26473
2012,Bay,26017,52.80935061,50432,52535,1311,1149,384,386,327,406,34070,31510,18313,31969
2012,Benzie,26019,48.00204918,8349,8469,85,70,132,157,29,40,4543,5416,3922,34311
2012,Berrien,26021,46.6905712,62197,64172,12117,13554,618,607,1496,1660,49430,44649,26617,34311
2012,Branch,26023,40.78947368,21379,20820,874,139,149,125,130,153,14057,12270,6922,23880
2012,Calhoun,26025,50.81076389,55537,58504,8233,8363,612,588,1308,1460,44534,37560,20731,26098
2012,Cass,26027,43.10561798,23555,23678,1764,1646,359,351,201,233,15171,15934,9101,30228
2012,Charlevoix,26029,42.60707368,12509,12807,101,95,253,276,47,74,7035,8326,5291,33653
2012,Cheboygan,26031,44.45376229,12162,12255,137,116,485,476,46,66,6799,8118,5928,33653
2012,Chippewa,26033,46.16985304,15306,13608,2718,163,3370,3411,174,207,14806,10654,5877,19530
2012,Clare,26035,47.56115864,15082,15064,169,104,141,129,40,63,8719,9413,6402,21081
2012,Clinton,26037,46.83453052,35804,36716,1007,860,197,213,614,716,25461,21861,10566,24156
2012,Crawford,26039,44.43455031,6898,6754,67,61,50,51,21,44,3557,4642,3061,27244
2012,Delta,26041,46.63009404,17525,17781,136,112,562,521,76,120,10340,11598,7340,27244
2012,Dickinson,26043,39.17721519,12729,12895,93,90,113,88,70,87,7357,8381,5074,23513
2012,Eaton,26045,51.58565884,47235,49702,3960,4105,310,346,1126,1118,35431,31832,16391,25985
2012,Emmet,26047,41.33768166,15175,15646,186,141,723,710,94,117,9776,10072,5841,31304
2012,Genesee,26049,64.23655036,155301,163283,42727,48839,1525,1638,2264,2477,139017,116800,61453,35389
2012,Gladwin,26051,46.37307785,12621,12518,85,61,74,77,37,57,6628,7810,6109,35389
2012,Gogebic,26053,54.09224207,7693,7104,689,49,219,231,20,32,4828,5035,3554,31908
2012,Grand Traverse,26055,44.03172393,41891,43766,1105,390,635,650,335,398,29246,26618,14327,37276
2012,Gratiot,26057,48.0095893,19773,19172,2380,142,159,137,83,109,15560,11209,6486,43300
2012,Hillsdale,26059,37.73164127,22579,22816,220,176,113,133,83,135,14601,13378,7721,45270
2012,Houghton,26061,45.34906981,18774,16091,242,155,138,128,701,426,14971,8496,5649,45270
2012,Huron,26063,42.53458627,15854,16053,117,106,58,64,86,100,8602,10084,7244,20296
2012,Ingham,26065,64.08646643,108729,115613,18635,19959,1150,1274,8563,8708,126453,66702,31755,22087
2012,Ionia,26067,43.49267754,30794,28902,3111,262,254,228,155,167,23408,17410,7799,24979
2012,Iosco,26069,47.46407117,12271,12497,130,117,122,120,81,104,5983,8124,6967,28252
2012,Iron,26071,45.45762138,5578,5719,40,42,69,76,10,28,2602,3881,3152,28252
2012,Isabella,26073,54.69418575,30930,32903,1109,1217,1525,1483,689,715,36868,14299,7145,29749
2012,Jackson,26075,47.08669223,71734,70909,8996,5919,462,378,722,788,53908,45779,23985,32096
2012,Kalamazoo,26077,56.73264154,105034,109204,15626,16490,814,893,3478,3546,103382,62050,32577,35047
2012,Kalkaska,26079,40.03425915,8493,8213,79,54,97,82,33,39,5025,5223,3078,37510
2012,Kent,26081,46.10880888,256721,265582,34182,35745,2783,2694,8325,9090,228752,156950,71570,37510
2012,Keweenaw,26083,42.92035398,1099,1052,7,4,2,1,0,1,472,717,593,19848
2012,Lake,26085,52.52910861,5205,4970,576,555,66,56,8,22,2719,3854,2921,22997
2012,Lapeer,26087,44.1946861,43076,42834,958,276,265,260,190,274,26769,28157,12937,25356
2012,Leelanau,26089,46.77430827,10013,10161,67,93,435,479,52,65,4912,7144,5478,28747
2012,Lenawee,26091,49.34847146,47132,47285,2325,875,363,322,294,382,32892,28351,15633,28747
2012,Livingston,26093,38.24910842,89301,89199,758,580,493,455,840,1108,55906,58321,24219,19015
2012,Luce,26095,38.54531311,2804,2497,735,27,194,193,11,14,2219,1902,1238,21185
2012,Mackinac,26097,43.84195735,4421,4242,105,85,1100,1061,25,27,2787,3747,2587,25298
2012,Macomb,26099,52.01323235,355306,370568,40619,47735,1815,1985,14830,15894,288099,243636,126858,28088
2012,Manistee,26101,53.01392301,11602,11409,816,96,328,308,39,61,6838,7910,5378,28088
2012,Marquette,26103,57.10727909,32163,32288,1102,301,749,721,186,300,25958,18946,10516,24019
2012,Mason,26105,47.49238016,13774,13993,197,160,176,177,72,94,8063,8745,5778,25340
2012,Mecosta,26107,45.02426457,20657,20498,765,737,206,196,212,186,17605,10569,6908,28347
2012,Menominee,26109,48.51008699,11446,11298,96,68,352,358,42,56,6363,7769,4846,31740
2012,Midland,26111,42.18134352,39172,40652,781,600,224,229,929,1063,27316,24451,12939,31740
2012,Missaukee,26113,32.77129269,7476,7224,58,56,54,57,28,37,4356,4415,2713,22075
2012,Monroe,26115,50.49858838,71436,73469,2061,1990,341,343,485,612,47914,45739,21937,23838
2012,Montcalm,26117,45.62692108,30757,29774,1539,221,243,226,130,179,20955,17845,9530,26735
2012,Montmorency,26119,41.16937914,4768,4612,40,25,22,29,5,16,2069,3230,2699,30250
2012,Muskegon,26121,58.99628253,69538,71206,12815,13186,1002,1012,584,744,56671,47634,24496,30250
2012,Newaygo,26123,41.19896153,23299,23141,408,320,240,239,87,125,14332,14186,7929,48458
2012,Oakland,26125,54.06558474,469885,485983,80895,100169,2523,2728,39369,39858,408961,361006,173205,50044
2012,Oceana,26127,44.79738099,12766,12717,132,120,222,215,45,59,7492,7630,4760,53123
2012,Ogemaw,26129,46.84200235,10391,10529,74,57,94,108,50,62,5562,6704,4941,57793
2012,Ontonagon,26131,45.41809851,3215,3047,21,21,41,47,7,12,1247,2368,1885,57793
2012,Osceola,26133,39.3301719,11471,11336,160,124,78,81,35,34,6747,6769,4198,20056
2012,Oscoda,26135,41.79066835,4291,4141,32,29,34,35,4,10,2057,2736,2093,23225
2012,Otsego,26137,40.035922,11527,11888,122,94,134,98,52,99,6962,7336,4382,26189
2012,Ottawa,26139,32.64783848,125141,129606,3122,2682,865,929,3757,4309,100353,67656,33902,30720
2012,Presque Isle,26141,45.69138277,6423,6394,52,46,67,44,18,33,2876,4400,3579,30720
2012,Roscommon,26143,48.05023645,11758,11894,97,93,95,91,60,73,5235,8154,6993,19034
2012,Saginaw,26145,56.00457256,75103,78832,19112,21239,610,680,1281,1393,66372,55103,31986,21532
2012,St. Clair,26147,46.39064078,76053,77512,2529,2304,520,527,490,609,49620,49339,25136,24922
2012,St. Joseph,26149,43.79385015,28700,29189,1114,1027,210,220,210,268,19181,16728,9522,27894
2012,Sanilac,26151,39.68088033,20623,20951,188,131,127,118,81,86,12105,12656,7850,27894
2012,Schoolcraft,26153,46.54354879,3655,3752,38,32,417,437,7,9,2089,2783,1876,21769
2012,Shiawassee,26155,51.86223951,33463,34398,363,264,222,221,159,209,22050,20594,10731,25248
2012,Tuscola,26157,44.51587765,26656,26677,507,300,177,189,80,116,16662,16516,9382,28885
2012,Van Buren,26159,50.22971848,34689,35275,1811,1873,540,539,224,272,23197,22267,11224,31309
2012,Washtenaw,26161,68.18310002,133089,135704,23848,25033,986,1091,15636,15946,154782,86811,38882,31309
2012,Wayne,26163,73.59212509,489230,503782,340637,393682,5689,6384,26610,28059,630477,487153,238362,20262
2012,Wexford,26165,42.25775591,15861,15898,140,110,132,136,105,137,9920,9488,5421,22695
2016,Alcona,26001,29.19265127,5148,5034,33,43,38,45,10,32,1987,3362,3705,24758
2016,Alger,26003,39.14783427,4073,3786,685,54,238,242,18,19,2661,2840,2225,29174
2016,Allegan,26005,34.55669787,55246,55352,1155,1098,515,509,464,616,36141,32653,17878,29174
2016,Alpena,26007,34.91802105,13794,14260,124,101,88,102,92,96,8069,8718,6397,16532
2016,Antrim,26009,34.43524038,11208,11310,82,83,147,155,34,47,5668,7143,5991,20681
2016,Arenac,26011,32.50613581,7460,7287,64,59,97,102,16,42,3998,4787,3607,25359
2016,Baraga,26013,34.88231744,3370,3097,659,47,668,667,15,13,2690,2494,1769,27593
2016,Barry,26015,32.18674954,29391,29099,293,234,189,207,140,159,17933,17758,10680,27593
2016,Bay,26017,43.30998599,49220,51042,1436,1220,403,402,337,421,32647,30182,20135,25235
2016,Benzie,26019,42.58318648,8395,8554,86,93,149,167,35,45,4541,5320,4400,25777
2016,Berrien,26021,43.28461155,61526,63223,11695,13039,613,591,1666,1804,47958,43025,29070,29662
2016,Branch,26023,30.04095685,21145,20581,931,181,153,124,162,180,13642,12045,7525,34470
2016,Calhoun,26025,43.40802501,54554,57408,8591,8544,656,637,1797,1991,43940,36403,22740,34470
2016,Cass,26027,33.7935202,23222,23330,1795,1589,391,412,206,264,14847,15511,10193,28910
2016,Charlevoix,26029,37.1949895,12437,12765,125,104,260,272,74,85,6830,8155,5963,30885
2016,Cheboygan,26031,33.13053523,12015,12077,153,109,469,468,41,72,6489,7946,6618,34357
2016,Chippewa,26033,37.09399352,14668,13006,2547,172,3407,3482,190,224,14207,10049,6449,38841
2016,Clare,26035,33.31503842,14794,14900,177,126,147,148,47,67,8301,9143,6942,38841
2016,Clinton,26037,43.2543013,36465,37329,1005,886,218,232,660,735,25096,22501,12328,21105
2016,Crawford,26039,32.64232673,6764,6591,91,83,53,57,36,64,3363,4411,3416,23716
2016,Delta,26041,36.65774335,17177,17409,161,134,574,578,79,113,9864,10806,8206,28159
2016,Dickinson,26043,31.37646965,12416,12461,107,104,129,124,80,94,7194,7799,5420,31273
2016,Eaton,26045,47.45846575,47454,49514,4104,4392,355,362,1380,1286,35827,30787,18984,31273
