histograms for each of the latitude and longitude columns

gistfile1.txt

import matplotlib.pyplot as plt

# Creating separate histograms for each of the latitude and longitude columns
df = divvy_tripdata
plt.figure(figsize=(12, 8))

# Start Latitude
plt.subplot(2, 2, 1)
plt.hist(df['start_lat'], bins=30, color='skyblue', edgecolor='black')
plt.axvline(df['start_lat'].mean(), color='red', linestyle='dashed', linewidth=1)
plt.title('Start Latitude')
plt.xlabel('Start Latitude')
plt.ylabel('Frequency')
plt.grid(True)

# Start Longitude
plt.subplot(2, 2, 2)
plt.hist(df['start_lng'], bins=30, color='green', edgecolor='black')
plt.axvline(df['start_lng'].mean(), color='red', linestyle='dashed', linewidth=1)
plt.title('Start Longitude')
plt.xlabel('Start Longitude')
plt.grid(True)

# End Latitude
plt.subplot(2, 2, 3)
plt.hist(df['end_lat'].dropna(), bins=30, color='blue', edgecolor='black')  # Drop NA values for end_lat
plt.axvline(df['end_lat'].mean(), color='red', linestyle='dashed', linewidth=1)
plt.title('End Latitude')
plt.xlabel('End Latitude')
plt.ylabel('Frequency')
plt.grid(True)

# End Longitude
plt.subplot(2, 2, 4)
plt.hist(df['end_lng'].dropna(), bins=30, color='purple', edgecolor='black')  # Drop NA values for end_lng
plt.axvline(df['end_lng'].mean(), color='red', linestyle='dashed', linewidth=1)
plt.title('End Longitude')
plt.xlabel('End Longitude')
plt.grid(True)

plt.tight_layout()
plt.show()