From dc116276f197ef3f08a38b012f6f150d0e9be6c0 Mon Sep 17 00:00:00 2001
From: Suliah <apatiras@msu.edu>
Date: Thu, 30 Jun 2022 10:30:19 -0400
Subject: [PATCH] Adding my files to the repository
---
Basic_Containers.ipynb | 188 +++++++++++++++++++++++++++++++++++
Functions_in_Python.ipynb | 200 ++++++++++++++++++++++++++++++++++++++
2 files changed, 388 insertions(+)
create mode 100644 Basic_Containers.ipynb
create mode 100644 Functions_in_Python.ipynb
diff --git a/Basic_Containers.ipynb b/Basic_Containers.ipynb
new file mode 100644
index 0000000..35eff7b
--- /dev/null
+++ b/Basic_Containers.ipynb
@@ -0,0 +1,188 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "id": "3c2a4f39",
+ "metadata": {},
+ "source": [
+ "# Basic Containers\n",
+ "Understanding and Using Basic Containers in Python"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "2b78245b",
+ "metadata": {},
+ "source": [
+ "\n",
+ "\n",
+ "\n",
+ "https://freesvg.org/img/387.png\n",
+ "\n",
+ "Python Language Logo from Free SVG\n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "71e867d9",
+ "metadata": {},
+ "source": [
+ "## Description\n",
+ "Many times, in using python, there will be a need to store values. A common way to do so and store the values under a single variable is to use basic containers. This page will breakdown the common container types in Python. \n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "58ec20e8",
+ "metadata": {},
+ "source": [
+ "## Self Assessment\n",
+ "\n",
+ "Click the following link to assess your knowledge on Basic Containers:\n",
+ "https://realpython.com/quizzes/pybasics-tuples-lists-dicts/ "
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "5d237ca9",
+ "metadata": {},
+ "source": [
+ "## Training Materials\n",
+ "\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "21f9b14e",
+ "metadata": {},
+ "source": [
+ "Video Description (URL Link to video)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "id": "deeec8f7",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/jpeg": 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+ "text/html": [
+ "\n",
+ " <iframe\n",
+ " width=\"100%\"\n",
+ " height=\"360\"\n",
+ " src=\"https://www.youtube.com/embed/aBqTgR-gP3g?cc_load_policy=True\"\n",
+ " frameborder=\"0\"\n",
+ " allowfullscreen\n",
+ " \n",
+ " ></iframe>\n",
+ " "
+ ],
+ "text/plain": [
+ "<IPython.lib.display.YouTubeVideo at 0x1cd12db60d0>"
+ ]
+ },
+ "execution_count": 1,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "from IPython.display import YouTubeVideo\n",
+ "YouTubeVideo(\"aBqTgR-gP3g\",width=\"100%\", height=360, cc_load_policy=True)"
+ ]
+ },
+ {
+ "cell_type": "raw",
+ "id": "08e8ef5c",
+ "metadata": {},
+ "source": [
+ "|Container Type|Mutable or Immutable|Initialization *Without* Values|Initializtion *With* Values|Adding Values to Container|Removing Values from Container|Modifying Values|Access Method|Notable Operations and Additional Information|\n",
+ "|---|---|---|---|---|---|---|---|---|\n",
+ "|**List**| Mutable |<ul><li>`a=list()` </li><li> `a=[]` </li></ul> | `a=['1', '2', '3']`| <ul><li>` list.append(item) #Adds item to the end of the list` </li><li> ` list.insert(index, item) #Adds item to the specified index in the list`</li></ul>|`list.remove(item) #removes the first instance of 'item' from the list. If there is not such element, this will cause an error`|`>>> a[0] = 'cat'` <br> `>>> a` <br> `['cat', '2', '3']` |Access by index: <br> `>>> a[0]` <br> `1`|See webpage at http://www.linuxtopia.org/online_books/programming_books/python_programming/python_ch14s07.html for some helpful methods when dealing with lists.|\n",
+ "|**Dictionary**|Mutable| `student={}` | `>>> student={'name': 'John Doe', 'age': 22, 'college': 'MSU'}` | `>>> student['major']='Computer Science'` <br> `>>> student` <br> `{'name': 'John Doe', 'age': 22, 'college': 'MSU', 'major': 'Computer Science'}` | `del dictName[keyName] #This method removes all entries associated with the given key` | `>>> student['age'] = 23` <br> `>>> student` <br> `{'name': 'John Doe', 'age': 23, 'college': 'MSU', 'major': 'Computer Science'}`| Access by key word. Note that this key **must** be a string. <br> `>>>student['college']` <br> `MSU`| The 'in' keyword can be very helpful with dictionaries. Ex: <br><ul><li>`'k' in dict #Returns true if key 'k' is in dictionary dict`</li><li>`'k' not in dict #Returns true if key 'k' is not in dicitonary dict`</li><li>`for key in dict #This will iterate over all keys in dictionary dict`</li></ul> <br>See webpage at http://www.python-course.eu/python3_dictionaries.php for additional helpful methods and operations|\n",