2016,Emmet,26047,39.64066409,15276,15618,204,171,709,716,99,123,9751,9722,6887,20581
2016,Genesee,26049,54.96881119,152164,160075,41211,47101,1462,1639,2290,2665,132867,114267,67597,23464
2016,Gladwin,26051,31.83420037,12404,12266,101,91,82,85,54,61,6282,7555,6553,26803
2016,Gogebic,26053,42.12876278,7361,6706,673,63,249,233,24,40,4561,4596,3759,30525
2016,Grand Traverse,26055,43.3358138,43378,44799,1075,433,708,730,352,439,29797,26557,16772,30525
2016,Gratiot,26057,36.44667439,19254,18638,2271,186,195,142,97,149,14884,10920,6788,25906
2016,Hillsdale,26059,25.39959776,22315,22450,249,227,136,160,100,130,14163,13017,8496,26854
2016,Houghton,26061,41.5234941,18442,15892,291,169,152,134,721,486,14866,8032,6025,29453
2016,Huron,26063,29.98493877,15277,15568,140,131,66,76,95,98,8239,9572,7575,32359
2016,Ingham,26065,64.3285791,109236,115782,19551,20469,1149,1265,10141,10340,128497,65150,36724,32359
2016,Ionia,26067,33.4253812,30952,28959,3106,295,263,232,190,185,23104,17529,8907,23733
2016,Iosco,26069,34.23955871,12208,12321,158,120,133,131,86,114,5970,7825,7211,25130
2016,Iron,26071,35.2879028,5404,5472,49,42,79,81,17,38,2515,3540,3285,27734
2016,Isabella,26073,48.03302165,31049,32734,1284,1332,1592,1614,684,844,35904,14640,8243,31933
2016,Jackson,26075,39.32884064,70772,70080,8852,6065,462,375,758,851,52055,44980,26629,31933
2016,Kalamazoo,26077,56.81745105,106504,110712,16728,17522,842,879,3866,4003,105777,61343,37024,21136
2016,Kalkaska,26079,27.15578847,8586,8260,103,67,96,87,50,51,5034,5167,3422,24541
2016,Kent,26081,48.34468021,266559,274040,36912,38099,2903,3027,10364,11005,240405,161322,82646,30241
2016,Keweenaw,26083,39.29903057,1092,1026,5,7,6,1,0,2,453,626,713,31746
2016,Lake,26085,38.03452334,5316,5058,710,583,78,75,13,28,2879,3871,3167,31746
2016,Lapeer,26087,29.77250941,43077,42578,1002,288,296,265,270,365,26357,27989,14903,23869
2016,Leelanau,26089,48.34082638,9996,10240,81,116,427,500,62,71,5006,6660,6249,26331
2016,Lenawee,26091,38.79110699,46661,46855,2475,1052,406,344,308,409,32052,27761,17587,29026
2016,Livingston,26093,34.36200831,92042,91606,829,618,571,524,917,1251,56795,60086,29868,31891
2016,Luce,26095,27.94419368,2753,2411,725,31,211,188,11,11,2130,1846,1307,31891
2016,Mackinac,26097,35.76942872,4213,4055,181,151,1017,1000,38,39,2669,3435,2846,28281
2016,Macomb,26099,43.97130046,354014,367171,48686,57594,1819,2119,17582,18518,290325,250138,140736,30013
2016,Manistee,26101,41.86144274,11436,11276,847,112,335,307,58,67,6720,7448,5963,32885
2016,Marquette,26103,52.27450469,31469,31490,1080,335,770,752,209,356,24923,17554,11952,35924
2016,Mason,26105,38.30697809,13835,14010,247,165,186,192,105,106,8044,8442,6430,35924
2016,Mecosta,26107,36.12075378,20384,20336,800,773,205,221,239,214,16950,10587,7591,23766
2016,Menominee,26109,34.55717215,11247,10895,122,89,391,364,43,70,6182,7373,5317,26633
2016,Midland,26111,39.60132722,38971,40231,889,674,232,247,1013,1176,26947,23874,14546,28513
2016,Missaukee,26113,22.51474608,7472,7164,71,67,69,80,55,54,4306,4261,2966,31388
2016,Monroe,26115,38.30785466,70566,72321,2219,2172,365,351,558,671,46627,44665,25319,31388
2016,Montcalm,26117,31.77434325,30602,29866,1445,243,275,215,141,176,20399,17720,10545,21918
2016,Montmorency,26119,26.89655172,4593,4450,43,33,29,33,7,18,1951,3065,2817,23737
2016,Muskegon,26121,50.80143264,70677,71868,13657,13282,1049,1079,625,865,57573,47311,27501,27276
2016,Newaygo,26123,29.04839841,23178,23078,441,336,246,247,117,145,14053,14084,8832,30424
2016,Oakland,26125,54.25978968,474599,486251,83031,101479,2488,2785,48080,47049,416815,362385,198575,30424
2016,Oceana,26127,35.47004732,12739,12570,233,168,238,223,51,59,7474,7390,5276,23104
2016,Ogemaw,26129,30.73957594,10147,10262,75,68,107,117,61,65,5408,6420,5221,27464
2016,Ontonagon,26131,36.273905,2955,2820,19,24,34,48,15,16,1045,2087,2057,31725
2016,Osceola,26133,26.93954785,11379,11176,206,147,83,88,44,48,6642,6522,4691,33899
2016,Oscoda,26135,26.85875997,4133,3969,32,31,34,40,8,15,1941,2553,2207,33899
2016,Otsego,26137,30.07951277,11735,11926,152,116,147,106,65,138,7129,7112,4888,36369
2016,Ottawa,26139,33.70278777,130992,134711,3627,3032,941,970,4164,4805,105199,68898,40018,39707
2016,Presque Isle,26141,34.84320557,6198,6210,56,67,61,60,27,46,2804,4015,3841,44419
2016,Roscommon,26143,34.49468941,11587,11649,116,108,113,103,75,96,5026,7732,7506,47798
2016,Saginaw,26145,49.40299338,72758,76145,18574,20528,671,682,1395,1532,63069,52455,35203,47798
2016,St. Clair,26147,33.3582414,75453,76488,2680,2471,545,538,580,752,48181,49009,28192,27968
2016,St. Joseph,26149,33.58322178,28678,29023,1162,1063,210,215,217,264,18937,16381,10393,29268
2016,Sanilac,26151,26.60079699,20154,20426,210,152,147,128,81,94,11593,12287,8475,32262
2016,Schoolcraft,26153,34.87898089,3472,3596,42,29,412,423,9,7,1926,2647,2063,34984
2016,Shiawassee,26155,39.4826284,33005,33903,420,322,238,237,174,242,21444,20383,11869,34984
2016,Tuscola,26157,30.28413028,25943,25875,498,322,199,199,80,119,15842,15949,10318,22833
2016,Van Buren,26159,42.56453063,34765,35097,1823,1766,559,528,296,367,22876,21702,12730,24826
2016,Washtenaw,26161,71.73252789,137316,139530,24545,25454,1006,1093,17867,17941,162206,86313,47100,27655
2016,Wayne,26163,69.4038376,482435,494101,326586,378467,5698,6445,30766,32100,607212,471383,259013,30145
2016,Wexford,26165,30.72873372,16021,16173,211,148,157,140,122,118,9904,9377,6019,30145
\ No newline at end of file
michigan_df.csv deleted 100644 → 0
View file @ 03a08739
year,county,FIPS,party,candidatevotes,version,ratio,White Male,White Female,Black Male,Black Female,Native Male,Native Female,Asian Male,Asian Female,Age <18,Age 18-44,Age 45-64,Age >=65
2000,Alcona,26001,democrat,2696,20191203,0.855329949,"5,839","5,711",19,6,45,34,10,13,"2,218","2,977","3,640","2,842"
2000,Alger,26003,democrat,2071,20191203,0.966853408,"4,483","4,305",601,8,183,201,19,19,"2,004","3,524","2,588","1,703"
2000,Allegan,26005,democrat,15495,20191203,0.549526545,"51,388","51,528",808,789,313,372,332,374,"30,566","40,130","23,455","11,753"
2000,Alpena,26007,democrat,7053,20191203,1.041955976,"15,043","15,878",61,48,58,75,46,60,"7,398","10,691","7,803","5,377"
2000,Antrim,26009,democrat,4329,20191203,0.638495575,"11,402","11,434",49,40,137,139,30,33,"5,670","7,343","6,200","4,051"
2000,Arenac,26011,democrat,3685,20191203,1.077170418,"8,435","8,267",300,24,107,91,17,37,"4,033","5,942","4,436","2,867"
2000,Baraga,26013,democrat,1400,20191203,0.762527233,"3,589","3,528",529,16,569,611,21,12,"2,008","3,200","2,232","1,435"
2000,Barry,26015,democrat,9769,20191203,0.621595826,"28,085","28,130",131,87,166,162,61,109,"15,470","20,688","14,056","6,717"
2000,Bay,26017,democrat,28251,20191203,1.275440181,"51,923","55,158",927,828,405,349,265,337,"26,879","40,077","26,941","16,295"
2000,Benzie,26019,democrat,3546,20191203,0.849952061,"7,775","7,937",37,25,146,142,10,18,"3,766","5,344","4,163","2,817"
2000,Berrien,26021,democrat,28152,20191203,0.788814481,"64,824","67,616","12,464","14,557",444,419,"1,031","1,116","42,211","58,072","38,734","23,454"
2000,Branch,26023,democrat,6691,20191203,0.765297953,"22,254","21,792",703,612,154,119,120,121,"11,711","17,489","10,657","6,018"
2000,Calhoun,26025,democrat,27312,20191203,1.038834582,"57,889","61,173","7,830","8,345",549,515,843,870,"35,820","51,211","32,112","18,871"
2000,Cass,26027,democrat,8808,20191203,0.835277383,"23,390","23,374","1,721","1,741",290,308,152,170,"13,045","17,797","13,339","6,965"
2000,Charlevoix,26029,democrat,4958,20191203,0.70646908,"12,644","12,887",35,44,243,233,41,44,"6,767","8,861","6,635","3,908"
2000,Cheboygan,26031,democrat,5484,20191203,0.804695525,"12,662","12,869",61,44,396,435,30,33,"6,276","8,476","7,029","4,749"
2000,Chippewa,26033,democrat,6370,20191203,0.84639915,"16,111","14,063","2,230",75,"2,988","2,885",139,102,"8,215","16,843","8,642","4,893"
2000,Clare,26035,democrat,6287,20191203,1.058952333,"15,221","15,693",88,45,128,135,35,53,"7,654","10,015","8,319","5,410"
2000,Clinton,26037,democrat,13394,20191203,0.741885455,"31,653","32,101",323,217,159,162,180,225,"18,214","23,696","16,028","7,082"
2000,Crawford,26039,democrat,2790,20191203,0.834080717,"7,012","6,926",196,33,65,33,23,20,"3,495","4,694","3,731","2,388"
2000,Delta,26041,democrat,7970,20191203,0.898433097,"18,322","19,002",42,24,520,495,59,78,"9,169","13,000","9,826","6,547"
2000,Dickinson,26043,democrat,5533,20191203,0.798182343,"13,347","13,766",33,29,81,79,54,71,"6,907","9,161","6,429","4,963"
2000,Eaton,26045,democrat,23211,20191203,0.935814216,"46,821","49,350","2,798","3,171",279,274,667,640,"27,158","39,299","25,701","11,842"
