diff --git a/Seaborn_Tutorial_DTTD.ipynb b/Seaborn_Tutorial_DTTD.ipynb
index 6bbb45f1fb0488830a886ba296f420b04b901888..73595bfbd1d76dc1e31fc4095cd8109f8247353d 100644
--- a/Seaborn_Tutorial_DTTD.ipynb
+++ b/Seaborn_Tutorial_DTTD.ipynb
@@ -266,6 +266,9 @@
    "metadata": {},
    "source": [
     "# Line Plots\n",
+    "\n",
+    "seaborn.lineplot(data=None, *, x=None, y=None, hue=None, size=None, style=None, units=None, weights=None, palette=None, hue_order=None, hue_norm=None, sizes=None, size_order=None, size_norm=None, dashes=True, markers=None, style_order=None, estimator='mean', errorbar=('ci', 95), n_boot=1000, seed=None, orient='x', sort=True, err_style='band', err_kws=None, legend='auto', ci='deprecated', ax=None, **kwargs)\n",
+    "\n",
     "Line plots can be used for many things including time series and regression plotting. The most basic form would be to call seaborn using sns, then clarify lineplot. In the parentheses you simply need to define your x variable and y variable, as well as the dataset you want the software to use."
    ]
   },
@@ -424,6 +427,9 @@
    "metadata": {},
    "source": [
     "# Violin Plots\n",
+    "\n",
+    "seaborn.violinplot(data=None, *, x=None, y=None, hue=None, order=None, hue_order=None, orient=None, color=None, palette=None, saturation=0.75, fill=True, inner='box', split=False, width=0.8, dodge='auto', gap=0, linewidth=None, linecolor='auto', cut=2, gridsize=100, bw_method='scott', bw_adjust=1, density_norm='area', common_norm=False, hue_norm=None, formatter=None, log_scale=None, native_scale=False, legend='auto', scale=<deprecated>, scale_hue=<deprecated>, bw=<deprecated>, inner_kws=None, ax=None, **kwargs)\n",
+    "\n",
     "- A Violin Plot is similar to box plots, in that it shows the distribution of quantitative data across several levels of one, or more, categorical variables.\n",
     "- Unlike a box plot, in which all of the plot components correspond to actual datapoints, the violin plot features a kernel density estimation of the underlying distribution.\n",
     "- This type of plot allows the distributions to be compared, a great tool for data analysis."
@@ -884,7 +890,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3.11 (default)",
    "language": "python",
    "name": "python3"
   },
@@ -898,7 +904,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.8"
+   "version": "3.11.6"
   }
  },
  "nbformat": 4,