1apt2(first draft).py

import matplotlib.pyplot as plt
import pandas as pd


df_full = pd.read_csv('Trips_Full Data.csv')


distance_columns = [
    'Trips <1 Mile', 'Trips 1-25 Miles', 'Trips 1-3 Miles', 'Trips 10-25 Miles',
    'Trips 100-250 Miles', 'Trips 100+ Miles', 'Trips 25-100 Miles', 'Trips 25-50 Miles',
    'Trips 250-500 Miles', 'Trips 3-5 Miles', 'Trips 5-10 Miles', 'Trips 50-100 Miles',
    'Trips 500+ Miles'
]


weekly_average = df_full.groupby('Week of Date')[distance_columns].mean()


weekly_average = weekly_average.reset_index().melt(id_vars=['Week of Date'], var_name='Distance Category', value_name='Average Trips')


plt.figure(figsize=(10, 7))


for category in weekly_average['Distance Category'].unique():
    subset = weekly_average[weekly_average['Distance Category'] == category]
    plt.bar(subset['Week of Date'], subset['Average Trips'], label=category)

plt.xlabel("Week")
plt.ylabel("Average Number of Trips")
plt.title("Average Number of Trips per Week by Distance Category")
plt.legend(title='Distance Category')
plt.xticks(rotation=90) # Rotate the x-axis labels for better readability
plt.grid(True) # Display grid
plt.show()
plt.savefig('Average Number of Trips per Week by Distance Category'.png')