2000,Emmet,26047,democrat,5451,20191203,0.63368984,"14,719","15,360",137,47,576,516,70,92,"7,977","11,044","7,985","4,511"
2000,Genesee,26049,democrat,119833,20191203,1.798187302,"163,774","173,116","42,840","49,867","1,517","1,744","1,973","2,134","119,597","168,067","98,449","50,852"
2000,Gladwin,26051,democrat,5573,20191203,0.970398746,"12,824","12,990",38,29,77,84,35,50,"6,069","7,984","7,281","4,793"
2000,Gogebic,26053,democrat,4066,20191203,1.034868923,"8,124","8,335",281,13,218,200,23,25,"3,529","5,593","4,204","3,893"
2000,Grand Traverse,26055,democrat,14371,20191203,0.642767689,"37,138","39,120",283,152,398,438,224,251,"19,792","29,197","18,812","10,203"
2000,Gratiot,26057,democrat,6538,20191203,0.786573628,"20,112","20,117","1,681",85,168,126,110,73,"10,081","17,411","9,229","5,751"
2000,Hillsdale,26059,democrat,6495,20191203,0.619574549,"22,911","23,175",149,98,99,99,72,95,"12,286","17,150","11,041","6,221"
2000,Houghton,26061,democrat,5688,20191203,0.720455985,"18,317","16,279",310,130,123,114,418,273,"7,822","15,053","7,528","5,561"
2000,Huron,26063,democrat,6899,20191203,0.774211649,"17,656","18,017",62,53,54,69,59,77,"8,737","11,339","8,962","7,009"
2000,Ingham,26065,democrat,69231,20191203,1.463224416,"112,179","120,371","16,168","17,632",978,"1,030","5,699","5,658","65,302","131,713","56,379","26,321"
2000,Ionia,26067,democrat,9481,20191203,0.68135106,"29,674","28,286","2,894",125,284,167,178,104,"16,593","26,163","12,758","6,198"
2000,Iosco,26069,democrat,6505,20191203,1.025216706,"13,166","13,648",82,67,108,111,62,90,"6,109","7,825","7,485","5,915"
2000,Iron,26071,democrat,3014,20191203,1.015840917,"6,252","6,517",146,14,73,78,9,17,"2,692","3,762","3,347","3,305"
2000,Isabella,26073,democrat,10228,20191203,1.017407739,"28,032","30,910",782,742,"1,012",990,486,490,"12,834","33,804","11,067","5,739"
2000,Jackson,26075,democrat,28160,20191203,0.878188736,"71,593","71,698","8,444","5,129",419,382,511,503,"40,645","60,901","36,721","20,412"
2000,Kalamazoo,26077,democrat,48807,20191203,1.01146019,"100,284","107,186","12,173","13,161",584,705,"2,563","2,352","57,404","103,697","50,680","27,227"
2000,Kalkaska,26079,democrat,2774,20191203,0.722019781,"8,241","8,148",34,26,81,61,23,26,"4,246","6,000","4,099","2,295"
2000,Kent,26081,democrat,95442,20191203,0.642265918,"248,240","255,122","27,486","29,371","1,874","1,969","5,901","6,215","162,684","239,599","114,174","59,721"
2000,Keweenaw,26083,democrat,540,20191203,0.72972973,"1,141","1,052",72,1,3,1,2,2,506,640,665,463
2000,Lake,26085,democrat,2584,20191203,1.317695054,"5,034","4,745",816,575,72,74,7,15,"2,478","3,488","3,135","2,237"
2000,Lapeer,26087,democrat,15749,20191203,0.773868606,"43,599","43,051",682,107,189,225,189,229,"24,697","33,984","21,122","8,468"
2000,Leelanau,26089,democrat,4635,20191203,0.677631579,"10,150","10,145",38,33,400,429,23,39,"5,198","6,332","6,031","3,696"
2000,Lenawee,26091,democrat,18365,20191203,0.888013152,"47,294","48,314","1,778",640,259,239,236,309,"25,687","37,269","23,555","12,558"
2000,Livingston,26093,democrat,28780,20191203,0.644756592,"78,415","77,108",641,217,448,406,504,606,"45,528","60,445","39,170","13,202"
2000,Luce,26095,democrat,956,20191203,0.645945946,"3,052","2,906",543,7,262,197,31,8,"1,503","2,730","1,693","1,080"
2000,Mackinac,26097,democrat,2533,20191203,0.774144254,"4,954","4,947",16,12,980,990,19,20,"2,641","3,718","3,399","2,180"
2000,Macomb,26099,democrat,172625,20191203,1.050893374,"364,661","380,664","11,804","11,535","1,603","1,647","9,355","9,577","190,129","311,334","181,419","107,964"
2000,Manistee,26101,democrat,5639,20191203,1.044065914,"11,809","11,850",420,36,222,163,61,48,"5,574","8,103","6,492","4,440"
2000,Marquette,26103,democrat,15503,20191203,1.232646895,"30,896","31,215",823,149,579,592,139,213,"13,811","26,119","15,922","8,754"
2000,Mason,26105,democrat,5579,20191203,0.789555618,"13,638","14,075",187,94,138,133,34,51,"6,857","9,401","7,339","4,753"
2000,Mecosta,26107,democrat,6300,20191203,0.780475719,"19,466","18,750",778,909,163,181,205,205,"9,130","17,415","8,761","5,351"
2000,Menominee,26109,democrat,4597,20191203,0.831434256,"12,201","12,320",28,24,332,314,26,36,"6,047","8,538","6,308","4,388"
2000,Midland,26111,democrat,15959,20191203,0.729154293,"39,311","40,883",534,480,206,174,652,673,"22,281","31,329","19,359","9,944"
2000,Missaukee,26113,democrat,2062,20191203,0.482452036,"7,200","7,180",14,28,33,45,13,23,"3,930","5,037","3,421","2,148"
2000,Monroe,26115,democrat,31555,20191203,1.090359364,"70,331","71,548","1,668","1,488",276,257,343,453,"40,076","55,376","34,630","16,282"
2000,Montcalm,26117,democrat,9627,20191203,0.758270321,"29,834","29,464","1,337",134,265,204,118,128,"16,640","23,594","13,793","7,457"
2000,Montmorency,26119,democrat,2139,20191203,0.777818182,"5,057","5,228",15,15,12,27,3,7,"2,089","2,758","3,040","2,477"
2000,Muskegon,26121,democrat,37865,20191203,1.260989743,"70,546","71,868","12,545","12,779",910,836,448,464,"46,910","64,069","37,520","21,897"
2000,Newaygo,26123,democrat,7677,20191203,0.67348013,"23,326","23,441",349,287,188,213,69,99,"13,935","16,719","11,177","6,141"
2000,Oakland,26125,democrat,281201,20191203,1.025087581,"498,246","513,869","58,116","68,009","2,194","2,342","27,046","26,343","300,894","473,034","286,955","135,282"
2000,Oceana,26127,democrat,4597,20191203,0.77743954,"13,283","13,047",65,54,171,186,41,55,"7,563","9,191","6,376","3,772"
2000,Ogemaw,26129,democrat,4896,20191203,1.040373991,"10,628","10,783",31,16,69,88,48,47,"5,089","6,653","5,873","4,095"
2000,Ontonagon,26131,democrat,1514,20191203,0.612459547,"3,924","3,793",6,1,43,42,4,12,"1,570","2,182","2,358","1,715"
2000,Osceola,26133,democrat,4006,20191203,0.70528169,"11,327","11,604",73,50,71,68,21,34,"6,301","7,995","5,649","3,303"
2000,Oscoda,26135,democrat,1677,20191203,0.759855007,"4,571","4,728",7,6,34,38,3,5,"2,181","2,657","2,643","1,911"
2000,Otsego,26137,democrat,4034,20191203,0.660445318,"11,471","11,637",35,31,102,80,33,54,"6,268","8,304","5,645","3,226"
2000,Ottawa,26139,democrat,29600,20191203,0.37609748,"113,067","116,693","1,673","1,507",551,537,"2,687","2,844","68,722","98,492","48,135","24,210"
2000,Presque Isle,26141,democrat,3242,20191203,0.88579235,"7,092","7,118",29,28,37,48,9,17,"3,004","4,135","4,006","3,233"
2000,Roscommon,26143,democrat,6433,20191203,1.039256866,"12,384","12,775",52,49,84,88,24,38,"5,077","6,839","7,488","6,090"
2000,Saginaw,26145,democrat,50825,20191203,1.235055404,"80,338","85,690","19,025","21,757",550,569,962,"1,008","55,729","76,764","49,023","28,383"
2000,St. Clair,26147,democrat,33002,20191203,0.983050847,"78,223","80,587","2,006","1,968",511,518,364,444,"44,021","62,166","38,267","20,167"
2000,St. Joseph,26149,democrat,8574,20191203,0.664342166,"29,625","30,322",908,908,161,150,199,207,"17,178","23,041","14,161","8,100"
2000,Sanilac,26151,democrat,7153,20191203,0.652288893,"21,806","22,215",120,49,86,108,64,68,"11,962","15,368","10,311","6,875"
2000,Schoolcraft,26153,democrat,2036,20191203,0.975095785,"3,994","4,106",146,6,297,325,24,17,"2,022","2,919","2,314","1,660"
2000,Shiawassee,26155,democrat,15520,20191203,0.981284775,"34,777","36,051",124,100,225,209,99,129,"19,227","26,862","17,019","8,606"
2000,Tuscola,26157,democrat,10845,20191203,0.820782563,"28,258","28,657",516,181,233,202,84,120,"15,586","21,071","14,107","7,487"
2000,Van Buren,26159,democrat,13796,20191203,0.932666306,"35,153","35,505","2,126","2,291",422,439,142,164,"21,335","27,369","18,167","9,371"
2000,Washtenaw,26161,democrat,86647,20191203,1.651708954,"128,186","129,766","20,961","21,577",784,837,"11,372","10,889","71,584","159,176","67,182","26,430"
2000,Wayne,26163,democrat,530414,20191203,2.37831415,"552,118","567,990","408,849","476,397","5,281","5,790","20,657","20,173","575,919","801,006","431,996","248,334"
2000,Wexford,26165,democrat,5326,20191203,0.738184338,"14,881","15,148",62,55,123,125,61,82,"8,182","10,883","7,177","4,295"
2004,Alcona,26001,democrat,2871,20191203,0.799276169,"5,744","5,598",15,8,38,32,9,15,"1,931","2,595","3,861","3,072"
2004,Alger,26003,democrat,2395,20191203,1.033218292,"4,373","4,225",605,12,202,225,20,18,"1,769","3,180","2,917","1,814"
2004,Allegan,26005,democrat,19355,20191203,0.568896596,"53,201","53,573",952,871,379,380,392,477,"30,732","39,525","27,624","12,344"
2004,Alpena,26007,democrat,7407,20191203,0.966340509,"14,794","15,545",68,56,58,85,61,68,"6,927","9,755","8,664","5,389"
2004,Antrim,26009,democrat,5072,20191203,0.605322831,"11,855","11,969",53,42,139,146,27,32,"5,572","7,193","7,039","4,459"
2004,Arenac,26011,democrat,4076,20191203,1.001228199,"8,439","8,171",235,28,107,97,15,36,"3,760","5,439","4,870","3,059"
