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

Pandas Datetime: Exercise-23 with Solution

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

Python Code Editor:

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