+ "|**Set**|Mutable. However the objects contained within a set **must** be immutable. | `s=set()`|`s=set(['a','b','c'])` | `s.add(item)`|<ul><li> `set.discard(item) #If item is in the set, the item is removed, otherwise nothing happens` </li><li> `set.remove(item) #If item is in the set, the item is removed, otherwise raise a KeyError` </li><li> `set.pop() #Remove and return an arbitrary element from the set. If the set is empty, raise a KeyError` </li>| Sets are unordered, therefore indexing does not mean anything. To modify a set, you must directly add or remove elements. |`>>> set.pop() #This will remove and return an arbitrary element from the set`|Some helpful methods include:<ul><li>`difference()`</li><li>`intersection()`</li><li>`isdisjoint()`</li><li>`union()`</li></ul><br> See webpage at http://www.programiz.com/python-programming/set for additional helpful methods and operations|\n",
+ "| **Tuple** |Immutable|<ul><li>`t=()`</li><li> `t=tuple()`</li><ul>|<ul><li>1-tuple:<br>`t=('Hello',)`</li><li> 2-tuple:<br> `t=('Hello', 'Goodbye')`</li><ul>|N/A|N/A|N/A|`t=('Hello','Goodbye','Goodnight')`<ul><li>Access By Index: <br> `>>> t[0]` <br> `'Hello'` </li><br><li> Access By Slice <br> `>>>t[0:1:2]` <br> `('Hello','Goodbye')`</li></ul>|<ul><li>Packing and Unpacking</li><br><li>Tuple to List: `list(tupleName)`</li></ul>|\n",
+ "| **NumPy Array\\***|Mutable|`a=np.array([])`| `a=np.array([1,2,3,4,5])` | <ul><li>`np.insert(arrayName,index,values,axis) #Inserts a value for an array at the given index.` </li><li>`np.append(arrayName,value,axis) #Appends values to the end of an array.`</li></ul>|`np.array(array,index/indices,axis) #Returns a new array with the given index or array of indices deleted on the given axis`|`>>> a[4] = 12` <br> `array([ 1, 2, 3, 4, 12])` <br><br> For additional information on manipulating NumPy Arrays see the webpage at http://docs.scipy.org/doc/numpy/reference/routines.array-manipulation.html |<ul><li>Access By Index: <br> `>>> a[0] `<br>` 1 `</li><li>Access By Slice: <br> `>>> a[0:5:2] `<br> `array([1, 3, 5])` </li></ul><br>See webpage at http://docs.scipy.org/doc/numpy/reference/arrays.indexing.html for further information about indexing of NumPy Arrays|See webpages at http://www.scipy-lectures.org/intro/numpy/array_object.html and https://docs.scipy.org/doc/numpy-dev/user/quickstart.html for additional information on NumPy Arrays|\n",
+ " \n",
+ "\\*Use of the NumPy Array requires the NumPy Python Module. Assuming import statement is \"import numpy as np\""
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "8bdbe577",
+ "metadata": {},
+ "source": [
+ "List – a data structure in Python that is a mutable ordered sequence of elements. \n",
+ "\tmy_list = [1, “worldâ€, 5.9]\n",
+ "\n",
+ "Dictionary – a mutable data storage method which is used to store data values in key : value pairs. \n",
+ "\tmy_dict = {‘msu’: 1, ‘spartans’ : ‘green’, “mcdonel’ : ‘hall’}\n",
+ " \n",
+ "Tuple – used to store multiple items in a single variable.\n",
+ "\tmy_tuple = (“appleâ€. “bananasâ€, “cherryâ€, “strawberryâ€)\n",
+ "\n",
+ "NumPy Array – a grid of values, all of the same type, and is indexed by a tuple of nonnegative integers. \n",
+ "\timport numpy as np\n",
+ "\tarr = np.array(1, 2, 3, 4, 5, 6)\n",
+ "\n",
+ "\tprint(arr)\n",
+ "\n",
+ "\toutput: [1, 2, 3, 4, 5, 6]\n",
+ "\n",
+ "Array – a collection of items stored at contiguous memory locations. Values can be accessed by referring to an index number. \n",
+ "\tcars = [“bmwâ€, “jeepâ€, “toyotaâ€, “kiaâ€]\n",
+ "\n",
+ "\n",
+ "Map – a built-in function that allows the user to process and transform all the items in a container in an iterable(such as a list or dictionary without using a loop.\n",
+ "\t# Return double of n\n",
+ "def addition(n):\n",
+ " \t\t return n + n\n",
+ " \n",
