Pandas Datetime: Create a heatmap for comparison of the top 10 years in which the UFO was sighted vs each Month

Last update on May 03 2025 12:58:16 (UTC/GMT +8 hours)

24. Heatmap for Top 10 UFO Years vs. Each Month

Write a Pandas program to create a heatmap (rectangular data as a color-encoded matrix) for comparison of the top 10 years in which the UFO was sighted vs each Month.

Sample Solution:

Python Code:

import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
#Source: https://bit.ly/1l9yjm9
df = pd.read_csv(r'ufo.csv')
df['Date_time'] = df['Date_time'].astype('datetime64[ns]')
most_sightings_years = df['Date_time'].dt.year.value_counts().head(10)
def is_top_years(year):
   if year in most_sightings_years.index:
       return year
month_vs_year = df.pivot_table(columns=df['Date_time'].dt.month,index=df['Date_time'].dt.year.apply(is_top_years),aggfunc='count',values='city')
month_vs_year.columns = month_vs_year.columns.astype(int)
print("\nHeatmap for comparison of the top 10 years in which the UFO was sighted vs each month:")
plt.figure(figsize=(10,8))
ax = sns.heatmap(month_vs_year, vmin=0, vmax=4)
ax.set_xlabel('Month').set_size(20)
ax.set_ylabel('Year').set_size(20)

Sample Output:

Heatmap for comparison of the top 10 years in which the UFO was sighted vs each month:

For more Practice: Solve these Related Problems:

Write a Pandas program to create a heatmap that displays UFO sighting counts for each month across the top 10 years.
Write a Pandas program to generate a pivot table for monthly UFO sightings for the top 10 years and plot it as a heatmap.
Write a Pandas program to visualize the monthly distribution of UFO sightings for the top 10 years using a color-coded matrix.
Write a Pandas program to build and display a heatmap from a pivot table comparing months versus the top 10 UFO sighting years.

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Python Code Editor:

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