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pandas assign multiple columns

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Danila answered on September 22, 2020 Popularity 9/10 Helpfulness 1/10

answer pandas assign multiple columns

related pandas set two columns on apply function

related combine multiple columns in pandas dataframe

related pandas assign multiple columns at once

related assign multiple columns pandas

related insert multiple column pandas

related how to create multiple columns after applying a function in pandas column python

related how to apply a function to multiple columns in pandas dataframe

related df multiple columns into one column

pandas assign multiple columns

Comment

-1

In [1069]: df.assign(**{'col_new_1': np.nan, 'col2_new_2': 'dogs', 'col3_new_3': 3})
Out[1069]:
   col_1  col_2 col2_new_2  col3_new_3  col_new_1
0      0      4       dogs           3        NaN
1      1      5       dogs           3        NaN
2      2      6       dogs           3        NaN
3      3      7       dogs           3        NaN

Popularity 9/10 Helpfulness 1/10 Language python

Source: stackoverflow.com

Tags: add assign multiple-columns pandas python

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Contributed on Jul 14 2022

Danila

0 Answers Avg Quality 2/10

Closely Related Answers

pandas set two columns on apply function

Comment

This allows f to be a user-defined function with multiple input values and uses column names rather than numeric indices to access the columns

df['new_column'] = df.apply(lambda x: f(x.col_1, x.col_2), axis=1)

Popularity 8/10 Helpfulness 4/10 Language python

Source: Grepper

Tags: apply function f

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Contributed on May 11 2023

FishBrawler

0 Answers Avg Quality 2/10

combine multiple columns in pandas dataframe

Comment

cols = ['foo', 'bar', 'new']
df['combined'] = df[cols].apply(lambda row: '_'.join(row.values.astype(str)), axis=1)

Popularity 9/10 Helpfulness 4/10 Language python

Source: stackoverflow.com

Tags: combine

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Contributed on Jan 29 2023

Niclas Bruhns

0 Answers Avg Quality 2/10

pandas assign multiple columns at once

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df = pd.DataFrame({'col1':[0,1,2], 'col2':[0,1,2], 'col3':[0,1,2]})

df
   col1  col2  col3
0     0     0     0
1     1     1     1
2     2     2     2

df['col1'], df['col2'], df['col3'] = zip(*df.apply(lambda r: (1, 2, 3), axis=1))

df
   col1  col2  col3
0     1     2     3
1     1     2     3
2     1     2     3

Popularity 10/10 Helpfulness 2/10 Language python

Source: Grepper

Tags: assign as

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Contributed on Jan 12 2022

serhii_rb

0 Answers Avg Quality 2/10

assign multiple columns pandas

Comment

import pandas as pd

df = {'col_1': [0, 1, 2, 3],
        'col_2': [4, 5, 6, 7]}
df = pd.DataFrame(df)

df[[ 'column_new_1', 'column_new_2','column_new_3']] = [np.nan, 'dogs',3]  #thought this wo

Popularity 10/10 Helpfulness 2/10 Language python

Source: www.edureka.co

Tags: assign as

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Contributed on Sep 22 2020

0 Answers Avg Quality 2/10

insert multiple column pandas

Comment

df['column_new_1'], df['column_new_2'], df['column_new_3'] = [np.nan, 'dogs', 3]

Popularity 9/10 Helpfulness 1/10 Language python

Source: stackoverflow.com

Tags: insert in

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Contributed on Apr 13 2022

Nutty Nightingale

0 Answers Avg Quality 2/10

how to create multiple columns after applying a function in pandas column python

Comment

>>> df = pd.DataFrame([[i] for i in range(10)], columns=['num'])
>>> df
    num
0    0
1    1
2    2
3    3
4    4
5    5
6    6
7    7
8    8
9    9

>>> def powers(x):
>>>     return x, x**2, x**3, x**4, x**5, x**6

>>> df['p1'], df['p2'], df['p3'], df['p4'], df['p5'], df['p6'] = \
>>>     zip(*df['num'].map(powers))

>>> df
        num     p1      p2      p3      p4      p5      p6
0       0       0       0       0       0       0       0
1       1       1       1       1       1       1       1
2       2       2       4       8       16      32      64
3       3       3       9       27      81      243     729
4       4       4       16      64      256     1024    4096
5       5       5       25      125     625     3125    15625
6       6       6       36      216     1296    7776    46656
7       7       7       49      343     2401    16807   117649
8       8       8       64      512     4096    32768   262144
9       9       9       81      729     6561    59049   531441

Popularity 10/10 Helpfulness 1/10 Language python

Source: stackoverflow.com

Tags: function functio

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Contributed on Mar 30 2022

Darkstar

0 Answers Avg Quality 2/10

how to apply a function to multiple columns in pandas dataframe

Comment

-1

>>> print df
   A  B  C
0 -1  0  0
1 -4  3 -1
2 -1  0  2
3  0  3  2
4  1 -1  0
>>> print df.applymap(lambda x: x>1)
       A      B      C
0  False  False  False
1  False   True  False
2  False  False   True
3  False   True   True
4  False  False  False

Popularity 10/10 Helpfulness 1/10 Language python

Source: stackoverflow.com

Tags: apply appl

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Contributed on Oct 17 2021

Darkstar

0 Answers Avg Quality 2/10

df multiple columns into one column

Comment

-1

df.stack().reset_index()

   level_0   level_1  0
0        0  Column 1  A
1        0  Column 2  E
2        1  Column 1  B
3        1  Column 2  F
4        2  Column 1  C
5        2  Column 2  G
6        3  Column 1  D
7        3  Column 2  H

Popularity 10/10 Helpfulness 1/10 Language python

Source: stackoverflow.com

Tags: multiple-columns mult

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Contributed on Jul 27 2021

Benja

0 Answers Avg Quality 2/10

pandas assign multiple columns

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pandas assign multiple columns

Closely Related Answers

pandas set two columns on apply function

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pandas assign multiple columns at once

assign multiple columns pandas

insert multiple column pandas

how to create multiple columns after applying a function in pandas column python

how to apply a function to multiple columns in pandas dataframe

df multiple columns into one column

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