+ " # We double all numbers using map()\n",
+ " numbers = (1, 2, 3, 4)\n",
+ " result = map(addition, numbers)\n",
+ " print(list(result))\n",
+ "\t\n",
+ "\toutput: [2, 4, 6, 8]\n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "44b461a0",
+ "metadata": {},
+ "source": [
+ "---\n",
+ "\n",
+ "Written by Suliah Apatira, Michigan State University \n",
+ "As part of the Data Science Bridge Project \n",
+ " \n",
+ "<a rel=\"license\" href=\"http://creativecommons.org/licenses/by-nc/4.0/\"><img alt=\"Creative Commons License\" style=\"border-width:0\" src=\"https://i.creativecommons.org/l/by-nc/4.0/88x31.png\" /></a><br />This work is licensed under a <a rel=\"license\" href=\"http://creativecommons.org/licenses/by-nc/4.0/\">Creative Commons Attribution-NonCommercial 4.0 International License</a>."
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3 (ipykernel)",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.9.12"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/Functions_in_Python.ipynb b/Functions_in_Python.ipynb
new file mode 100644
index 0000000..f87bbdb
--- /dev/null
+++ b/Functions_in_Python.ipynb
@@ -0,0 +1,200 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "id": "3c2a4f39",
+ "metadata": {},
+ "source": [
+ "# Functions in Python\n",
+ "An Introduction to Creating and Using Functions in Python "
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "2b78245b",
+ "metadata": {},
+ "source": [
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "Coding [Day 102] photo found on Flickr by gerlos\n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "71e867d9",
+ "metadata": {},
+ "source": [
+ "## Description\n",
+ "The fundamental units of any Python program are functions. A function is a named segment of code with a name that carries out a specific action. Usually, this entails receiving some input, processing it, and then producing an output. Functions let you divide your code into distinct, reusable pieces. Functions can even be used outside of the original application in which they were defined. There are two types of functions called built-in functions and user-defined functions. Built-in functions are built into Python. Whereas, user-defined functions are defined by the users themselves. \n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "58ec20e8",
+ "metadata": {},
+ "source": [
+ "## Self Assessment\n",
+ "\n",
+ "1. Python Functions Quiz: Python Functions Quiz https://pynative.com/python-functions-quiz/\n",
+ "\n",
+ "\n",
+ "2. Python Functions Exercise: https://pynative.com/python-functions-exercise-with-solutions/\n",
+ "\n",
+ "\n",
+ "3. Python Basics: Chapter 06 – Functions and Loops Quiz: \n",
+ "https://realpython.com/quizzes/pybasics-functions-loops/\n",
+ "It is suggested that you are familiar with loops and functions before completing this quiz. There is a crash course on loops in training material #2. "
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "5d237ca9",
+ "metadata": {},
+ "source": [
+ "## Training Materials\n",
+ "\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "21f9b14e",
+ "metadata": {},
+ "source": [
+ "1. In this article, you'll learn about functions, what a function is, the syntax, components, and types of functions. Also, you'll learn to create a function in Python.\n",
+ "\n",
+ "https://www.programiz.com/python-programming/function#:~:text=In%20Python%2C%20a%20function%20is,and%20makes%20the%20code%20reusable\n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "ebf1e694",
+ "metadata": {},
+ "source": [
+ "2. In this 12 minute video, you'll get a crash course into statements & functions. "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "id": "ee42a54e",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
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\n",
+ "text/html": [
+ "\n",
+ " <iframe\n",
+ " width=\"100%\"\n",
+ " height=\"360\"\n",
+ " src=\"https://www.youtube.com/embed/l26oaHV7D40?cc_load_policy=True\"\n",
+ " frameborder=\"0\"\n",
+ " allowfullscreen\n",
+ " \n",
+ " ></iframe>\n",
+ " "
+ ],
+ "text/plain": [
+ "<IPython.lib.display.YouTubeVideo at 0x1c4b55e6c10>"
+ ]
+ },
+ "execution_count": 2,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "from IPython.display import YouTubeVideo\n",
