Example 1: Filtering with axis set to 'columns' or 1
When axis is 'columns' or 1, then the regex pattern is applied to the column names of the DataFrame.
>>> df.filter(regex='[a-z].*s', axis = 'columns') masters stats 0 yes Advanced 1 yes Novice 2 yes Novice 3 no Advanced 4 no Advanced 5 yes Advanced 6 yes Advanced 7 no Novice 8 yes Advanced 9 yes Novice
Example 2: Filtering with axis set to 'rows' or 0
When axis is 'rows' or 0, then the regex pattern is applied to the values of the columns specified in the index_label of the DataFrame.
The index columns will be cast into VARCHAR columns in order to perform the match.
>>> df.filter(regex = '^Beg.+', axis = 0)
id masters gpa stats admitted
programming
Beginner 21 no 3.87 Novice 1
Beginner 22 yes 3.46 Novice 0
Beginner 39 yes 3.75 Advanced 0
Beginner 34 yes 3.85 Advanced 0
Beginner 38 yes 2.65 Advanced 1
Beginner 3 no 3.70 Novice 1
Beginner 1 yes 3.95 Beginner 0
Beginner 32 yes 3.46 Advanced 0
Beginner 40 yes 3.95 Novice 0
Beginner 29 yes 4.00 Novice 0