<jupyter_start><jupyter_text>Final Data Analysis<jupyter_code>import pandas as pd
import matplotlib.pyplot as plt

import os 
print (os.getcwd())
NY_mergedDF = pd.read_csv("Resources/NY_mask_mandates_v_accidents.csv")
NY_mergedDF.head()
NY_grouped_df = NY_mergedDF.groupby(['Date'])
print(NY_grouped_df)
NY_grouped_df.count().head(10)
NY_mask_mandates_passed = NY_grouped_df.count()["Face Masks Req in Public"]
plt.figure(figsize=(20,10))
NY_mask_mandates_passed.plot(kind="line")
plt.ylabel("Mask Mandates Passed")
plt.xlabel("Date")
plt.savefig("NY_mask_mandates_per_day.png")
plt.show()
x_axis = NY_mergedDF["Date"].unique()
y_axis = NY_mergedDF["Date"].value_counts()

plt.figure(figsize=(20,10))
plt.plot(x_axis, y_axis)
plt.xticks(rotation = 90)
plt.xlim(-0.25, len(x_axis))
plt.tick_params(axis='x', which='major', labelsize=5)
plt.xlabel('Date')
plt.ylabel('Number of Accidents per Day')
plt.savefig("NY_accidents_per_day.png")
plt.show()
GA_mergedDF = pd.read_csv("Resources/GA_mask_mandates_v_accidents.csv")
GA_mergedDF.head()
x_axis = GA_mergedDF["Date"].unique()
y_axis = GA_mergedDF["Date"].value_counts()

plt.figure(figsize=(20,10))
plt.plot(x_axis, y_axis)
plt.xticks(rotation = 90)
plt.xlim(-0.25, len(x_axis))
plt.tick_params(axis='x', which='major', labelsize=5)
plt.xlabel('Date')
plt.ylabel('Number of Accidents per Day')
plt.savefig("GA_accidents_per_day.png")
plt.show()<jupyter_output><empty_output>
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