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


23. Top 10 UFO Years vs. Each Month

Write a Pandas program to create a comparison of the top 10 years in which the UFO was sighted vs each Month.

Sample Solution:

Python Code:

import pandas as pd
#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.index = month_vs_year.index.astype(int)
month_vs_year.columns = month_vs_year.columns.astype(int)
print("\nComparison of the top 10 years in which the UFO was sighted vs each month:")
print(month_vs_year.head(10))

Sample Output:

Comparison of the top 10 years in which the UFO was sighted vs each month:
Date_time   1    2    3    4    5    6    7    8    9    10   11   12
Date_time                                                            
1993       NaN  NaN  1.0  1.0  NaN  1.0  3.0  2.0  3.0  NaN  1.0  NaN
1994       2.0  NaN  3.0  2.0  2.0  NaN  NaN  1.0  NaN  NaN  NaN  1.0
1995       2.0  1.0  NaN  1.0  1.0  1.0  3.0  NaN  1.0  NaN  2.0  NaN
1996       NaN  1.0  NaN  1.0  1.0  1.0  3.0  3.0  1.0  NaN  1.0  NaN
1997       NaN  2.0  1.0  NaN  2.0  1.0  3.0  1.0  1.0  1.0  1.0  1.0
1998       1.0  2.0  1.0  3.0  NaN  2.0  1.0  NaN  NaN  1.0  NaN  2.0
1999       NaN  NaN  2.0  NaN  1.0  2.0  4.0  NaN  NaN  1.0  NaN  1.0
2000       NaN  3.0  2.0  NaN  2.0  1.0  1.0  NaN  NaN  NaN  1.0  2.0
2001       2.0  1.0  2.0  2.0  1.0  2.0  NaN  1.0  2.0  NaN  1.0  1.0
2002       3.0  1.0  1.0  NaN  3.0  NaN  2.0  1.0  2.0  1.0  NaN  NaN

For more Practice: Solve these Related Problems:

  • Write a Pandas program to extract the top 10 years with the highest UFO sightings and create a pivot table comparing monthly sightings.
  • Write a Pandas program to group the UFO dataset by year and month, then filter for the top 10 years and plot a grouped bar chart.
  • Write a Pandas program to build a pivot table of monthly UFO sighting counts for the top 10 years and visualize the trends.
  • Write a Pandas program to compare monthly UFO sightings for the top 10 years using a multi-level pivot table and plot the output.

Python Code Editor:

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Previous: Write a Pandas program to create a comparison of the top 10 years in which the UFO was sighted vs the hours of the day.
Next: 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.

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