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# Selecting rows from a Pandas DataFrame whose column values contain a substring

schedule Aug 11, 2023
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To select rows from a DataFrame where certain column values contain a specific substring, use the Series' `str.contains(~)` method.

Consider the following DataFrame:

``` df = pd.DataFrame({"A":["abc","abd","cc"],"B":["dd","ee","ff"]}, index=["a","b","c"])df A Ba abc ddb abd eec cc ff ```

# Solution

To select all rows where value for column `A` contains the substring `"ab"`:

``` mask = df["A"].str.contains("ab")df[mask] A Ba abc ddb abd ee ```

# Explanation

We first extract column `A` using `df["A"]` as a `Series`:

``` df["A"] a abcb abdc ccName: A, dtype: object ```

We then use the Series' `str.contains("ab")` method, which returns a Series of boolean where `True` indicates the presence of the input substring (`"ab"`):

``` mask = df["A"].str.contains("ab")mask a Trueb Truec FalseName: A, dtype: bool ```

We then finally use the `[~]` notation to extract the rows that correspond to `True`:

``` df[mask] A Ba abc ddb abd ee ```

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