Pandas: Split the specified dataframe into groups based on first column and set other column values into a list of values
Pandas Grouping and Aggregating: Split-Apply-Combine Exercise-13 with Solution
Write a Pandas program to split the following dataframe into groups based on first column and set other column values into a list of values.
Test Data:
X Y Z 0 10 10 22 1 10 15 20 2 10 11 18 3 20 20 20 4 30 21 13 5 30 12 10 6 10 14 0
Sample Solution:
Python Code :
import pandas as pd
df = pd.DataFrame( {'X' : [10, 10, 10, 20, 30, 30, 10],
'Y' : [10, 15, 11, 20, 21, 12, 14],
'Z' : [22, 20, 18, 20, 13, 10, 0]})
print("Original DataFrame:")
print(df)
result= df.groupby('X').aggregate(lambda tdf: tdf.unique().tolist())
print(result)
Sample Output:
Original DataFrame: X Y Z 0 10 10 22 1 10 15 20 2 10 11 18 3 20 20 20 4 30 21 13 5 30 12 10 6 10 14 0 Y Z X 10 [10, 15, 11, 14] [22, 20, 18, 0] 20 [20] [20] 30 [21, 12] [13, 10]
Python Code Editor:
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Previous: Write a Pandas program to split the following dataframe into groups, group by month and year based on order date and find the total purchase amount year wise, month wise.
Next: Write a Pandas program to split the following dataframe into groups based on all columns and calculate Groupby value counts on the dataframe.
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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
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