+ "YouTubeVideo(\"l26oaHV7D40\",width=\"100%\", height=360, cc_load_policy=True)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "dd9c7fa5",
+ "metadata": {},
+ "source": [
+ "3. If you need more indepth help, this 30 minute video has a step-by-step breakdown of how to create and use functions in python. "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "id": "64684dfd",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/jpeg": 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X1xNC4t9EuicCR6isafQTHnuc9+HX3ve4uc98T3vc47S5znbXOPnK+haGCdPMamMlibwnFJUm1sxatqtf5c+vMcJUqueGjRVKzTvtW1fwOWJXklbTHtH71Dk+7a09Xl9bk+WYWa+pq6+rn05a7f1gtSSt8pqSundew1zg07NAlWB4Hbz7GBV+UJcaFyxSjJ2nkGsinjYT5mcsWgeQABV7JU9cBPiJ/tix7pUXDfSNCM8krXV7OLXv2kb3g82sZG3Q/wBDs0X7kfMfsX4CvmBq289FCIigBERAEREAREQEfcP/AInP0yv/AFir2VYTh/8AE5+mV/6xV7K9++jb+yf+WX6ROczT7bsRfXg/8UYX7Lo+7RLT6e8JuE4JPHXvSTNmmhE7GRQSS/iy98YcXNGqPCjdszz2LccH/ijC/ZdH3aJVz43/AI5p+yY/e7a6qlBTnZmHJ2RMmj/DTo7dlbC24YJJCGsFqGWuxxJyA5Z7eSBJIABcM81IMrGvaWuAc14LXNcAWuaRkQ4HYQR5F/PEq5PFuxWa3o7TdO5z31nz1mvcc3Oiglc2EEnp1Y9Vmf7xXK9BQV0RGVyE+HfQw6N4pUxLDPxFezNy9Zrc9Wpcgc2R0IH+wdmHNZ5uVb+S0Ky+gekkOL4dVxCHY21EC9meZimaSyaEnzska5uflyB8qj3jaV2vwBjz+VXxKs9h9bmTxH/4yFR5xUNMu5rsuETOyhxMmatmdjLkbPDYPNysTP1oGgbXKWnUpbXOv0G5nW8bTRDl6kOMQtzlw7KC1kNrqkr/AMW85bTyczvqFiQnoVY1/QfFaMVqCatO0SQ2oZIZWHofHI0se0/K0lUms6BWm4//AJPjPlnXRAyUjpruHKi2R0ForfjSB6Lh0hXMLV+rsvm/QiaJq4pGiPI1rGMzN/GXy6tUzG1tWJ/45483KTMA+Ss0+VTFpPpLQwyNkt+zFVZNJycbpXZa79UuLWgDM7Gk/Z5wsvBcOhp1oKtdupDUhjgib5o4mhjQT5TkNp8pzVQuMPpn+F8XkZE7Wp4Vr1a2Rza94cO6px59eRoaCNhbDGfKrMYutNvmJf1UWT77GjnxrU/Wd/4rb6MaZYXib5I6FuG0+BofI2IkljXEhpOYGwkH7FQ1TvxOPz7Ffodf9tIq6uGUYt3IU7ssjiV2KtDLYne2KGtE+aaR35McUbS973fvQ0E/UuS77GjnxrU/Wd/4rO4WvEGN+xcR90mVFlRQoKom2TKVi1HDbwh4JdwDEatXEK09ieOERxMc4ueW2YXkAFvka1x+pYXE58XYl7RZ7tEqyKzfE58XYl7RZ7tEr1WmoUml0kJ3Z1PGe+DN756j79XVO1cTjPfBm989R9+rqnaqwnodvyInvBV7+DLxJg/sfD/dIVRAq9/Bl4kwf2Ph/ukKpxm5EwK/ccLxrQ9mf2mZRToZo9Pit+th9bZJbk1dcglsUbQXyzPy/RYxrnZbM8gBtIUrccLxrQ9mf2mZbbidYG0vxLEnAF0Yiowu9HW/H2ftAq/YVVGexRuQ1eROGhGi1PB6cdKlGGRxjN7zkZZ5SAHzTvA8OR2XyAAAAAADX6b8IuD4M4R3rTWTPaHNrxMfPPqnoc6OIExsORyc/VByORWy05x1uGYbdvuAd3FWklawnISSAZRRk+TWkLG/xlRLE701qeWzYkdNYtSOlmlcc3Pe7pPqHQABsAAAyACx6NHyjbZVKVi5GivDFgGIzsrQ2jFPK4NjZaikriRxOQYyR45MvJyAbrZknYCu4xCnFYikgnjZNDOwskikaHxyMcMnNe12xwIX89iM9h8quNxcdLZMVwVndD3SWsNlNOaR5zfK1jGPglcTtc4xva0uO0ujefKpr4fYV0IyuV54c9APwDiAZDrGhfa6Wm5xLizVIEtZ7jtc6MuZkTtLZGZkkOWDwIfCLB/po/ZSKx/GcwNtvR+xKG5y4XLFcjPlDWu5Kfb6PIyyHLzsb5lXDgQ+EWD/AE0fspFkU6m3Sd99mUtWZd5VY4zfB13BZOL1GZUsQl/zpjRsrW3nPX2fkwzHM+YPzH6bQrR2p2RRvlkcGRwsdI9x6GsYC5zj6gAT9Sx8bwyC7Wmq2WNlr24nRSsPQ5jhlsI2tcNhDhtBAI2hYNKo4SuXGro/n2pi4ofj+x7Ete+4auE4TdDp8DxGWlNm+P8AdKs5GQsVnE6j9mwSDItcPI5p8haT3fFD8f2PYlr33DVsarTptroLS3lhuF34P437GxD3WVUXV6OF34P437GxD3WVUXVnB+i/eTM6vgi8d4d87L7tMrNKsvBF47w752X3aZWaXjP0of2jS/2V/wB5m9yn7J/xfyQREXmhtT9YwuIa0EucQAB0knoC4nTrhHhw+R9SjHDbtQksnszZvqwyDY+KGJpHLvacwXkgAjLI7cuj0wxd2H4ZduMOrM2Ntas4dLZ7TuTEjf30cfKP/iquBXtf0acD8NiaDzDFw2ryapxlrHTfJrnd9FfouchwjzepRkqFJ2drya3+47Z/CvjuZytRtHkaKVHIeoZwE5fKV576+PD/APLZuVDs64gleSV7L5twi/wo91fI5Djlfrv8Wdx32cf64zcqHZ15PC1j/XGblQ7OuHJXlxVLy/C+qj+C+RWsXX67/Fm90s0wxDFRCL04mFUyGICCvDqmXU1/3CNutnybOnPoXPkoSvJKvwhGEdmKsuhaIolKUneTu+lglWL4uUjmaPW3tJa5uKy5EdIzhpAquJKsfxfoizRqZztgs4jNKz1taa0BI/jxPH8UrneFc9nLarvZ7Lt77PcbbJI3xUfHOjsjidj/AGr/ALV+tsNnOpNqh7tjJwA0h3kEobscw+fpCwCV5cV88vGVJaVG5R54ybaf47n0Narenc9KeHg9ys+laH0mjcxzmOGTmEgj1j/svCzL5144Jv0ntMTz53xEAOPrLC37Fhrncdh1QrSgt2ji3v2Wk1f22av7bluDutd/P70ERFiFQREQBERAR9w/+Jz9Mr/1ir2VYTh/8Tn6ZX/rFXsr376Nv7J/5ZfpE5zNPtuxF9eD/wAUYX7Lo+7RKB+NXo7iFvFaktSjetxNwxkbpKtSxYY2QWbLixxhY7Vdquacj5wp44P/ABRhfsuj7tEt3n5PKuphU2J3MRq6KS6N8FGkF6RrGYfYrNcQHTXmOpxxj0nCYCRw9TGuPqVvOD7RmLB8Nq4dE4vFWM68hGqZZpHulml1czqh0j3kDM5DIZnJbm1ZjiaXyvZGwdLpHtY0fK5xyCjPhA4b8Hw6N7asrMTt5EMiqvD4Gu8hmtNzja0HpDNZ3qHSq51J1tEiElE5Xjg4/G2rRwxrhy09ju2Vo6WwQskij1h5A+SUkfR3eZVvp2ZIZI5onGOWvIyWKRv5Ucsbg+N7fW1zQfqWdpTj1rE7c125Jyk9l2biBqsY0DJkUTMzqRNbkANvRmSSSTrFn0qexGxabuy9nBnpVHjOF1b7MmvmZqWIx/qrMfgzx7durrAkZ9LXNPlWNNouDpHFjGqMmYLLSJ2bJe6o5Y3efW5N0zc/MSoC4qelrqmJuwt5Jr4wHOjHSI7kEbnh+XkD4WPaT544vMVapa6rF05NLwi7F3RHPGD0z/A+ESci7Vu4lrVauRyczWb+PsDyjk4ycj6b4vOqagZbPMpA4fdLXYtjVkjMV8Me+jWYdmyGRzZ5cvSklDjn06rYwehR+s7D09