2004,Baraga,26013,democrat,1660,20191203,0.839656045,"3,548","3,457",599,18,590,639,21,12,"1,884","3,084","2,465","1,451"
2004,Barry,26015,democrat,11312,20191203,0.606932074,"29,165","29,001",178,111,164,169,91,126,"15,455","20,237","16,002","7,311"
2004,Bay,26017,democrat,31049,20191203,1.220095882,"51,678","54,335","1,069",973,395,367,280,356,"25,919","37,539","29,522","16,473"
2004,Benzie,26019,democrat,4383,20191203,0.829485238,"8,468","8,536",42,39,147,157,10,21,"3,961","5,403","4,872","3,184"
2004,Berrien,26021,democrat,32846,20191203,0.799639692,"63,755","66,439","12,084","14,075",475,470,"1,174","1,270","40,061","54,154","41,930","23,597"
2004,Branch,26023,democrat,7004,20191203,0.649480712,"22,855","21,921","1,056",436,162,118,118,125,"11,658","16,949","11,850","6,334"
2004,Calhoun,26025,democrat,29891,20191203,0.931386907,"58,181","61,285","8,202","8,479",590,551,"1,071","1,084","35,283","49,794","35,165","19,201"
2004,Cass,26027,democrat,9537,20191203,0.735652576,"23,939","23,923","1,734","1,692",309,335,163,195,"12,705","16,988","14,763","7,834"
2004,Charlevoix,26029,democrat,5729,20191203,0.697467738,"12,854","13,045",51,51,260,250,40,50,"6,446","8,237","7,711","4,207"
2004,Cheboygan,26031,democrat,5941,20191203,0.761862016,"13,004","13,103",70,65,438,482,29,37,"6,030","8,299","7,891","5,008"
2004,Chippewa,26033,democrat,7203,20191203,0.789629467,"15,900","13,949","2,371",96,"3,174","3,055",147,111,"7,980","15,960","9,809","5,054"
2004,Clare,26035,democrat,6984,20191203,0.985327314,"15,547","15,777",100,59,124,126,38,50,"7,178","9,787","8,983","5,873"
2004,Clinton,26037,democrat,15483,20191203,0.70412479,"33,733","34,441",682,634,184,192,335,404,"18,772","25,758","18,253","7,822"
2004,Crawford,26039,democrat,3126,20191203,0.778192681,"7,192","7,093",132,36,58,32,21,27,"3,233","4,352","4,406","2,600"
2004,Delta,26041,democrat,9381,20191203,0.96911157,"18,106","18,662",54,42,560,552,61,86,"8,537","12,017","10,901","6,668"
2004,Dickinson,26043,democrat,5650,20191203,0.730540471,"13,183","13,675",43,38,93,79,51,69,"6,377","8,370","7,389","5,095"
2004,Eaton,26045,democrat,25411,20191203,0.853262147,"47,806","50,201","3,360","3,861",287,298,878,842,"26,903","38,690","29,065","12,875"
2004,Emmet,26047,democrat,6846,20191203,0.662601626,"15,226","15,962",133,72,627,625,80,99,"8,090","10,775","9,263","4,696"
2004,Genesee,26049,democrat,128334,20191203,1.530153809,"166,111","174,684","43,624","50,413","1,527","1,690","2,132","2,353","118,709","161,521","109,531","52,773"
2004,Gladwin,26051,democrat,6343,20191203,0.936927622,"13,321","13,341",50,31,68,83,32,45,"5,934","7,819","7,941","5,277"
2004,Gogebic,26053,democrat,4421,20191203,1.123506989,"8,084","7,891",506,15,214,217,22,27,"3,119","5,490","4,603","3,764"
2004,Grand Traverse,26055,democrat,18256,20191203,0.665160679,"39,211","41,094",670,239,465,489,276,324,"19,722","29,363","22,540","11,143"
2004,Gratiot,26057,democrat,7377,20191203,0.750152532,"20,106","20,039","1,878",111,141,118,97,93,"9,889","16,786","10,099","5,809"
2004,Hillsdale,26059,democrat,7123,20191203,0.556310528,"23,226","23,499",163,113,93,113,74,111,"12,018","16,475","12,404","6,495"
2004,Houghton,26061,democrat,6731,20191203,0.757228035,"18,520","16,124",251,121,124,116,561,337,"7,488","15,185","8,060","5,421"
2004,Huron,26063,democrat,7629,20191203,0.788853273,"17,208","17,418",71,56,49,67,63,82,"7,911","10,380","9,716","7,007"
2004,Ingham,26065,democrat,76877,20191203,1.404556583,"112,291","119,379","17,345","18,760","1,051","1,151","6,794","6,815","62,215","132,204","62,553","26,614"
2004,Ionia,26067,democrat,10647,20191203,0.640575176,"31,193","29,174","3,292",168,274,164,167,130,"16,583","26,335","15,041","6,603"
2004,Iosco,26069,democrat,6557,20191203,0.898096151,"12,957","13,360",87,89,116,104,54,93,"5,377","6,993","8,193","6,297"
2004,Iron,26071,democrat,3215,20191203,0.997208437,"6,025","6,145",110,16,67,69,8,20,"2,295","3,268","3,706","3,191"
2004,Isabella,26073,democrat,12334,20191203,1.049344904,"29,550","32,159",924,951,"1,155","1,165",552,611,"12,685","36,086","12,434","5,862"
2004,Jackson,26075,democrat,31025,20191203,0.775063079,"73,241","72,963","8,604","5,325",439,367,593,608,"40,327","59,616","41,369","20,828"
2004,Kalamazoo,26077,democrat,61462,20191203,1.075507026,"101,385","106,906","13,226","13,987",673,767,"2,861","2,700","56,722","101,963","56,148","27,672"
2004,Kalkaska,26079,democrat,3189,20191203,0.627261998,"8,620","8,493",45,32,88,75,18,29,"4,321","5,788","4,812","2,479"
2004,Kent,26081,democrat,116909,20191203,0.682875684,"250,902","258,555","29,781","31,865","2,096","2,159","6,875","7,321","162,174","234,969","131,657","60,754"
2004,Keweenaw,26083,democrat,630,20191203,0.806658131,"1,068","1,011",41,1,1,1,0,2,413,582,718,412
2004,Lake,26085,democrat,2675,20191203,1.068717539,"5,257","5,061",682,599,66,70,8,14,"2,384","3,325","3,563","2,485"
2004,Lapeer,26087,democrat,18086,20191203,0.707700736,"44,895","44,320",839,182,212,231,178,268,"24,540","32,489","24,637","9,459"
2004,Leelanau,26089,democrat,6048,20191203,0.782102677,"10,350","10,462",43,43,416,472,29,44,"4,903","5,721","7,059","4,176"
2004,Lenawee,26091,democrat,20787,20191203,0.809620253,"48,400","48,942","1,903",781,290,274,275,351,"25,493","36,440","26,345","12,938"
2004,Livingston,26093,democrat,33991,20191203,0.577488957,"86,471","85,130",747,422,495,439,716,825,"49,099","62,499","47,676","15,971"
2004,Luce,26095,democrat,1045,20191203,0.597484277,"3,005","2,835",592,8,223,199,22,10,"1,351","2,553","1,901","1,089"
2004,Mackinac,26097,democrat,2819,20191203,0.760658392,"4,803","4,718",22,17,"1,024","1,023",19,21,"2,472","3,358","3,554","2,263"
2004,Macomb,26099,democrat,196160,20191203,0.97029174,"368,338","384,821","20,316","21,611","1,735","1,775","12,185","12,637","197,731","308,687","206,540","110,460"
2004,Manistee,26101,democrat,6272,20191203,0.996346307,"11,990","12,002",431,40,268,221,45,51,"5,435","7,715","7,300","4,598"
2004,Marquette,26103,democrat,17412,20191203,1.18529612,"31,268","31,545",917,203,657,649,160,221,"12,944","25,915","17,739","9,022"
2004,Mason,26105,democrat,6333,20191203,0.779542097,"13,875","14,254",188,114,146,165,39,61,"6,706","8,915","8,194","5,027"
2004,Mecosta,26107,democrat,7730,20191203,0.796086509,"20,423","19,864",712,817,176,195,178,188,"9,181","17,899","9,703","5,770"
2004,Menominee,26109,democrat,5326,20191203,0.896331202,"12,064","12,094",38,32,352,347,22,38,"5,751","7,751","7,151","4,334"
2004,Midland,26111,democrat,18355,20191203,0.753211047,"39,762","41,285",595,530,213,194,708,771,"21,801","29,781","21,621","10,855"
2004,Missaukee,26113,democrat,2319,20191203,0.458753709,"7,534","7,406",21,32,40,53,14,27,"3,881","4,860","4,038","2,348"
2004,Monroe,26115,democrat,36089,20191203,0.963143848,"72,261","73,638","1,909","1,743",294,288,425,559,"39,855","54,035","39,723","17,504"
2004,Montcalm,26117,democrat,11471,20191203,0.766368252,"30,827","30,425","1,351",156,247,209,122,145,"16,561","23,161","15,798","7,962"
2004,Montmorency,26119,democrat,2196,20191203,0.665454545,"5,117","5,124",16,16,14,27,4,8,"1,883","2,603","3,322","2,518"
2004,Muskegon,26121,democrat,44282,20191203,1.254376523,"71,315","72,644","13,049","12,866",908,906,530,553,"45,737","62,733","42,318","21,983"
2004,Newaygo,26123,democrat,9057,20191203,0.665564374,"24,019","23,934",393,309,203,233,70,111,"13,576","16,358","12,735","6,603"
2004,Oakland,26125,democrat,319387,20191203,1.008697767,"488,253","502,856","65,817","77,781","2,290","2,422","32,447","31,946","299,341","444,014","321,276","139,181"
2004,Oceana,26127,democrat,5441,20191203,0.814886925,"13,545","13,372",74,85,168,208,49,55,"7,346","8,984","7,209","4,017"
2004,Ogemaw,26129,democrat,5215,20191203,0.956178951,"10,820","10,919",39,20,72,89,46,48,"4,865","6,360","6,574","4,254"
2004,Ontonagon,26131,democrat,1863,20191203,0.823607427,"3,795","3,598",7,2,37,44,4,10,"1,320","1,936","2,499","1,742"
2004,Osceola,26133,democrat,4467,20191203,0.676920746,"11,787","11,830",101,63,76,74,26,33,"6,255","7,783","6,369","3,583"
2004,Oscoda,26135,democrat,1792,20191203,0.697276265,"4,566","4,647",10,6,30,32,2,6,"2,005","2,410","2,898","1,986"
2004,Otsego,26137,democrat,4674,20191203,0.625702811,"12,007","12,202",47,46,106,86,36,56,"6,200","8,232","6,526","3,628"
2004,Ottawa,26139,democrat,35552,20191203,0.38623327,"118,491","122,334","2,119","2,021",639,673,"3,271","3,500","70,735","99,635","56,341","26,337"
2004,Presque Isle,26141,democrat,3432,20191203,0.861878453,"7,006","6,975",32,30,42,46,10,22,"2,737","3,747","4,337","3,342"
2004,Roscommon,26143,democrat,6810,20191203,0.924769147,"12,607","12,813",56,58,88,82,26,41,"4,780","6,397","8,299","6,295"
