Answers for "pandas multiple columns"

0

set dtype for multiple columns pandas

import pandas as pd

df = pd.DataFrame({'id':['a1', 'a2', 'a3', 'a4'],
  				   'A':['0', '1', '2', '3'],
                   'B':['1', '1', '1', '1'],
                   'C':['0', '1', '1', '0']})

df[['A', 'B', 'C']] = df[['A', 'B', 'C']].apply(pd.to_numeric, axis = 1)
Posted by: Guest on August-17-2020
1

how to pick out separate columns from the pandas dataframe object

df1 = df.iloc[:, 0:2] # If you want to do it by index. Remember that Python does not slice inclusive of the ending index.
df1 = df[['a', 'b']] ## if you want to do it b nae
Posted by: Guest on October-21-2020
2

python add multiple columns to pandas dataframe

# Basic syntax:
df[['new_column_1_name', 'new_column_2_name']] = pd.DataFrame([[np.nan, 'word']], index=df.index)
# Where the columns you're adding have to be pandas dataframes

# Example usage:
# Define example dataframe:
import pandas as pd
import numpy as np
df = pd.DataFrame({
    'col_1': [0, 1, 2, 3],
    'col_2': [4, 5, 6, 7]
})

print(df)
   col_1  col_2
0      0      4
1      1      5
2      2      6
3      3      7

# Add several columns simultaneously:
df[['new_col_1', 'new_col_2', 'new_col_3']] = pd.DataFrame([[np.nan, 42, 'wow']], index=df.index)
print(df)
   col_1  col_2  new_col_1  new_col_2 new_col_3
0      0      4        NaN         42       wow
1      1      5        NaN         42       wow
2      2      6        NaN         42       wow
3      3      7        NaN         42       wow

# Note, this isn't much more efficient than simply doing three
#	separate assignments, e.g.:
df['new_col_1'] = np.nan
df['new_col_2'] = 42
df['new_col_3'] = 'wow'
Posted by: Guest on November-11-2020
0

df only take 2 columns

df1 = df[['a', 'b']]
Posted by: Guest on August-06-2020
0

assign multiple columns pandas

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
Posted by: Guest on September-22-2020

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