iPtZbk7sKd+Jx+fYp9DrftpFBCnficfn2KfQ637aRTiPs2I7ycuFrxBjfsXEfdJlRZXp4WvEGN+xcR90mVFlawfov3kzCs3xOfF2Je0We7RKsis3xOfF2Je0We7RKvFegRDeS5pro1WxelJQt8pyE7onP5J/JvzikZKzJ2Ry8JjVH3N70e/wDXb19xdlwp6VuwTC58RbALJrvrt5F0phDuWnjhJ5QMfllymf5Jzyy2dKhjnNTfE8X/ABJ3Y1h0o1Wvqbi42uc7Xm96Pf8Art6+4pPwXD46lavUi1uSpV4q8WsdZ3JwxtjZrO8rtVozKr3zmpvieL/iTuxqftF8TN2jSuFgjN+nWsmMO1xGZ4WSlgfkNYDXyzyGeXQFFWNRemFbmK3ccLxrQ9mf2mZSHxSq4ZgD3jpnxOy93ytjrwj+SIKPOOF41oezP7TMpA4o9kPwKZnlrYpYYf48NaYH5Pxh+wq9P7BEL0jZcaOYt0atNH+us0mH5Bail/njCp+ricZyqZNGrpaMzXlpy5D0RbhY8/IGvcfkBVO1dwnodvyKZ7wrBcTOweVxmLPwTHQkA8gcHXGuI9ZBb+qFX1WE4mdZ2vjMxHg6lCJp8hdnce8fKBqfrBV4n7N+OciG8mvhMgEuC4vGf9ZhN9vyE1Zcj9RyP1KoXAf8IsH+mj9lIrd8KNnkcDxiT0MJvEfwjWlDR9biB9aqJwH/AAiwf6aP2Uix8P6EvHMVS3ou1ahbJG+N4zbKxzHDzteC0j7Co04uWlhv4UKVh4dewJwpT5nN8kUebK1jpJILGFhcel0Lz5QpPVGtFtK7GC4y+/XzdydqwyeHPJtiu+Y8rC4+TPIEHyOYw7csjao09uLRVJ2LWcNGgUePYc6Fuq27V1paMztmrLl4UL3dIhlADT5iGOyJYAoP4p1eSHSO5DKx0csGEXIpY3jJ8ckd/DmPY4eRwcCD8isxo1jVfEakF2o/lK9uMSRu6DltDmPH6MjXBzXNO0FpHkXFXNHBT0sqYtC3KPHKNrDreQ6LUUbLcMh/hw0nNJ89dvlcpp1GouDDWtzfcLvwfxv2NiHusqour0cLvwfxv2NiHusqour+D9F+8omdXwReO8O+dl92mVmlWXgi8d4d87L7tMrNLxn6UP7Rpf7K/wC8ze5T9k/4v5IIiLzQ2pw/DvMRhVOPyS4o959fI1C0D/nFQmSpo4e2H8GUX+RmJTMPyvrNcP5Iz9ihUlfVnACyyLD26r/HaZ5ln93jZ9n6IEryShKk/gM0DixF0l+4wSVKsnJRQvzEc87WiSR8+W01omOYS0flueGnYCD0uNxlPC0pVam5fi+hL2tmuw+HlWmoR3sjanRsT58hBPOG7CYYZJciPIeTaclkHR/EOo3tzs/4atu3EBE1scADWRgNbs1GADoEcEeTI2+YZFeDjVj0x+o3+5ee1PpIwsZNbDfu1+S/C66GzqIcF5tekVJOj+IdRvbnZ/w15/yexE9FG+fV3FZ/w1bY43Z9MfqN/uXk45Z9MfqN/uVr/wBSsL6uXw+ZcXBWfXK56I8E+LXpGGxC/Dqzj4U1phZMR5WwVDlNLLl0AgN9asEasNKpBh9ZvJxVmMYGZhzmMjzLRI4bHzOc58jj6T16mxWd2fh6ut06jWsJ+VzRmsBxXH8I+GNTMo+TgrQ6N3vvq7u2nMkm9G7NbzK8jjhXtPV+PdYErwShK8ErhzoUjYMP+aj1WnfyxNz/AJgsZZEX5r//AFn9i1Y6wM1+1j/BH9DD+8/eERFrCQiIgCIiAj7h/wDE5+mV/wCsVeyrCcP/AInP0yv/AFir2V799G39k/8ALL9InOZp9t2Ivrwf+KML9l0fdolXHjgNBxqmchmMIj25bfzu2rG8H/inC/ZdH3aJV043/jmn7Jj97trrcP8AafiYUtxChjb05DPz5BekRbItBERAd1wA/CbCPpE3udlXWVKeAH4TYR9Im9zsq6y12M9Ne75l2G4oJpl4yxL2ne96lWqW10y8ZYl7Tve9SrVLYLcWgp34nH59in0Ot+2kUEKd+Jx+fYp9Dr/tpFaxH2bKo7ycuFrxBjfsXEfdJlRZXp4WvEGN+xcR90mVFlawfov3kzCs3xOfF2Je0We7RKsis3xOfF2Je0We7RKvFfZkQ3nU8Z74M3vnqPv1dU7VxOM98Gb3z1H36uqdqnCeh2/Ime8FXv4MvEmD+x8P90hVECr38GXiTB/Y+H+6QqnGbkTAr9xwvGtD2Z/aZll8T/SBsdq/hr3Zd2RR2oAdgMkGbJ2jzuMb43ZeaF3mWJxwvGtD2Z/aZlEGj+Lz0LVe7VdqWKcrZYnHaMxmHNcM/Cjc0ua4eVr3DyquENujYhu0i+OkmExX6dqlNnyV6vLA8jpDZWFms3zOGeYPnAVFNLNH7WF3JqNxhZNXcRnkQyaPMhk8JP5cLwMwflByIIFzuDHT6lj1UTV3BliNo7qpucOWrvOw7P04Sc9WQDIjzEOaNxpHo3QxFjY79Wvbawks5eJrzGT0mNxGtGT52kLFpVXSbTRXJXKDRsLnNa0Oc97g1jGtLnvc45NaxrdrnEkAAbTmrmcX/Q2TBsHZHYbqW70rrdlnSYnPaxkcBI8rI2Mzy2axfln0rf6O6C4Ph8nLUsPqQTAECZsTTK0HpDZX5vaD5gVsdJcdqYbWkt3ZmV4IR4T3npP6LGNHhSSHLIMaCT5Aqq1fyi2UiIxsRzxptIG1MCdVDspsXnjrsaD4XIxObPYfl6GqxsZ+faq88CHwiwf6aP2Ui88LenMuP4g605ro68LTDTgcRnFBnmXPyOXLPPhOI8zW5kMBXrgQ+EeD/TR+ykWTCnsUmnvsylu7LvL+fWM/nNn6VP8AtXr+gq/n1jX5zZ+lT/tXqzg97JqEp8W3hF/Bdv8AB1t+WH4lKAx7j4NS27JrZMz+TDJk1jvIDqO2DXJti5gOWYB1TmMwDkfOPMdp+1fzwIz2edWt4tXCN+Eqv4MuSZ38OiHJvec3W6jcmteSdrpo82sdntILHbSXZTiqP312iEuY7vhd+D+N+xsQ91lVF1ejhd+D+N+xsQ91lVF1OD9F+8iZ1fBF47w752X3aZWaVZeCLx3h3zsvu0ys0vGfpQ/tGl/sr/vM3uU/ZP8Ai/kgiIvNDanOcKuHm1gdwNGb8PlhvtHl1I9aGw75GwzOd/FVeiVayCQNO1oe1zXMkjcM2yRvBbJG4HpBaSFBPCPwe2MOkfPVZJZwx7i6KdgdI6u07eRtgZmN7OjXPguGRzzJaPoD6LeEFKpg3gKkrVINuKf3ot306bPT3WOH4S4CflVXitGrP2NHDEqzvBFG2PRmhq7DOZy4+cvuWXO/kjYPkaFV7lW+cfaFaHgsdnoxhZ9cvvV1dTw4k1lk7eNGYfB1J4rs/mjcOK8EoSvJK+fD0dIErw4r9AJ6ATl5gT/Mvwxv9F36p/uTZk9UitWPBK8Er6GJ/ou/VP8AcvBif6L/ANU/3KPJy6CtNdJ8yV5cV9OReehjyfUxxP8AMsyvh+plJZBY0bWwnZLKfIC3pZH5yVVDDzlq1aK3yekUva/De5XehM6sILV9nO/ce5xqQQR/pODp3jzcpk2P69Ro+0LFX0szOke57ul5zPmHkAHqAAH1L5rSY/EKvWc4+joo/wAMUkr+1pXftbMOKdtd+99uoREWGVBERAEREBH3D/4nP0yv/WKvaszwrYDYxLDjWqhhl7oik/GP1G6rNbW8LI7doUS96LGfRq7x9xe1cAc7wOEyzydetGMvKSdpNJ2tHU0OY0Kk6t4xbVuYxqPCzpHBFHDFiUjIq8bIomCvSIZHG0MY0F1ck5NAGZJOxaDSrSa/iszJ8QsOtTRRCFj3RwxlsYc54ZlCxrT4T3HMjPauo70WM+jV3j7id6LGfRq7x9xdmuEuULVYiH4oweK1uqzgEXf96LGfRq7x9xO9FjPo1d4+4q+VGVf5mHeXzI4pW6rOARd/3osZ9GrvH3E70WM+jV3j7icqMq/zMO8vmOKVuqzjcDxWxRsRW6khhs1nF0UoaxxYXMdGSGyNLT4L3DaD0rr+/HpP8aS7tQ7Mvfeixn0au8fcTvRYz6NXePuKl8Jcoe/EQ7yJ4rW6rOFt2HyySSyO15J5HyyOIALpJHF73ENAAzc4nYMtq+S7/vRYz6NXePuJ3osZ9GrvH3FPKjKf8zDvL5kcUrdVnALd6J6V4jhL5ZMOsuqvsMayVzY4ZNdrSXNBE0bgMiT