2004,Saginaw,26145,democrat,54887,20191203,1.1637231,"79,347","84,094","19,599","22,176",545,566,"1,019","1,143","53,421","73,311","53,092","28,665"
2004,St. Clair,26147,democrat,36174,20191203,0.846373421,"80,093","81,937","2,295","2,135",527,505,427,538,"43,586","60,084","43,904","20,883"
2004,St. Joseph,26149,democrat,9648,20191203,0.628943937,"29,519","30,015",997,974,172,171,183,234,"16,691","21,745","15,469","8,360"
2004,Sanilac,26151,democrat,7883,20191203,0.624050032,"21,853","22,522",136,58,100,120,72,78,"11,535","14,552","11,606","7,246"
2004,Schoolcraft,26153,democrat,2137,20191203,0.942655492,"4,040","4,064",128,7,324,363,21,15,"1,902","2,689","2,605","1,766"
2004,Shiawassee,26155,democrat,16881,20191203,0.869840779,"35,438","36,497",242,147,226,210,112,162,"19,114","25,981","18,953","8,986"
2004,Tuscola,26157,democrat,12631,20191203,0.820781077,"28,296","28,611",525,222,205,177,77,117,"14,942","19,782","15,608","7,898"
2004,Van Buren,26159,democrat,16151,20191203,0.9159011,"35,709","36,070","1,975","2,144",496,485,168,194,"20,796","26,331","20,625","9,489"
2004,Washtenaw,26161,democrat,109953,20191203,1.789162802,"131,939","133,865","22,253","22,972",823,866,"13,532","13,172","73,770","159,997","77,084","28,571"
2004,Wayne,26163,democrat,600047,20191203,2.328019399,"529,566","543,041","393,067","458,327","5,359","5,920","24,441","24,109","547,492","735,688","465,577","235,073"
2004,Wexford,26165,democrat,6034,20191203,0.672986839,"15,515","15,670",87,76,117,138,78,97,"8,132","10,821","8,270","4,555"
2008,Alcona,26001,democrat,2896,20191203,0.850763807,"5,679","5,488",11,10,39,33,6,20,"1,759","2,308","3,859","3,360"
2008,Alger,26003,democrat,2472,20191203,1.129798903,"4,397","4,150",595,20,219,230,20,16,"1,636","2,953","3,111","1,947"
2008,Allegan,26005,democrat,24165,20191203,0.803865474,"53,743","54,256",994,933,410,407,353,493,"29,890","36,761","31,061","13,877"
2008,Alpena,26007,democrat,7705,20191203,1.081403509,"14,510","15,149",81,52,63,96,83,85,"6,404","8,882","9,172","5,661"
2008,Antrim,26009,democrat,6079,20191203,0.809885425,"11,695","11,906",54,37,153,144,24,34,"5,183","6,439","7,409","5,016"
2008,Arenac,26011,democrat,4155,20191203,1.091410559,"8,216","7,897",152,31,91,118,11,31,"3,339","4,680","5,194","3,334"
2008,Baraga,26013,democrat,1725,20191203,0.934452871,"3,508","3,296",643,21,635,705,7,7,"1,825","2,940","2,571","1,486"
2008,Barry,26015,democrat,13449,20191203,0.818513785,"29,546","29,263",226,172,171,190,97,123,"15,049","18,973","17,585","8,181"
2008,Bay,26017,democrat,32589,20191203,1.36957344,"50,992","53,567","1,254","1,111",385,360,302,349,"24,654","35,375","31,048","17,243"
2008,Benzie,26019,democrat,5451,20191203,1.163004054,"8,637","8,669",59,54,132,136,16,30,"3,851","5,030","5,338","3,514"
2008,Berrien,26021,democrat,40381,20191203,1.117658456,"62,701","65,137","11,971","13,646",536,564,"1,350","1,475","37,562","50,828","44,160","24,830"
2008,Branch,26023,democrat,8413,20191203,0.88242081,"22,650","21,471","1,456",237,140,112,113,126,"11,142","15,823","12,763","6,577"
2008,Calhoun,26025,democrat,34561,20191203,1.210415718,"56,954","59,916","8,291","8,516",579,579,"1,207","1,271","33,865","46,627","37,097","19,724"
2008,Cass,26027,democrat,12083,20191203,1.087187331,"23,973","24,222","1,780","1,707",340,300,157,205,"12,587","16,220","15,693","8,184"
2008,Charlevoix,26029,democrat,6817,20191203,0.933068711,"12,534","12,983",75,53,244,275,43,73,"6,041","7,449","8,166","4,624"
2008,Cheboygan,26031,democrat,6720,20191203,0.971098266,"12,709","12,804",94,82,468,491,34,56,"5,593","7,469","8,204","5,472"
2008,Chippewa,26033,democrat,8184,20191203,0.989960082,"15,703","13,636","2,870",109,"3,334","3,302",154,139,"7,649","15,482","10,687","5,429"
2008,Clare,26035,democrat,7496,20191203,1.103488886,"15,154","15,330",144,89,134,115,43,55,"6,587","9,045","9,350","6,082"
2008,Clinton,26037,democrat,20005,20191203,1.01414377,"34,900","36,075",894,908,179,204,538,604,"18,852","25,929","20,386","9,135"
2008,Crawford,26039,democrat,3441,20191203,0.966301601,"7,098","7,028",71,47,42,41,18,34,"2,964","3,923","4,648","2,844"
2008,Delta,26041,democrat,9974,20191203,1.138194682,"17,802","18,215",83,69,559,531,62,88,"7,875","11,022","11,567","6,945"
2008,Dickinson,26043,democrat,5995,20191203,0.850475245,"12,886","13,325",68,65,87,72,49,70,"5,843","7,582","8,095","5,102"
2008,Eaton,26045,democrat,30742,20191203,1.186949807,"47,700","50,258","3,613","3,880",309,324,950,987,"25,624","36,835","31,375","14,187"
2008,Emmet,26047,democrat,8515,20191203,0.91421516,"15,253","15,797",122,96,708,700,80,96,"7,584","10,053","9,979","5,236"
2008,Genesee,26049,democrat,143927,20191203,1.986542629,"161,476","170,275","43,451","50,043","1,521","1,672","2,216","2,428","111,401","149,128","116,047","56,506"
2008,Gladwin,26051,democrat,6590,20191203,1.031137537,"12,842","12,801",61,34,66,72,33,47,"5,349","7,031","7,956","5,620"
2008,Gogebic,26053,democrat,4757,20191203,1.428528529,"7,878","7,507",624,37,190,223,12,28,"2,829","5,092","4,990","3,588"
2008,Grand Traverse,26055,democrat,23258,20191203,0.941009872,"40,603","42,600",917,303,549,573,314,350,"19,577","28,823","25,420","12,389"
2008,Gratiot,26057,democrat,9105,20191203,1.09408796,"20,224","19,746","2,270",110,139,116,65,104,"9,408","16,232","10,973","6,161"
2008,Hillsdale,26059,democrat,8765,20191203,0.781124677,"23,007","23,218",192,134,90,112,87,111,"11,378","15,371","13,167","7,035"
2008,Houghton,26061,democrat,7476,20191203,0.922849031,"18,657","16,055",183,112,129,121,659,376,"7,498","14,936","8,509","5,349"
2008,Huron,26063,democrat,8367,20191203,0.992055964,"16,440","16,628",89,77,54,59,69,88,"7,067","9,229","10,076","7,132"
2008,Ingham,26065,democrat,93994,20191203,2.022115612,"109,793","116,531","18,323","19,424","1,063","1,148","7,435","7,598","59,900","127,086","66,077","28,252"
2008,Ionia,26067,democrat,12565,20191203,0.887609494,"31,441","29,262","3,565",184,252,176,147,140,"16,068","25,139","16,885","7,075"
2008,Iosco,26069,democrat,7309,20191203,1.110284065,"12,829","13,174",99,93,107,98,52,90,"4,908","6,379","8,610","6,645"
2008,Iron,26071,democrat,3080,20191203,1.045130641,"5,854","5,979",59,17,66,73,9,24,"2,078","2,914","3,957","3,132"
2008,Isabella,26073,democrat,16679,20191203,1.486541889,"30,572","32,701","1,021","1,044","1,427","1,363",575,625,"12,602","36,523","13,717","6,486"
2008,Jackson,26075,democrat,37480,20191203,1.050095259,"72,259","72,177","8,664","5,559",472,379,619,696,"38,264","55,987","44,695","21,879"
2008,Kalamazoo,26077,democrat,77051,20191203,1.494568802,"102,395","107,440","14,420","15,176",782,840,"2,899","2,910","56,490","100,145","60,524","29,703"
2008,Kalkaska,26079,democrat,3780,20191203,0.83499006,"8,728","8,517",54,39,88,75,15,30,"4,149","5,333","5,301","2,763"
2008,Kent,26081,democrat,149909,20191203,1.010604304,"251,688","261,050","32,056","34,024","2,475","2,431","7,387","8,123","159,988","227,476","147,116","64,654"
2008,Keweenaw,26083,democrat,610,20191203,0.806878307,"1,060","1,030",19,6,2,1,0,1,397,499,753,470
2008,Lake,26085,democrat,2919,20191203,1.28646981,"5,257","5,009",618,604,57,62,5,17,"2,142","2,941","3,900","2,646"
2008,Lapeer,26087,democrat,21457,20191203,0.939818668,"44,104","43,790",896,229,237,244,165,249,"22,699","29,132","27,077","11,006"
2008,Leelanau,26089,democrat,7355,20191203,1.060103776,"10,209","10,376",48,56,434,514,43,51,"4,510","5,059","7,423","4,739"
2008,Lenawee,26091,democrat,24640,20191203,1.108661417,"48,287","48,565","2,207",836,324,281,293,376,"24,156","34,694","28,236","14,083"
2008,Livingston,26093,democrat,42349,20191203,0.761782271,"88,866","88,441",647,468,516,452,800,981,"47,887","58,613","54,810","19,861"
2008,Luce,26095,democrat,1191,20191203,0.799328859,"2,908","2,677",666,10,209,190,10,10,"1,243","2,325","1,968","1,144"
2008,Mackinac,26097,democrat,3027,20191203,0.92625459,"4,531","4,477",40,38,"1,081","1,052",11,18,"2,165","2,934","3,692","2,457"
2008,Macomb,26099,democrat,223784,20191203,1.192478006,"361,733","378,281","31,450","35,309","1,782","1,858","13,322","14,122","196,671","296,389","227,924","116,873"
2008,Manistee,26101,democrat,7235,20191203,1.313067151,"11,861","11,713",676,52,302,275,29,52,"4,917","7,185","7,901","4,957"
2008,Marquette,26103,democrat,19635,20191203,1.521385402,"31,667","31,803","1,013",261,706,675,154,260,"12,483","25,445","18,988","9,623"
2008,Mason,26105,democrat,7817,20191203,1.093745628,"13,755","14,118",185,129,181,183,48,69,"6,356","8,202","8,832","5,278"
2008,Mecosta,26107,democrat,9101,20191203,0.98516995,"20,493","20,077",698,695,187,201,164,168,"8,715","17,415","10,205","6,348"
