create dataframe with column names pandas
In [4]: import pandas as pd
In [5]: df = pd.DataFrame(columns=['A','B','C','D','E','F','G'])
In [6]: df
Out[6]:
Empty DataFrame
Columns: [A, B, C, D, E, F, G]
Index: []create dataframe with column names pandas
In [4]: import pandas as pd
In [5]: df = pd.DataFrame(columns=['A','B','C','D','E','F','G'])
In [6]: df
Out[6]:
Empty DataFrame
Columns: [A, B, C, D, E, F, G]
Index: []change name of column pandas
#df.rename() will only return a new df with the new headers
#df = df.rename() will change the heders of the current dataframe
df = df.rename(columns={"old_col1": "new_col1", "old_col2": "new_col2"})rename column pandas
df_new = df.rename(columns={'A': 'a'}, index={'ONE': 'one'})
print(df_new)
# a B C
# one 11 12 13
# TWO 21 22 23
# THREE 31 32 33
print(df)
# A B C
# ONE 11 12 13
# TWO 21 22 23
# THREE 31 32 33rename column pandas
>>> df.rename(index={0: "x", 1: "y", 2: "z"})
A B
x 1 4
y 2 5
z 3 6name columns pandas
>gapminder.columns = ['country','year','population',
'continent','life_exp','gdp_per_cap']Copyright © 2021 Codeinu
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