0ZLpO9FjPo1d4+4neixn0au8fcR8J8pe/Ew7yHFK3VZh4pwqaQ2oJq1jEZJILcMkE0Zr0miSKVhZIwuZAHAFriMwQdq4xd/3osZ9GrvH3E70WM+jV3j7ihcJsoW7EQ7yJ4rW6rOAXR6J6cYthMckWHW31Y55BJI1sVeTWeGhgdnNE4jwQBsy6FvO9FjPo1d4+4neixn0au8fcUvhPlL0eIh3kRxSt1WavSPhHxzEa76l29JYrSljnxOgqMDjG9sjDrRQtcMntadh8i5Rd/wB6LGfRq7x9xO9FjPo1d4+4oXCbKVuxEO8ieKVuqzgF2uHcK+kVeGKvDiUkcNWKOGGMV6RDIomBkbAXVy45NaBmSTs2rK70WM+jV3j7id6LGfRq7x9xHwmyh78RDvIcVrdVnMaV6UYhisrJsRsOtSwx8kx7o4Yy2PWL9XKFjQfCcTmRntWnXf8Aeixn0au8fcTvRYz6NXePuKVwnylaLEw7yI4pW6rOIw69NWlZPXllgmiObJYZHRSMz6dV7CCAfKPKpHwfh40jrtDXT1reXQ61VaXZeYurOiLvlOZ9a1/eixn0au8fcTvRYz6NXePuKmXCXKJb8RDvInitbqs3N7jBaRSNLWmhASMteGo8vHrHdE0jc/lBUd6SaRX8SlE1+1PbkbnqmV+bYwekRRNyjhBy2hjQCur70WM+jV3j7id6LGfRq7x9xI8JMnjuxEO8g8LWf3WcAsvBsSnp2IrVWQw2Kz9eKUNY4sfkRmGyNLTsJ6Qeldp3osZ9GrvH3E70WM+jV3j7iq5T5T/mYd5fMjilbqs8d+PSf40l3ah2ZcNNI57nPcc3SOc5x2bXOJLjs2dJK7zvRYz6NXePuJ3osZ9GrvH3FC4S5Qt2Ih3kTxWt1WcAs3AsVsUbMNupI6GxVfrxSNyJaci0ghwIc0tLmlpBBDiD0rsu9FjPo1d4+4neixn0au8fcU8p8p/zMO8vmRxSt1WecY4YNIbdeerYuMfBcgkgmZ3JUbrRSsLJG6zIg5ubXEZgghcEu/70WM+jV3j7id6LGfRq7x9xRHhNlEd2Ih3kTxWt1Wavgi8d4d87L7tMrNKFtAODbFKWJ1LU7a4hryPc/Un1nZOhkYMm6u3a4KaV5B9ImYYfGY6nPDzU4qkk3F3Se1N209jRusspyhTakra8/uQREXAGyC+led8Z1mOcw+dpyz+XzhfNFXCcoNSi7NbmtGvcQ0nozKN+X0m/7qL/AMFkmw99Ylxz1bDANjWgDk3nIBoA6SftWsWdBtqyfvLEbj6gWPaD9uxb3LcwxVao4VKspLYlpKTktIt7m2iy6UItNJLVbjGJXglHFeSVcZnJGXh+JSQBwYGnXIz1g79HPLLVcPOVknSKfzR/8z/EWoJWXgzA57/BD3she+KNwzD5BlkNX9LIaxy8uS2OEx2KWzSp1GlzLo3vRb2+hc70LFahSs5yjcyjpJY80f8AzP8AEX0sYnNJAyXWLHcu+P8AFue0FoY1wzBcduZWLigLoGySMEcvLajSGCMyR6hLs2ADMA6u3Ly5LxH+Zs+lyfsmK5isfiXRqJ1G06e0r/Va+tG11zPt3ap2ZY8lScVKMbPat09P4g35z/rpf94/+9Y5JJzOZJ6SdpPylfiLjKlepU9OTfvbf6l1RS3IIiKyVBERAEREAREQBEWLi1vkK9ifV1+5q802pnq63JRuk1dbI6uerlnkelVRi5NJb2Q3YykVY2cauUgEYJH4QB8au8u3qK/edTN8SR/8Vd2FdTyJzf1X5ofuMXj1Hp+D+RZtFXfRTjKyXr9GkcHjiGI36tQyjEnSGLumeOHlAzuNuvq6+ermM8ukKxC0+Z5PisulGOJjsuSutVLT/wBrZepVoVNYsIiLWF0IiIAiIgCIiAIiIAiJ/wBkARczwoaXx4FhVnE5InT9z8myOBrgwyzTSNiiYZCDybNZ4JdkcmtdkCcgYe4NOMbLfxOtQv0III8RsR1oZ600rnRTTODIWyxyj8Yxzy1us0ty1gcjtW5wWQ43GYeeJowvCN7u6T0V3ZN3dl0e5alieIhCSjJ6ssOiItMXwiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgC+9KxyZOY1mSN1ZGZ5azenYfI4HaCvgiu0a06U1ODs1u8bmuZp6NaPQiSTVmZr6Bf4Vdwmb6GYbM31OjPT8rc81hTRPb+W1zfU5pb/On/ZZUeITtGQlky8xcSPsdmtxHMcPP04uL/0fWXZGTTXfYjOpH2+/R/z/AENcXhfsbXkjUDi4HZqAkg+rV25rZfhSx/tHfYz/AMV5fiVg7DLJ9Ti3+jkp47hFzz7sV8fKP9Cvy8+qvx/8TwcPneQ+y8xNy/LncTIR5mRk67j6ti/bczSGMjBbFCCGA/lEk5ue/L9Jx+zYvg4knM5knynaftK/Fi4vMvKxcKcbJ+k29qUra6uyVr62S32u3ZFDu7bXNuS0SCIi1ZIREQBERAEREAREQBazSvxff+gW/d5Fs1rNK/F9/wCgW/d5Few/2sf4l+pTLcz+fOhVFlq9hlWXW5K7foVpSwhrxHYsQwyajiCA7VecjkduStmeLXo56eKb3F2dVK0PxBtS5h1t7XPZQu0bT2My13srTxTOazWIGuQwgZkDMhWfPGjwr4txT7aX+OvaOFlPN5VKfm/atZ7Wy0tbq17tGkwjo2flOy50OB8XzAKdqrchfiRmoWoLUQfajczla8rJo9dogBczWYMxmMxmpMxXGqVQsFu1VqmUOMYs2IYC8Ny1iwSuGsBrNzy6NYedRtwacOdDHcRjw2vTvQSzRTSiSc1uTAhZruB5KVzsz8ijrjwj8fgPzGJ/08PXBwy3H5hmVPB5lOSk4tpu0mlaT01tq49JnurTp0nOktLlksLxStba59WxXssY7Uc+vNHOxr8g7Uc6JxAdk5pyO3Jw86YpilWo1r7VivVY92o19iaOBjn5F2o10rgC7JrjkNuQPmUJ8Sgf6FxH22/3Civzjrj/AENhvtpnuN5YXmKHnfzftu21s7VtfRvuLnGH5HylubcTThWNU7ZeKlqraMWqZBWsQzlgdnql4icdUHVdln06p8y+eJaQ4fVfyVm7SrS6odydi3Xhk1Tnk7UkeHapyO31FV14jw/HY98zhf8ATxBcpxwmg6S7QD/oml0/OWlsqXBSnPN55f5R7MYKW1bV6Re6/wDqLTxbVFVLb3u/Et3imL1KsBtWrFevWAae6J5o4ocn7WZSvcGnW8mR2+Rc9hvCdo7ZlbDDi+Gvle4NYzuqNhe47A1heQHuJ2ADPNVU0Z0V0l0zZAWyRmngdavh8E1uWSGpFyELGasTGMe+a25ga+SQNOZc0FzRqNHK8I+gt/AbTaeIsi1pouVilge6WvPHrFjjG97Guza4ZFrmgjMbMnAnaYTgTgZTeHq4n+n1exC2i9qerdtXu/DUtTx1RLaUfq9LP6BrxNK1jXPe5rGMaXOe8hrWtHS5zjsaB5yoo4qOks2I6PtjsPdJLhFuSiJHnWe+BscU9fWJ2nVjnEYJ25QhQlxouEKfEsTsYXFIW4bhExgdExx1LVuIjl5ZwNjxHIHRtacwOSLul2zncDwWrYnMZ4Lasqbe3P8A08zS6ZXVlf8AQyamLjGkqnTuRZOfhY0ZY7UdjWGZ/vLUcjf14yW/yrf4LpJh92F9indp2oIQXSSwWYZY4g0EuMrmOIiyAJOtlkAqeaDcBWPYtTjvRCnVr2WCSv3bPLHJPG4AslbHBBIWxOG0F2RIyIBBBMncCvAzieFux996OuLFvBpcOw+SKcSQym22UzEnVD4wHRVhm9oPhuy2ZraZnweyjD05eTxV6kWk4vZet0mrK26+ursk7lqlia0mrw0fOaXjU8IFoXatbCsVcKUuHh87cNuMDXTmxO08pPVdr56jWeAXZZZbNq7TisaSUK+jsbLd6nDOb9572WbkEcx15sw9zZZA863TmelVr4QNBb+j88NTEBAJZ64nZ3PLyrOT13xbXFjcna0btnyLd6CcDuM43TbfotpGu+WWIGeyYpNeF2o/Ngidsz8ua67F5Nl7yinQdZRpbSfldFtv61r62d7vn5jChXqeWctm76OguXpVRwzFcMniuvgmw21CHyTcu1sIjYRIydllrtVmq5rXB4OQLVGnBrwWaI0MRhs1MRGJXYnl9SGbEqM/JSNa4mSKCoxhlka3WOb9bV1dYAEZraY/gs2HaAWqFnU5eho1PBLybtdmuyBwOq7IZj1quHFnA/yswbYP3S9/0u8uUyjLassBi5UcRJU4Of1Y+jNRje+/TaWjtvRmV6qVSG1HV27Nf5F5FptJNKsMw0NOIXqdLlBmxtmxFE9487GOdrPHyArmuHnTs6P4PJahDTctStqUg8azRPI173TPb+k2OKOR+R2EtY0/lKn2h+i+K6T4lJHATZuTA2Ldy3K4MY3MN5WzNqudtOTWtaCfIG5NOWvyDgvHHUJYvE1PJ0Y8/O7b9Xokt19bvRIuYjF+TkoRV5F08H4StH7kjYa2LYdJLIdVkfdUbHvd6LGyEF7vUM11hVIOFHgWxXAavdk7qtumHsjllrOkzgdI4MZy0U0bSI3PLWhzSdrmggZhSVxR+EexLM7ALsrpmcg+bDZJXF0kfI7Zqeu45vj5P8YwfoiKUdGqG5WZ8E6CwbxmX1vKQj6Se+y32atqt7i0tNblFLGS29ipGzLDYrjVKoWC3aq1TKHGMWbEMBeG5axYJXDWA1m55dGsPOvoMTrGubYsQGqGGQ2hNH3OGA5F/L62pqAgjPPLYq2ceAfj8C+YxP8Ap0FGmhOF6QaTVq2BUnNdQwUSTasj3QVIXWZ5ZxJbe0OMspe6VsbQ0kBrsmjJ7kwHBClicvp42dbYi23Pa3RinJaO+rbSSTtv7GqY1xqOCjfo9+hbZnCto0X8mMawvWzyzNuIM/3pOpl9a7GN7XNDmkOa8BzXNIc1zSMw5rhsII25hUO4UODDFNHeQN4V5IbjnMisVZHyRcowaxifysbHsk1c3AFuRDXZE5HKbuJbpJNNVxHC5XF8eGPr2KmsSeTitGZssLQfyY2yQh4Hnnf0KrOeCeGoYDj2Dq7cFa97O6b2bpq26W9NdPQKGMlKp5Oasye8VxGvUidPamhrQR/lzWJWQxNz6NaSQho+1co3hZ0ZLtUYzhufrssDf1z4P8qrDxptJbF3SG1Uke7uXBTHXrQ5nUD3QRSzzlnQZXPkLdbp1WMC2+iXFyxDEMOq3xiFOA4hWitRQOhmlyinYJIuUnY4APLHNJDWuAJIzOSu0OCmBoYOniMwruDqJOKitFdXS3Sb03vRLd7SJYupKbjTje3j2FssLxGvbibNVngswv8AyZq8sc8TvLskicWn7VlKDeLZwTYho/dxOziPc+tNXgr1nVZ3SxStMj5LD3NcxjgQY4ANdoPhPy6TnOS5DNsLQw2JlTw9TykFa0l7UnbRu9tz9t9DMozlKN5Kz6AiItaXQiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgC1mlfi+/9At+7yLZrWaV+L7/ANAt+7yK9h/tY/xL9SmW5n89tEcPFu3h1Rzixt+5Sque0AuY2zPFC57QdhcA8kZ7NiszzWqHxrf/ANxV/wDFVz4MvG2B+2MJ99rr+h5XrPDnOsZgKtJYaeypKV9E72a6UzUYChContK5EXBhwFVMBxKPEor9qzJDFNEIpooGsImZqE5xgHMdKj/jwfu+BfMYn/Tw9WdVbeO/ReW4HaA/FsfiFZ580kraksQ+tsE/6i5jgzmdfGZ3Rq4me1LZlFN2WmxOy0SW9sysVSjCg1FdH6o3fEp8S4j7bf7hRX5x1vE2G+2me43lwPFh4UsNwOG/SxR8kEVqwy3BOyGaw3lOSbDLFIyBjntOUURDgCD4YOWQzwuMhwqwaQOrUsOZI6hh8jrT7Ekbo32J+TdEHMicNeKvHHJJteAXGQ7GhoLt9HJsW+Ejr+Tfk1La2/u22LaPc3fSy17DH8vDiuzfXdbn3nT8R/8Ad8e+Zwv+niC5TjgfCb/2ml+0trquI+4d0Y63ymDDCB6hJfB/pD7VyvHA+E3/ALTS/aW1m4b+9Nb/AGl/1plEv6pH3/zZPHFYaBonheQA1n4iT6z+FLozPnOQA+oKNePE0cpgB8pZiwJ9QOGEfzn7VJfFZ+CeFfw8R/6reUa8eL8vR/8Ag4v/AD4Wudyj+9M/92t+lQya39UXuj/I3fEi8WYp7XZ7nXVX8feZrdx0jtU2Ltl0jz+iZZ5C9x+TWJ+pWf4kh/0ZivtZnuddV94X9H34djmK05Glre7Z5othAfWtvdYgc0+UakgaSP0mPHkXWZLVis7xsPvPYa9yWv6ow66fkKb95f6KFsbWxsAayJoYxo6GsYA1rR6gAAvSgjg14xGEvoQR4zJNUvVomRSvFaxYhsmNoaJ43Vo3uY54ALmOAycTkSMiu64O+FfCseu2qeHmdxp12TiWaLkWzsMnJyGGN55TVY50QJc1v7qNnlPlmMyDH4ZzdSlLZhvnb6tr2upbnf2fM21PEU5Ws9/NzkE8dPx1h/sdvvlpSrxQ/gxD7Qv/ALdRbx1Y3DF8NeR4L8JLWnyF0duYvHygSM/WC2PFw4XMHwfB5MPxOaSvLBdnmhLa1iw2aKcMfsNeN2pIJOUGTshlqHM7cu6xmErYrg1QhQi5STi7R1drzW5a72a+E4wxUnJ28Im3hw+DWO+yLn7FyqdxaPhZg3zl7/pd5Wf4Rscr4nobil+qXGvewK3LEXt1X6pieCHtBOq4EEEZ7CFWDi0fCzBvnL3/AEu8rfBenKnk2NhJWa8omnvTVPVE4tp1qbXs/Uk/jwzv/wBAxZnk3HFJSPIZGDD2MPyhssg/jlZfEhrs7lxqbIco+5UhcfLyccD5GD1DWmk/+hbvjiaNyW8Gr3oWF7sEtGSbIEubTssEU7wAOhsjKzneZrXE/kqG+LbwlV9H7tpl7lBQxSOISSxsdKa89cyclKYmAudGWyyNdqAu/czkQCrmCozx3Bd0MOrzi3eK3tqpt29+y00ufciKklTxe1Ld/wDlv1LS8M8DZNHMea8AgYJiEgz9OGrLNGflD42n6gqd8AczmaUYGW9Jv6h/gyV543//ABe5TXw78N+EWMItYdhM7rljFIu5pJBBYihr15chOXOsMYXyOj1mBrc8i/M5ZZGN+Kho3Jd0hht6p7nwOKSzM/LweWmikr1Ys/TLpJJB6q7lXwewtXAZLip4qLipKVlLR6w2Vo+s9Fff+BGJmqleChru3e87HjwfnGBfMYn/AE6C6XiUNH4GxI5DM408E5bSBRo5AnzDM/aVzXHg/OMC+YxP+nQXTcSnxLiPtuT3CgsXEf3Tp+//AO2RXH+uPxzIyuObGDo/WJG2PGqxafMTUvNP8jiuF4kfjDGfoFP9vMu945Xweg9s1fdrq4LiR+MMZ+gVP28yYD+6tb3v/vAVP63HxzM+vGg4KLzr82OYdDJbgutjddggYZJ680UbIeVbCwF0sD2RsJ1QS1weT4JzEX6BcK2O4IBDTt69eJxHcNxndFdhB2sa1xEtcZ/oxvYMydmatXpPw04HhmKzYVeknhkrMhL7LYXTV2yTMEghfyGtK14Y6N2eoW+H0jJR3xiNJ9DsTwueWKenbxfVYKMtRrjbEmu3ZPI1o/zbU19Zspy9Ea+qsnJMzxVSjSweOwjnSkoqE9m62XbZcrpx0X3rppa2bKK9KCk5052fOvad/wACHC5W0jZJC+IU8Sqs5SWtr8pHLDrBpsVnkBzmBzmhzSM2F7drgQTJipjxSoJH6TwOjz1YKF2ScjoERjbEA71GaSH7ArnLkeF2V0Mvxzp0PRcVK2/Zu2rdPNfXpM3B1ZVKd5b72CIi5cywiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCx8UqieCeAktFmCWEuAzLRLG5hcAekjWzWQiqjJxd1vRDIG0d4tFKlbp224nckOH261lkboK4a91aZkzWOLdoBLAM/Wp5RFsMxzbFY+SliZ7Tju0Stf3JFunRhT9FWC0Gn+iVPG6EuH3WuMUpa9kkZDZoJmZ8nPC4ghsjcyNoIIc4EEEhb9FhUa06M1Upu0k7premi5KKkrPcViscVixyh5PGIeS1thkw9/KhuewENs6rnZeXMZ+YKStC+A3CcNoXqhMlqxi9KanZvStaJWQzM1SyrEPBrsDtV+WbnEsbrOcGtAlNFvcXwrzPEwUKlXRNPRKN2tVeyV9ebcY8MHSi7pfzIx4HuB+HRuzZsQXrFru2s2CSOaGJjRqSCRkgMe3MeGMv/wBh8yxOFbgQq6QYh+EJb1mq/uaGvycMUL26sLpHB2cm3M8ofsUsosVZ/jliXi1U/pWtlytHdppa1uZcxVxens7FtOg53g20