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# Getting rows where values do not contain substring in Pandas DataFrame

schedule Aug 11, 2023
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To get rows where values do not contain a substring, use `str.contains(~)` with the negation operator `~`.

Consider the following DataFrame:

``` df = pd.DataFrame({"A":["aab","abc","def"],"B":[3,4,5]})df A B0 aab 31 abc 42 def 5 ```

# Solution

To get all rows where the value in column `A` does not contain the substring `"ab"`:

``` df[~df["A"].str.contains("ab")] A B2 def 5 ```

# Explanation

We first extract column `A` as a `Series`, and then check for the presence of `"ab"`:

``` df["A"].str.contains("ab") 0 True1 True2 FalseName: A, dtype: bool ```

Since we are interested in values that do not contain `"ab"`, we invert the booleans using `~`:

``` ~df["A"].str.contains("ab") 0 False1 False2 TrueName: A, dtype: bool ```

Finally, we pass this boolean mask into `[]` to extract the rows from `df` corresponding to `True` in the mask:

``` df[~df["A"].str.contains("ab")] A B2 def 5 ```
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