Breaking News: Grepper is joining You.com. Read the official announcement!

pandas set two columns on apply function

Add Answer

FishBrawler answered on September 22, 2020 Popularity 8/10 Helpfulness 4/10

answer pandas set two columns on apply function

related pandas apply function on two columns

related pandas pass two columns to function

related combine multiple columns in pandas dataframe

related apply on dataframe access multiple columns

related pandas combine two columns into one

related put two columns together in one column in pandas dataframe

related pandas assign multiple columns at once

related assign multiple columns pandas

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

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 pandas python set two-columns

Link to this answer
Share Copy Link

Contributed on May 11 2023

FishBrawler

0 Answers Avg Quality 2/10

Closely Related Answers

pandas apply function on two columns

Comment

def stream_half(col1, col2):
    if col1 == 'desktop':
        return col2/2
    else:
        return int(col2)
        
df['clean'] = df.apply(lambda row: stream_half(row['device'], 
  row['streams']), axis = 1)

Popularity 10/10 Helpfulness 5/10 Language python

Source: Grepper

Tags: function functio

Link to this answer
Share Copy Link

Contributed on Mar 30 2022

Kat

0 Answers Avg Quality 2/10

pandas pass two columns to function

Comment

#Method 1:
df["Delivery Charges"] = df[["Weight", "Package Size", "Delivery Mode"]].apply(
  lambda x : calculate_rate(*x), axis=1)

#Method 2:
df["Delivery Charges"] = df.apply(
  lambda x : calculate_rate(x["Weight"], 
  x["Package Size"], x["Delivery Mode"]), axis=1)

Popularity 10/10 Helpfulness 4/10 Language python

Source: codeforests.medium.com

Tags: function functio

Link to this answer
Share Copy Link

Contributed on May 14 2021

Exuberant Eland

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

Link to this answer
Share Copy Link

Contributed on Jan 29 2023

Niclas Bruhns

0 Answers Avg Quality 2/10

apply on dataframe access multiple columns

Comment

df['col_3'] = df.apply(lambda x: x.col_1 + x.col_2, axis=1)

Popularity 10/10 Helpfulness 4/10 Language python

Source: Grepper

Tags: apply appl

Link to this answer
Share Copy Link

Contributed on Mar 22 2022

Tirbo06

0 Answers Avg Quality 2/10

pandas combine two columns into one

Comment

df["station"] = df["End station"].combine_first(df["Start station"])
df.drop(["End station", "Start station"], 1, inplace=True)

Popularity 9/10 Helpfulness 2/10 Language python

Source: stackoverflow.com

Tags: combine

Link to this answer
Share Copy Link

Contributed on Nov 23 2022

FishBrawler

0 Answers Avg Quality 2/10

put two columns together in one column in pandas dataframe

Comment

# First dataframe with three columns
dlist=["vx","vy","vz"]
df=pd.DataFrame(columns=dlist)
df["vx"]=df1["v2x"]
df["vy"]=df1["v2y"]
df["vz"]=df1["v2z"]
# second dataframe with three columns
dlist=["vx","vy","vz"]
df0=pd.DataFrame(columns=dlist)
df0["vx"]=df2["v1x"]
df0["vy"]=df2["v1y"]
df0["vz"]=df2["v1z"]
# Here with concat we can create new dataframe with garther both in one
# YOU CAN PUT SOME VALUES IN EACH AND CHECK IT
# WHAT INSIDE THE CONCAT MUST BE A LIST OF DATAFRAME
v = pd.concat([df,df0])

Popularity 10/10 Helpfulness 2/10 Language python

Source: Grepper

Tags: dataframe data

Link to this answer
Share Copy Link

Contributed on Aug 05 2022

Itchy Iguana

0 Answers Avg Quality 2/10

pandas assign multiple columns at once

Comment

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

Link to this answer
Share Copy Link

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

Link to this answer
Share Copy Link

Contributed on Sep 22 2020

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

Link to this answer
Share Copy Link

Contributed on Mar 30 2022

Darkstar

0 Answers Avg Quality 2/10

pandas set two columns on apply function

Contents

More Related Answers

pandas set two columns on apply function

Closely Related Answers

pandas apply function on two columns

pandas pass two columns to function

combine multiple columns in pandas dataframe

apply on dataframe access multiple columns

pandas combine two columns into one

put two columns together in one column in pandas dataframe

pandas assign multiple columns at once

assign multiple columns pandas

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

Grepper

Documentation

Social

Legal

Contact

Oops, You will need to install Grepper and log-in to perform this action.