UjwPC62FxSvsMpmciaRrWPfy9may7WazYMnTEbPIAud4ZuCuDSY0TNbnqHDBaDORjik5TurufW1uU6Mu5m5ZekVIiLGpZniaWJeLhO1Vtvast8r30tbW75it0ouOw1p0HD8D3BzDo3Ws1obM1oXLIsOfMxjHNcImRaoEewjJgK/OFfguw3SKNndQkgtV2lsF2vqiZjCdYxSNcC2aHWzOq7oJJaWkknuUVXnXFcZ43tvyt77S0e63MrbtLWs+cjyMNnYtp0FX5OKxa1vBxmuWZ/lOw+UPy/gi0Rn9akzge4FKej1g3e67F266B0GuWtr12xyFpkDK7C5xzLG/lvdlqjIA7VKiLY4zhXmeLpOjVq/Vas0lGN17WkmW4YSlB3S1OF4YuDSppJWiimkfWs03PfVtxsEhjMgAkjkicRysDtRhLdZpzjaQRtzhutxWLGuOVxmER57THh8hkIz25B9kNacvLt+tWeRW8BwmzHA0vI0KlocyaUrX6Lp211tuuTUwtOo9qS1OIwng4r1tHZdHI7Fh1eetbgNiUROmb3Y+SWVzWsa1gAfK8hvr6SuQ4OuACpguKVMUjxG3YfRMxbDLDAxjuWrzVjm5m0ZCYn6gpmRWIZ7joQqwjU0qtupovrOStLmurrosVPD0207bt3sPMsbXtcx7WvY9pa9jgHNc1wIc1zTsc0gkEHzqBNN+LNQsyvmwu4/DRI4uNWWHuuszPpEB5RkkLc/IS8DoGQyAn1Fay7N8Xl8nLDT2b71o0/emmn77aE1aMKitJFaMJ4rLuUBuYuDED4TatItlcPM2WaZzWH1ljvkU9aDaJUMFqNpYfDyMLXF73OcXyzyuADpp5XbZJCAB5gGgAAAAb1FkZlwgx2YRUMRUvFfdSUVf2qKV+3dzFNLDU6bvFEc8MnBRX0lfSfNbnqHDmWGt5GOKTXFgwl2tynRlyDejzlbHgf4PYdG6c9OGxLabauOtOkmYxjg50MMOqBHsyyhB+srtUWPLN8XLCrBuf9Et0bLpvvtfe77yryMNvbtr0nH8LegkWkVBlCaxLVZHbjtcpCxj3l0cc0YZlJsyPLE5/vQtLwOcEVfRqe3PDcsWzehiicJooowwRPc8Fpj6drj0qSkSnm+LhhXhIz/onvjZa6p77X3pc4dGDnt216SE+Eni8UsUtWL9a9ZpWrsrpphK0Xa7pHnNzmse9ksYPQAJC1oAAaAAFxlfis2dYcpjFcMz2lmHyOfl5cg6yAD9as+i2eH4X5rQpqnCrolZXUZNL3uLf4lqWCoyd2jjOCvg3w7R2u+KmJJZrJabNyctM82pnqM8BobHC3Wdkxo8pJLjtXZoi0WJxVXE1HVrS2pPe3v8dC5lojIhBRVluCIixyoIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIqX867SLqmC7ve7cnOu0i6pgu73u3Ls+QeadEe8YPnGiXQRUv512kXVMF3e925OddpF1TBd3vduTkHmnRHvDzjRLoIqX867SLqmC7ve7cnOu0i6pgu73u3JyDzToj3h5xol0EVL+ddpF1TBd3vduTnXaRdUwXd73bk5B5p0R7w840S6CKl/Ou0i6pgu73u3JzrtIuqYLu97tycg806I94ecaJdBFS/nXaRdUwXd73bk512kXVMF3e925OQeadEe8PONEugipfzrtIuqYLu97tyc67SLqmC7ve7cnIPNOiPeHnGiXQRUv512kXVMF3e925OddpF1TBd3vduTkHmnRHvDzjRLoIqX867SLqmC7ve7cnOu0i6pgu73u3JyDzToj3h5xol0EVL+ddpF1TBd3vduTnXaRdUwXd73bk5B5p0R7w840S6CKl/Ou0i6pgu73u3JzrtIuqYLu97tycg806I94ecaJdBFS/nXaRdUwXd73bk512kXVMF3e925OQeadEe8PONEugipfzrtIuqYLu97tyc67SLqmC7ve7cnIPNOiPeHnGiXQRUv512kXVMF3e925OddpF1TBd3vduTkHmnRHvDzjRLoIqX867SLqmC7ve7cnOu0i6pgu73u3JyDzToj3h5xol0EVL+ddpF1TBd3vduTnXaRdUwXd73bk5B5p0R7w840S6CKl/Ou0i6pgu73u3JzrtIuqYLu97tycg806I94ecaJdBFS/nXaRdUwXd73bk512kXVMF3e925OQeadEe8PONEugipfzrtIuqYLu97tyc67SLqmC7ve7cnIPNOiPeHnGiXQRUv512kXVMF3e925OddpF1TBd3vduTkHmnRHvDzjRLoIqX867SLqmC7ve7cnOu0i6pgu73u3JyDzToj3h5xol0EVL+ddpF1TBd3vduTnXaRdUwXd73bk5B5p0R7w840S6CKl/Ou0i6pgu73u3JzrtIuqYLu97tycg806I94ecaJdBFS/nXaRdUwXd73bk512kXVMF3e925OQeadEe8PONEugipfzrtIuqYLu97tyc67SLqmC7ve7cnIPNOiPeHnGiXQRUv512kXVMF3e925OddpF1TBd3vduTkHmnRHvDzjRLoIqX867SLqmC7ve7cnOu0i6pgu73u3JyDzToj3h5xol0EVL+ddpF1TBd3vduTnXaRdUwXd73bk5B5p0R7w840S6CKl/Ou0i6pgu73u3JzrtIuqYLu97tycg806I94ecaJdBFS/nXaRdUwXd73bk512kXVMF3e925OQeadEe8PONEgJERe3mgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiIAiIgCIiAIiID/9k=\n",
+ "text/html": [
+ "\n",
+ " <iframe\n",
+ " width=\"100%\"\n",
+ " height=\"360\"\n",
+ " src=\"https://www.youtube.com/embed/u-OmVr_fT4s?cc_load_policy=True\"\n",
+ " frameborder=\"0\"\n",
+ " allowfullscreen\n",
+ " \n",
+ " ></iframe>\n",
+ " "
+ ],
+ "text/plain": [
+ "<IPython.lib.display.YouTubeVideo at 0x1c4b55cc040>"
+ ]
+ },
+ "execution_count": 1,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "from IPython.display import YouTubeVideo\n",
+ "YouTubeVideo(\"u-OmVr_fT4s\",width=\"100%\", height=360, cc_load_policy=True)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "44b461a0",
+ "metadata": {},
+ "source": [
+ "---\n",
+ "\n",
+ "Written by Suliah Apatira, Michigan State University \n",
+ "As part of the Data Science Bridge Project \n",
+ " \n",
+ "<a rel=\"license\" href=\"http://creativecommons.org/licenses/by-nc/4.0/\"><img alt=\"Creative Commons License\" style=\"border-width:0\" src=\"https://i.creativecommons.org/l/by-nc/4.0/88x31.png\" /></a><br />This work is licensed under a <a rel=\"license\" href=\"http://creativecommons.org/licenses/by-nc/4.0/\">Creative Commons Attribution-NonCommercial 4.0 International License</a>."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "116d24a5",
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3 (ipykernel)",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.9.12"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
--
GitLab