rename columns in python
df.rename(columns={'oldName1': 'newName1',
'oldName2': 'newName2'},
inplace=True, errors='raise')
# Make sure you set inplace to True if you want the change
# to be applied to the dataframerename columns in python
df.rename(columns={'oldName1': 'newName1',
'oldName2': 'newName2'},
inplace=True, errors='raise')
# Make sure you set inplace to True if you want the change
# to be applied to the dataframerename df column
import pandas as pd
data = pd.read_csv(file)
data.rename(columns={'original':'new_name'}, inplace=True)python: change column name
df = df.rename(columns = {'myvar':'myvar_new'})change column name df
>>> df = pd.DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]})
>>> df.rename(columns={"A": "a", "B": "c"})
a c
0 1 4
1 2 5
2 3 6Renaming row value in pandas
# if the row value in column 'is_blue' is 1
# Change the row value to 'Yes'
# otherwise change it to 'No'
df['is_blue'] = df['is_blue'].apply(lambda x: 'Yes' if (x == 1) else 'No')
# You can also use mapping to accomplish the same result
# Warning: Mapping only works once on the same column creates NaN's otherwise
df['is_blue'] = df['is_blue'].map({0: 'No', 1: 'Yes'})dataframe rename column
df = pd.DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]})
# Option 1
df.rename({"A": "a", "B": "c"}, axis=1)
# Option 2
df.rename(columns={"A": "a", "B": "c"})
# Result
a c
0 1 4
1 2 5
2 3 6Copyright © 2021 Codeinu
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