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# Selecting columns that do not begin with certain prefix in Pandas DataFrame

schedule Aug 12, 2023
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PythonPandas
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Consider the following DataFrame:

``` df = pd.DataFrame({"aab":[1],"aac":[2],"bbb":[3]})df aab aac bbb0 1 2 3 ```

# Solution

To select columns that do not begin with `"aa"`:

``` df.iloc[:,~df.columns.str.startswith("aa")] bbb0 3 ```

# Explanation

We first start by fetching the columns that begin with the prefix `"aa"`:

``` df.columns.str.startswith("aa") array([ True, True, False]) ```

Since we want columns that do not start with `"aa"`, we flip the booleans using `~`:

``` ~df.columns.str.startswith("aa") array([False, False, True]) ```

Finally, to select columns that correspond to `True`:

``` df.iloc[:,~df.columns.str.startswith("aa")] bbb0 3 ```

Here, the `:` before the comma indicates that we want to fetch all the rows.

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