Collapse multiple columns in pandas

NumPy | Python Methods and Functions

To collapse multiple columns in Pandas, follow these steps:

Step # 1: Download NumPy and Pandas. 
Step # 2: Generate some random data and use it to create a Pandas dataframe. 
Step # 3: Convert multiple lists into one data frame by creating a dictionary for each named list. 
Step # 4: Then use the Pandas info frame in the dict. The data frame with data columns and a column for names is ready. 
Step # 5: Specify which columns should be collapsed. This can be done by specifying the mapping as a dictionary, where the keys are the names of the columns to be concatenated or collapsed, and the values ​​— the names of the resulting column.

Example 1:

# Python program collapse
# multiple columns with pandas

import pandas as pd

 
# sample data

n = 3

Sample_1 = [ 57 , 51 , 6 ]

Sample_2 = [ 92 , 16 , 19 ]

Sample_3 = [ 15 , 93 , 71 ]

Sample_4 = [ 28 , 73 , 31 ]

  

sample_id = zip ([ "S" ] * n, list ( range ( 1 , n + 1 )))

 

s_names = [`` .join ([w [ 0 ], str (w [ 1 ])]) for w in sample_id]

 

d = { `s_names` : s_names, ` Sample_1` : Sample_1, 

  ` Sample_2` : Sample_2, ` Sample_3` : Sample_3,

`Sample_4` : Sample_4}

 

df_1 = pd.DataFrame (d)

 

mapping = { `Sample_1` : `Result_1` ,

  `Sample_2` : ` Result_1`

  ` Sample_3` : `Result_2`

`Sample_4` : `Result_2` }

 

df = df_1.set_index ( `s_names` ). groupby (mapping, axis = 1 ). sum ()

  

df.reset_index (level = 0 )

Output:

Example 2:

# Python program collapse
# multiple columns with pandas

import pandas as pd

df = pd.DataFrame ({ `First` : [ `Manan` , `Raghav` , `Sunny` ],

  ` Last` : [ ` Goel` , `Sharma` , `Chawla` ],

`Age` : [ 12 , 24 , 56 ]})

  

mapping = { `First` : `Full Name` , ` Last` : `Full Name` }

  

df = df.set_index ( `Age` ) .groupby (mapping, axis = 1 ). sum ()

 

df.reset_index (level = 0 )

Exit:





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