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Pandas: Split a given dataframe into groups and display target column as a list of unique values

Pandas Grouping and Aggregating: Split-Apply-Combine Exercise-20 with Solution

Write a Pandas program to split a given dataframe into groups and display target column as a list of unique values.

Test Data:

   id  type     book
0   A     1     Math
1   A     1     Math
2   A     1  English
3   A     1  Physics
4   A     2     Math
5   A     2  English
6   B     1  Physics
7   B     1  English
8   B     1  Physics
9   B     2  English
10  B     2  English

Sample Solution:

Python Code :

import pandas as pd
df = pd.DataFrame( {'id' : ['A','A','A','A','A','A','B','B','B','B','B'], 
                    'type' : [1,1,1,1,2,2,1,1,1,2,2], 
                    'book' : ['Math','Math','English','Physics','Math','English','Physics','English','Physics','English','English']})

print("Original DataFrame:")
print(df)
new_df = df[['id', 'type', 'book']].drop_duplicates()\
                         .groupby(['id','type'])['book']\
                         .apply(list)\
                         .reset_index()

new_df['book'] = new_df.apply(lambda x: (','.join([str(s) for s in x['book']])), axis = 1)
print("\nList all unique values in a group:")
print(new_df)

Sample Output:

Original DataFrame:
   id  type     book
0   A     1     Math
1   A     1     Math
2   A     1  English
3   A     1  Physics
4   A     2     Math
5   A     2  English
6   B     1  Physics
7   B     1  English
8   B     1  Physics
9   B     2  English
10  B     2  English

List all unique values in a group:
  id  type                  book
0  A     1  Math,English,Physics
1  A     2          Math,English
2  B     1       Physics,English
3  B     2               English

Python Code Editor:


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Python: Tips of the Day

Python: Time library

Time library provides lots of time related functions and methods and is good to know whether you're developing a website or apps and games or working with data science or trading financial markets. Time is essential in most development pursuits and Python's standard time library comes very handy for that.

Let's check out a few simple examples:

moment=time.strftime("%Y-%b-%d__%H_%M_%S",time.localtime())

import time
time_now=time.strftime("%H:%M:%S",time.localtime())
print(time_now)
date_now=time.strftime("%Y-%b-%d",time.localtime())
print(date_now)

Output:

11:36:34
2020-Nov-30