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# Combining two columns of type string in a Pandas DataFrame

schedule Aug 12, 2023
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# Solution

Consider the following DataFrame:

``` df = pd.DataFrame({"A":["a","b"], "B":["c","d"]})df A B0 a c1 b d ```

To combine columns `A` and `B`:

``` df["C"] = df["A"] + df["B"]df A B C0 a c ac1 b d bd ```

# Case of missing values

Be wary of the fact that concatenating a missing value (`NaN`) and a string will result in a `NaN`.

As an example, here's a DataFrame with a `NaN` entry:

``` df = pd.DataFrame({"A":["a","b"], "B":[np.nan,"d"]})df A B0 a NaN1 b d ```

Combining columns `A` and `B` gives:

``` df["C"] = df["A"] + df["B"]df A B C0 a NaN NaN1 b d bd ```

Observe how `"a" + nan = nan`.

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