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Adding new column using lists in Pandas DataFrame

schedule Aug 12, 2023
Last updated
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Adding a single column using a list

Consider the following DataFrame:

df = pd.DataFrame({"A":[3,4],"B":[6,7]}, index=["a","b"])
df
A B
a 3 6
b 4 7

To create column C using a list:

df["C"] = [8,9]
df
A B C
a 3 6 8
b 4 7 9

Adding multiple columns using a nested list

Consider the same DataFrame as above:

df
A B
a 3 6
b 4 7

To add a two columns using a nested list:

my_data = [[8,9],[10,11]]
pd.concat([df, pd.DataFrame(my_data, index=df.index, columns=["C","D"])], axis=1)
A B C D
a 6 8 8 9
b 7 9 10 11

Here, we first convert my_data into a DataFrame:

pd.DataFrame(my_data, index=df.index, columns=["C","D"])
C D
a 8 9
b 10 11

Note the following:

  • we set the index of this DataFrame to df.index since concat(~) requires the row labels to align to perform horizontal concatenation.

  • axis=1 for concat(~) means that we concatenate the DataFrames horizontally, as opposed to vertically.

robocat
Published by Isshin Inada
Edited by 0 others
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