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# Selecting columns 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 begin with `"aa"`:

``` df.iloc[:,df.columns.str.startswith("aa")] aab aac0 1 2 ```

# Explanation

We first begin by checking which columns have labels that begin with `"aa"`:

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

We then use the `iloc` property to extract the columns that correspond to `True`:

``` df.iloc[:,df.columns.str.startswith("aa")] aab aac0 1 2 ```

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

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