2008,Menominee,26109,democrat,5981,20191203,1.23192585,"11,737","11,633",70,45,371,383,32,46,"5,240","6,854","7,751","4,472"
2008,Midland,26111,democrat,20701,20191203,0.929838746,"39,309","40,948",746,553,198,206,788,857,"20,497","27,876","23,314","11,918"
2008,Missaukee,26113,democrat,2898,20191203,0.648467219,"7,513","7,287",39,37,51,52,18,31,"3,743","4,473","4,335","2,477"
2008,Monroe,26115,democrat,39180,20191203,1.092643204,"72,710","74,355","2,128","1,919",329,327,454,584,"37,999","51,109","44,074","19,624"
2008,Montcalm,26117,democrat,13208,20191203,0.993755173,"31,030","30,271","1,490",153,236,206,113,136,"15,958","21,966","17,140","8,571"
2008,Montmorency,26119,democrat,2403,20191203,0.845828933,"4,918","4,905",19,17,20,26,5,12,"1,676","2,312","3,351","2,583"
2008,Muskegon,26121,democrat,53821,20191203,1.846663236,"71,331","72,572","13,564","13,269",922,964,546,678,"44,276","60,139","46,518","22,913"
2008,Newaygo,26123,democrat,10790,20191203,0.909627382,"24,032","23,735",406,305,225,244,72,134,"12,803","15,251","13,865","7,234"
2008,Oakland,26125,democrat,372566,20191203,1.345217291,"471,838","488,734","73,232","89,058","2,374","2,517","35,940","35,852","287,628","413,988","345,666","152,263"
2008,Oceana,26127,democrat,6405,20191203,1.093003413,"13,308","13,120",107,108,184,202,38,53,"6,903","8,145","7,652","4,420"
2008,Ogemaw,26129,democrat,5391,20191203,1.050263004,"10,705","10,854",50,28,72,92,37,47,"4,556","5,798","6,910","4,621"
2008,Ontonagon,26131,democrat,1966,20191203,1.078442128,"3,499","3,315",9,6,34,46,4,9,"1,116","1,528","2,524","1,754"
2008,Osceola,26133,democrat,4855,20191203,0.812824376,"11,570","11,669",132,90,63,83,25,30,"5,922","7,035","6,795","3,910"
2008,Oscoda,26135,democrat,1887,20191203,0.813362069,"4,488","4,382",12,12,30,27,3,9,"1,868","2,113","2,906","2,076"
2008,Otsego,26137,democrat,5634,20191203,0.834419431,"11,795","12,123",86,64,110,88,47,65,"5,780","7,462","7,168","3,968"
2008,Ottawa,26139,democrat,50828,20191203,0.609960398,"121,700","126,256","2,469","2,446",770,808,"3,494","3,963","69,952","98,950","63,756","29,248"
2008,Presque Isle,26141,democrat,3722,20191203,1.032168608,"6,754","6,732",40,36,52,41,17,29,"2,474","3,158","4,581","3,488"
2008,Roscommon,26143,democrat,7082,20191203,1.05277241,"12,186","12,290",65,62,92,87,27,47,"4,192","5,554","8,460","6,650"
2008,Saginaw,26145,democrat,60276,20191203,1.42749556,"76,611","80,944","19,179","21,644",599,617,"1,130","1,242","48,793","68,012","55,168","29,993"
2008,St. Clair,26147,democrat,40677,20191203,1.055558439,"78,618","80,424","2,522","2,300",510,510,465,610,"40,571","54,885","47,732","22,771"
2008,St. Joseph,26149,democrat,12322,20191203,0.956231569,"29,276","29,865","1,058","1,039",184,205,198,258,"16,281","20,332","16,619","8,851"
2008,Sanilac,26151,democrat,9047,20191203,0.847176702,"21,579","21,990",151,85,108,110,69,85,"10,747","13,351","12,550","7,529"
2008,Schoolcraft,26153,democrat,2184,20191203,1.06122449,"3,819","3,836",26,9,373,394,6,8,"1,747","2,238","2,772","1,714"
2008,Shiawassee,26155,democrat,19397,20191203,1.192340792,"34,704","35,614",301,200,212,208,125,159,"17,927","23,754","20,155","9,687"
2008,Tuscola,26157,democrat,13503,20191203,0.982751092,"27,570","27,612",505,255,188,183,72,127,"13,807","17,888","16,360","8,457"
2008,Van Buren,26159,democrat,18588,20191203,1.196601004,"35,432","35,723","1,868","1,982",518,532,186,260,"19,744","24,616","22,049","10,092"
2008,Washtenaw,26161,democrat,130578,20191203,2.420531643,"130,826","133,445","22,771","24,184",867,907,"14,233","14,362","72,732","152,802","83,356","32,705"
2008,Wayne,26163,democrat,660085,20191203,3.00609795,"501,227","515,624","362,573","422,073","5,441","6,047","25,705","26,368","489,158","663,209","482,521","230,170"
2008,Wexford,26165,democrat,7379,20191203,0.917329687,"16,011","16,082",127,97,114,139,85,110,"8,136","10,493","9,118","5,018"
2012,Alcona,26001,democrat,2472,20191203,0.692243069,"5,292","5,135",19,23,35,35,7,24,"1,450","1,991","3,607","3,522"
2012,Alger,26003,democrat,2212,20191203,0.949356223,"4,275","3,980",652,45,229,216,26,19,"1,528","2,733","3,108","2,073"
2012,Allegan,26005,democrat,20806,20191203,0.66850882,"53,614","53,948","1,032",974,476,483,390,531,"28,407","35,029","32,563","15,449"
2012,Alpena,26007,democrat,6549,20191203,0.897369142,"14,075","14,521",116,93,75,95,92,94,"5,838","8,228","9,161","5,934"
2012,Antrim,26009,democrat,5107,20191203,0.645067576,"11,307","11,440",66,65,145,144,33,46,"4,622","5,747","7,376","5,501"
2012,Arenac,26011,democrat,3669,20191203,0.90436283,"7,726","7,396",56,57,98,107,19,38,"2,966","4,209","5,018","3,304"
2012,Baraga,26013,democrat,1574,20191203,0.843515541,"3,442","3,186",659,55,674,682,12,11,"1,712","2,847","2,581","1,581"
2012,Barry,26015,democrat,11491,20191203,0.68994296,"29,121","28,789",266,197,189,189,117,143,"13,963","17,697","17,993","9,358"
2012,Bay,26017,democrat,27877,20191203,1.119063867,"50,432","52,535","1,311","1,149",384,386,327,406,"23,037","34,070","31,510","18,313"
2012,Benzie,26019,democrat,4685,20191203,0.923152709,"8,349","8,469",85,70,132,157,29,40,"3,450","4,543","5,416","3,922"
2012,Berrien,26021,democrat,33465,20191203,0.87584077,"62,197","64,172","12,117","13,554",618,607,"1,496","1,660","35,725","49,430","44,649","26,617"
2012,Branch,26023,democrat,6913,20191203,0.688888889,"21,379","20,820",874,139,149,125,130,153,"10,520","14,057","12,270","6,922"
2012,Calhoun,26025,democrat,29267,20191203,1.032965094,"55,537","58,504","8,233","8,363",612,588,"1,308","1,460","31,780","44,534","37,560","20,731"
2012,Cass,26027,democrat,9591,20191203,0.757642784,"23,555","23,678","1,764","1,646",359,351,201,233,"11,581","15,171","15,934","9,101"
2012,Charlevoix,26029,democrat,5939,20191203,0.742375,"12,509","12,807",101,95,253,276,47,74,"5,510","7,035","8,326","5,291"
2012,Cheboygan,26031,democrat,5831,20191203,0.800301949,"12,162","12,255",137,116,485,476,46,66,"4,898","6,799","8,118","5,928"
2012,Chippewa,26033,democrat,7100,20191203,0.857695095,"15,306","13,608","2,718",163,"3,370","3,411",174,207,"7,620","14,806","10,654","5,877"
2012,Clare,26035,democrat,6338,20191203,0.9069834,"15,082","15,064",169,104,141,129,40,63,"6,258","8,719","9,413","6,402"
2012,Clinton,26037,democrat,18191,20191203,0.880920097,"35,804","36,716","1,007",860,197,213,614,716,"18,239","25,461","21,861","10,566"
2012,Crawford,26039,democrat,2994,20191203,0.799679487,"6,898","6,754",67,61,50,51,21,44,"2,686","3,557","4,642","3,061"
2012,Delta,26041,democrat,8330,20191203,0.873715125,"17,525","17,781",136,112,562,521,76,120,"7,555","10,340","11,598","7,340"
2012,Dickinson,26043,democrat,4952,20191203,0.644120708,"12,729","12,895",93,90,113,88,70,87,"5,353","7,357","8,381","5,074"
2012,Eaton,26045,democrat,27913,20191203,1.065503684,"47,235","49,702","3,960","4,105",310,346,"1,126","1,118","24,248","35,431","31,832","16,391"
2012,Emmet,26047,democrat,7225,20191203,0.704671803,"15,175","15,646",186,141,723,710,94,117,"7,103","9,776","10,072","5,841"
2012,Genesee,26049,democrat,128978,20191203,1.796150847,"155,301","163,283","42,727","48,839","1,525","1,638","2,264","2,477","100,784","139,017","116,800","61,453"
2012,Gladwin,26051,democrat,5760,20191203,0.864735025,"12,621","12,518",85,61,74,77,37,57,"4,983","6,628","7,810","6,109"
2012,Gogebic,26053,democrat,4058,20191203,1.178281069,"7,693","7,104",689,49,219,231,20,32,"2,620","4,828","5,035","3,554"
2012,Grand Traverse,26055,democrat,20875,20191203,0.786726464,"41,891","43,766","1,105",390,635,650,335,398,"18,979","29,246","26,618","14,327"
2012,Gratiot,26057,democrat,7610,20191203,0.923431622,"19,773","19,172","2,380",142,159,137,83,109,"8,700","15,560","11,209","6,486"
2012,Hillsdale,26059,democrat,7106,20191203,0.605952076,"22,579","22,816",220,176,113,133,83,135,"10,555","14,601","13,378","7,721"
2012,Houghton,26061,democrat,6801,20191203,0.829795022,"18,774","16,091",242,155,138,128,701,426,"7,539","14,971","8,496","5,649"
2012,Huron,26063,democrat,6518,20191203,0.740177152,"15,854","16,053",117,106,58,64,86,100,"6,508","8,602","10,084","7,244"
2012,Ingham,26065,democrat,80847,20191203,1.784465634,"108,729","115,613","18,635","19,959","1,150","1,274","8,563","8,708","57,721","126,453","66,702","31,755"
2012,Ionia,26067,democrat,11018,20191203,0.769682152,"30,794","28,902","3,111",262,254,228,155,167,"15,256","23,408","17,410","7,799"
2012,Iosco,26069,democrat,6242,20191203,0.903459256,"12,271","12,497",130,117,122,120,81,104,"4,368","5,983","8,124","6,967"
2012,Iron,26071,democrat,2687,20191203,0.833436725,"5,578","5,719",40,42,69,76,10,28,"1,927","2,602","3,881","3,152"
2012,Isabella,26073,democrat,13038,20191203,1.207222222,"30,930","32,903","1,109","1,217","1,525","1,483",689,715,"12,259","36,868","14,299","7,145"
