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# Adding new column using lists in Pandas DataFrame

schedule Aug 12, 2023
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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 Ba 3 6b 4 7 ```

To create column `C` using a list:

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

# Adding multiple columns using a nested list

Consider the same DataFrame as above:

``` df A Ba 3 6b 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 Da 6 8 8 9b 7 9 10 11 ```

Here, we first convert `my_data` into a DataFrame:

``` pd.DataFrame(my_data, index=df.index, columns=["C","D"]) C Da 8 9b 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.

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