2012,Jackson,26075,democrat,32301,20191203,0.88988374,"71,734","70,909","8,996","5,919",462,378,722,788,"36,236","53,908","45,779","23,985"
2012,Kalamazoo,26077,democrat,69051,20191203,1.31121112,"105,034","109,204","15,626","16,490",814,893,"3,478","3,546","57,076","103,382","62,050","32,577"
2012,Kalkaska,26079,democrat,3272,20191203,0.667618853,"8,493","8,213",79,54,97,82,33,39,"3,764","5,025","5,223","3,078"
2012,Kent,26081,democrat,133408,20191203,0.855590829,"256,721","265,582","34,182","35,745","2,783","2,694","8,325","9,090","157,850","228,752","156,950","71,570"
2012,Keweenaw,26083,democrat,582,20191203,0.751937984,"1,099","1,052",7,4,2,1,0,1,384,472,717,593
2012,Lake,26085,democrat,2752,20191203,1.106554081,"5,205","4,970",576,555,66,56,8,22,"1,964","2,719","3,854","2,921"
2012,Lapeer,26087,democrat,18796,20191203,0.791944047,"43,076","42,834",958,276,265,260,190,274,"20,270","26,769","28,157","12,937"
2012,Leelanau,26089,democrat,6576,20191203,0.878791928,"10,013","10,161",67,93,435,479,52,65,"3,831","4,912","7,144","5,478"
2012,Lenawee,26091,democrat,21776,20191203,0.974274082,"47,132","47,285","2,325",875,363,322,294,382,"22,102","32,892","28,351","15,633"
2012,Livingston,26093,democrat,37216,20191203,0.619409816,"89,301","89,199",758,580,493,455,840,"1,108","44,288","55,906","58,321","24,219"
2012,Luce,26095,democrat,991,20191203,0.62721519,"2,804","2,497",735,27,194,193,11,14,"1,116","2,219","1,902","1,238"
2012,Mackinac,26097,democrat,2652,20191203,0.780688843,"4,421","4,242",105,85,"1,100","1,061",25,27,"1,945","2,787","3,747","2,587"
2012,Macomb,26099,democrat,208016,20191203,1.083907812,"355,306","370,568","40,619","47,735","1,815","1,985","14,830","15,894","190,159","288,099","243,636","126,858"
2012,Manistee,26101,democrat,6473,20191203,1.128290047,"11,602","11,409",816,96,328,308,39,61,"4,533","6,838","7,910","5,378"
2012,Marquette,26103,democrat,18115,20191203,1.331397913,"32,163","32,288","1,102",301,749,721,186,300,"12,390","25,958","18,946","10,516"
2012,Mason,26105,democrat,6856,20191203,0.904485488,"13,774","13,993",197,160,176,177,72,94,"6,057","8,063","8,745","5,778"
2012,Mecosta,26107,democrat,7515,20191203,0.818984307,"20,657","20,498",765,737,206,196,212,186,"8,375","17,605","10,569","6,908"
2012,Menominee,26109,democrat,5242,20191203,0.942127965,"11,446","11,298",96,68,352,358,42,56,"4,738","6,363","7,769","4,846"
2012,Midland,26111,democrat,17450,20191203,0.72954555,"39,172","40,652",781,600,224,229,929,"1,063","18,944","27,316","24,451","12,939"
2012,Missaukee,26113,democrat,2274,20191203,0.487459807,"7,476","7,224",58,56,54,57,28,37,"3,506","4,356","4,415","2,713"
2012,Monroe,26115,democrat,36310,20191203,1.02014441,"71,436","73,469","2,061","1,990",341,343,485,612,"35,147","47,914","45,739","21,937"
2012,Montcalm,26117,democrat,11430,20191203,0.839145437,"30,757","29,774","1,539",221,243,226,130,179,"14,739","20,955","17,845","9,530"
2012,Montmorency,26119,democrat,2049,20191203,0.699795082,"4,768","4,612",40,25,22,29,5,16,"1,519","2,069","3,230","2,699"
2012,Muskegon,26121,democrat,44436,20191203,1.438803264,"69,538","71,206","12,815","13,186","1,002","1,012",584,744,"41,286","56,671","47,634","24,496"
2012,Newaygo,26123,democrat,8728,20191203,0.700650237,"23,299","23,141",408,320,240,239,87,125,"11,412","14,332","14,186","7,929"
2012,Oakland,26125,democrat,349002,20191203,1.177016937,"469,885","485,983","80,895","100,169","2,523","2,728","39,369","39,858","278,238","408,961","361,006","173,205"
2012,Oceana,26127,democrat,5063,20191203,0.811508255,"12,766","12,717",132,120,222,215,45,59,"6,394","7,492","7,630","4,760"
2012,Ogemaw,26129,democrat,4791,20191203,0.881184477,"10,391","10,529",74,57,94,108,50,62,"4,158","5,562","6,704","4,941"
2012,Ontonagon,26131,democrat,1586,20191203,0.832109129,"3,215","3,047",21,21,41,47,7,12,911,"1,247","2,368","1,885"
2012,Osceola,26133,democrat,3981,20191203,0.648265755,"11,471","11,336",160,124,78,81,35,34,"5,605","6,747","6,769","4,198"
2012,Oscoda,26135,democrat,1657,20191203,0.717937608,"4,291","4,141",32,29,34,35,4,10,"1,690","2,057","2,736","2,093"
2012,Otsego,26137,democrat,4681,20191203,0.667665098,"11,527","11,888",122,94,134,98,52,99,"5,334","6,962","7,336","4,382"
2012,Ottawa,26139,democrat,42737,20191203,0.484733344,"125,141","129,606","3,122","2,682",865,929,"3,757","4,309","68,500","100,353","67,656","33,902"
2012,Presque Isle,26141,democrat,3192,20191203,0.841328413,"6,423","6,394",52,46,67,44,18,33,"2,222","2,876","4,400","3,579"
2012,Roscommon,26143,democrat,6198,20191203,0.924936577,"11,758","11,894",97,93,95,91,60,73,"3,779","5,235","8,154","6,993"
2012,Saginaw,26145,democrat,54381,20191203,1.272963483,"75,103","78,832","19,112","21,239",610,680,"1,281","1,393","44,789","66,372","55,103","31,986"
2012,St. Clair,26147,democrat,33983,20191203,0.86534593,"76,053","77,512","2,529","2,304",520,527,490,609,"36,449","49,620","49,339","25,136"
2012,St. Joseph,26149,democrat,10112,20191203,0.77916474,"28,700","29,189","1,114","1,027",210,220,210,268,"15,507","19,181","16,728","9,522"
2012,Sanilac,26151,democrat,7212,20191203,0.657849129,"20,623","20,951",188,131,127,118,81,86,"9,694","12,105","12,656","7,850"
2012,Schoolcraft,26153,democrat,1865,20191203,0.870681606,"3,655","3,752",38,32,417,437,7,9,"1,599","2,089","2,783","1,876"
2012,Shiawassee,26155,democrat,17197,20191203,1.077371257,"33,463","34,398",363,264,222,221,159,209,"15,924","22,050","20,594","10,731"
2012,Tuscola,26157,democrat,11425,20191203,0.802317416,"26,656","26,677",507,300,177,189,80,116,"12,142","16,662","16,516","9,382"
2012,Van Buren,26159,democrat,16290,20191203,1.00923115,"34,689","35,275","1,811","1,873",540,539,224,272,"18,535","23,197","22,267","11,224"
2012,Washtenaw,26161,democrat,120890,20191203,2.142983762,"133,089","135,704","23,848","25,033",986,"1,091","15,636","15,946","70,858","154,782","86,811","38,882"
2012,Wayne,26163,democrat,595846,20191203,2.786749231,"489,230","503,782","340,637","393,682","5,689","6,384","26,610","28,059","438,081","630,477","487,153","238,362"
2012,Wexford,26165,democrat,6184,20191203,0.73183432,"15,861","15,898",140,110,132,136,105,137,"7,690","9,920","9,488","5,421"
2016,Alcona,26001,democrat,1732,20191203,0.41228279,"5,148","5,034",33,43,38,45,10,32,"1,329","1,987","3,362","3,705"
2016,Alger,26003,democrat,1663,20191203,0.643326886,"4,073","3,786",685,54,238,242,18,19,"1,389","2,661","2,840","2,225"
2016,Allegan,26005,democrat,18050,20191203,0.528040254,"55,246","55,352","1,155","1,098",515,509,464,616,"28,283","36,141","32,653","17,878"
2016,Alpena,26007,democrat,4877,20191203,0.536523652,"13,794","14,260",124,101,88,102,92,96,"5,473","8,069","8,718","6,397"
2016,Antrim,26009,democrat,4448,20191203,0.525209588,"11,208","11,310",82,83,147,155,34,47,"4,264","5,668","7,143","5,991"
2016,Arenac,26011,democrat,2384,20191203,0.481616162,"7,460","7,287",64,59,97,102,16,42,"2,735","3,998","4,787","3,607"
2016,Baraga,26013,democrat,1156,20191203,0.535681186,"3,370","3,097",659,47,668,667,15,13,"1,583","2,690","2,494","1,769"
2016,Barry,26015,democrat,9114,20191203,0.474638059,"29,391","29,099",293,234,189,207,140,159,"13,341","17,933","17,758","10,680"
2016,Bay,26017,democrat,21642,20191203,0.763979102,"49,220","51,042","1,436","1,220",403,402,337,421,"21,517","32,647","30,182","20,135"
2016,Benzie,26019,democrat,4108,20191203,0.741650117,"8,395","8,554",86,93,149,167,35,45,"3,263","4,541","5,320","4,400"
2016,Berrien,26021,democrat,29495,20191203,0.763189898,"61,526","63,223","11,695","13,039",613,591,"1,666","1,804","34,104","47,958","43,025","29,070"
2016,Branch,26023,democrat,5061,20191203,0.429407772,"21,145","20,581",931,181,153,124,162,180,"10,245","13,642","12,045","7,525"
2016,Calhoun,26025,democrat,24157,20191203,0.767034991,"54,554","57,408","8,591","8,544",656,637,"1,797","1,991","31,095","43,940","36,403","22,740"
2016,Cass,26027,democrat,7270,20191203,0.510426174,"23,222","23,330","1,795","1,589",391,412,206,264,"10,658","14,847","15,511","10,193"
2016,Charlevoix,26029,democrat,5137,20191203,0.592229652,"12,437","12,765",125,104,260,272,74,85,"5,174","6,830","8,155","5,963"
2016,Cheboygan,26031,democrat,4302,20191203,0.495450881,"12,015","12,077",153,109,469,468,41,72,"4,351","6,489","7,946","6,618"
2016,Chippewa,26033,democrat,5379,20191203,0.589673317,"14,668","13,006","2,547",172,"3,407","3,482",190,224,"6,991","14,207","10,049","6,449"
2016,Clare,26035,democrat,4249,20191203,0.499588477,"14,794","14,900",177,126,147,148,47,67,"6,020","8,301","9,143","6,942"
2016,Clinton,26037,democrat,16492,20191203,0.762248105,"36,465","37,329","1,005",886,218,232,660,735,"17,605","25,096","22,501","12,328"
2016,Crawford,26039,democrat,2110,20191203,0.484611851,"6,764","6,591",91,83,53,57,36,64,"2,549","3,363","4,411","3,416"
2016,Delta,26041,democrat,6436,20191203,0.578724935,"17,177","17,409",161,134,574,578,79,113,"7,349","9,864","10,806","8,206"
2016,Dickinson,26043,democrat,3923,20191203,0.457226107,"12,416","12,461",107,104,129,124,80,94,"5,102","7,194","7,799","5,420"
2016,Eaton,26045,democrat,24938,20191203,0.903256185,"47,454","49,514","4,104","4,392",355,362,"1,380","1,286","23,249","35,827","30,787","18,984"
2016,Emmet,26047,democrat,6972,20191203,0.656744537,"15,276","15,618",204,171,709,716,99,123,"6,556","9,751","9,722","6,887"
2016,Genesee,26049,democrat,102751,20191203,1.220683101,"152,164","160,075","41,211","47,101","1,462","1,639","2,290","2,665","93,876","132,867","114,267","67,597"
2016,Gladwin,26051,democrat,3794,20191203,0.467011324,"12,404","12,266",101,91,82,85,54,61,"4,754","6,282","7,555","6,553"
2016,Gogebic,26053,democrat,2925,20191203,0.727974116,"7,361","6,706",673,63,249,233,24,40,"2,433","4,561","4,596","3,759"
2016,Grand Traverse,26055,democrat,20965,20191203,0.764783132,"43,378","44,799","1,075",433,708,730,352,439,"18,788","29,797","26,557","16,772"
2016,Gratiot,26057,democrat,5666,20191203,0.573481781,"19,254","18,638","2,271",186,195,142,97,149,"8,340","14,884","10,920","6,788"
2016,Hillsdale,26059,democrat,4799,20191203,0.340475346,"22,315","22,450",249,227,136,160,100,130,"10,091","14,163","13,017","8,496"
2016,Houghton,26061,democrat,6018,20191203,0.710088496,"18,442","15,892",291,169,152,134,721,486,"7,364","14,866","8,032","6,025"
2016,Huron,26063,democrat,4579,20191203,0.428264123,"15,277","15,568",140,131,66,76,95,98,"6,065","8,239","9,572","7,575"
2016,Ingham,26065,democrat,79110,20191203,1.803364639,"109,236","115,782","19,551","20,469","1,149","1,265","10,141","10,340","57,562","128,497","65,150","36,724"
2016,Ionia,26067,democrat,8352,20191203,0.50207394,"30,952","28,959","3,106",295,263,232,190,185,"14,642","23,104","17,529","8,907"
2016,Iosco,26069,democrat,4345,20191203,0.520671061,"12,208","12,321",158,120,133,131,86,114,"4,265","5,970","7,825","7,211"
2016,Iron,26071,democrat,2004,20191203,0.545306122,"5,404","5,472",49,42,79,81,17,38,"1,842","2,515","3,540","3,285"
2016,Isabella,26073,democrat,11404,20191203,0.924298914,"31,049","32,734","1,284","1,332","1,592","1,614",684,844,"12,346","35,904","14,640","8,243"
2016,Jackson,26075,democrat,25795,20191203,0.648229588,"70,772","70,080","8,852","6,065",462,375,758,851,"34,551","52,055","44,980","26,629"
2016,Kalamazoo,26077,democrat,67148,20191203,1.315750284,"106,504","110,712","16,728","17,522",842,879,"3,866","4,003","56,912","105,777","61,343","37,024"
2016,Kalkaska,26079,democrat,2280,20191203,0.372792675,"8,586","8,260",103,67,96,87,50,51,"3,677","5,034","5,167","3,422"
2016,Kent,26081,democrat,138683,20191203,0.93590903,"266,559","274,040","36,912","38,099","2,903","3,027","10,364","11,005","158,536","240,405","161,322","82,646"
2016,Keweenaw,26083,democrat,527,20191203,0.647420147,"1,092","1,026",5,7,6,1,0,2,347,453,626,713
2016,Lake,26085,democrat,1939,20191203,0.613801836,"5,316","5,058",710,583,78,75,13,28,"1,944","2,879","3,871","3,167"
2016,Lapeer,26087,democrat,12734,20191203,0.423943803,"43,077","42,578","1,002",288,296,265,270,365,"18,892","26,357","27,989","14,903"
2016,Leelanau,26089,democrat,6774,20191203,0.935764608,"9,996","10,240",81,116,427,500,62,71,"3,578","5,006","6,660","6,249"
2016,Lenawee,26091,democrat,16750,20191203,0.633749527,"46,661","46,855","2,475","1,052",406,344,308,409,"21,110","32,052","27,761","17,587"
2016,Livingston,26093,democrat,34384,20191203,0.523507917,"92,042","91,606",829,618,571,524,917,"1,251","41,609","56,795","60,086","29,868"
2016,Luce,26095,democrat,681,20191203,0.387813212,"2,753","2,411",725,31,211,188,11,11,"1,058","2,130","1,846","1,307"
2016,Mackinac,26097,democrat,2085,20191203,0.556891026,"4,213","4,055",181,151,"1,017","1,000",38,39,"1,744","2,669","3,435","2,846"
2016,Macomb,26099,democrat,176317,20191203,0.784799591,"354,014","367,171","48,686","57,594","1,819","2,119","17,582","18,518","186,304","290,325","250,138","140,736"
2016,Manistee,26101,democrat,4979,20191203,0.720028923,"11,436","11,276",847,112,335,307,58,67,"4,307","6,720","7,448","5,963"
2016,Marquette,26103,democrat,16042,20191203,1.095316127,"31,469","31,490","1,080",335,770,752,209,356,"12,032","24,923","17,554","11,952"
2016,Mason,26105,democrat,5281,20191203,0.620928865,"13,835","14,010",247,165,186,192,105,106,"5,930","8,044","8,442","6,430"
2016,Mecosta,26107,democrat,5827,20191203,0.565453663,"20,384","20,336",800,773,205,221,239,214,"8,044","16,950","10,587","7,591"
2016,Menominee,26109,democrat,3539,20191203,0.528051328,"11,247","10,895",122,89,391,364,43,70,"4,349","6,182","7,373","5,317"
2016,Midland,26111,democrat,15635,20191203,0.65566552,"38,971","40,231",889,674,232,247,"1,013","1,176","18,066","26,947","23,874","14,546"
2016,Missaukee,26113,democrat,1565,20191203,0.29056814,"7,472","7,164",71,67,69,80,55,54,"3,499","4,306","4,261","2,966"
2016,Monroe,26115,democrat,26863,20191203,0.620951897,"70,566","72,321","2,219","2,172",365,351,558,671,"32,612","46,627","44,665","25,319"
2016,Montcalm,26117,democrat,7874,20191203,0.465724256,"30,602","29,866","1,445",243,275,215,141,176,"14,299","20,399","17,720","10,545"
2016,Montmorency,26119,democrat,1287,20191203,0.367924528,"4,593","4,450",43,33,29,33,7,18,"1,373","1,951","3,065","2,817"
2016,Muskegon,26121,democrat,37304,20191203,1.032579511,"70,677","71,868","13,657","13,282","1,049","1,079",625,865,"40,717","57,573","47,311","27,501"
2016,Newaygo,26123,democrat,6212,20191203,0.409411455,"23,178","23,078",441,336,246,247,117,145,"10,819","14,053","14,084","8,832"
2016,Oakland,26125,democrat,343070,20191203,1.18626017,"474,599","486,251","83,031","101,479","2,488","2,785","48,080","47,049","267,987","416,815","362,385","198,575"
2016,Oceana,26127,democrat,3973,20191203,0.549667958,"12,739","12,570",233,168,238,223,51,59,"6,141","7,474","7,390","5,276"
2016,Ogemaw,26129,democrat,3030,20191203,0.443825985,"10,147","10,262",75,68,107,117,61,65,"3,853","5,408","6,420","5,221"
2016,Ontonagon,26131,democrat,1176,20191203,0.569215876,"2,955","2,820",19,24,34,48,15,16,742,"1,045","2,087","2,057"
2016,Osceola,26133,democrat,2705,20191203,0.368729553,"11,379","11,176",206,147,83,88,44,48,"5,316","6,642","6,522","4,691"
2016,Oscoda,26135,democrat,1044,20191203,0.367217728,"4,133","3,969",32,31,34,40,8,15,"1,561","1,941","2,553","2,207"
2016,Otsego,26137,democrat,3556,20191203,0.430195984,"11,735","11,926",152,116,147,106,65,138,"5,256","7,129","7,112","4,888"
2016,Ottawa,26139,democrat,44973,20191203,0.508359049,"130,992","134,711","3,627","3,032",941,970,"4,164","4,805","69,127","105,199","68,898","40,018"
2016,Presque Isle,26141,democrat,2400,20191203,0.534759358,"6,198","6,210",56,67,61,60,27,46,"2,065","2,804","4,015","3,841"
2016,Roscommon,26143,democrat,4287,20191203,0.526593785,"11,587","11,649",116,108,113,103,75,96,"3,583","5,026","7,732","7,506"
2016,Saginaw,26145,democrat,44396,20191203,0.976401504,"72,758","76,145","18,574","20,528",671,682,"1,395","1,532","41,558","63,069","52,455","35,203"
2016,St. Clair,26147,democrat,24553,20191203,0.500560641,"75,453","76,488","2,680","2,471",545,538,580,752,"34,125","48,181","49,009","28,192"
2016,St. Joseph,26149,democrat,7526,20191203,0.505643644,"28,678","29,023","1,162","1,063",210,215,217,264,"15,121","18,937","16,381","10,393"
2016,Sanilac,26151,democrat,4873,20191203,0.362412613,"20,154","20,426",210,152,147,128,81,94,"9,037","11,593","12,287","8,475"
2016,Schoolcraft,26153,democrat,1369,20191203,0.535602504,"3,472","3,596",42,29,412,423,9,7,"1,354","1,926","2,647","2,063"
2016,Shiawassee,26155,democrat,12546,20191203,0.652418097,"33,005","33,903",420,322,238,237,174,242,"14,845","21,444","20,383","11,869"
2016,Tuscola,26157,democrat,7429,20191203,0.434393638,"25,943","25,875",498,322,199,199,80,119,"11,126","15,842","15,949","10,318"
2016,Van Buren,26159,democrat,13258,20191203,0.741084405,"34,765","35,097","1,823","1,766",559,528,296,367,"17,893","22,876","21,702","12,730"
2016,Washtenaw,26161,democrat,128483,20191203,2.537635046,"137,316","139,530","24,545","25,454","1,006","1,093","17,867","17,941","69,133","162,206","86,313","47,100"
2016,Wayne,26163,democrat,519444,20191203,2.26838375,"482,435","494,101","326,586","378,467","5,698","6,445","30,766","32,100","418,990","607,212","471,383","259,013"
2016,Wexford,26165,democrat,4436,20191203,0.4436,"16,021","16,173",211,148,157,140,122,118,"7,790","9,904","9,377","6,019"
\ No newline at end of file