bigframes.pandas.DataFrame.insert

DataFrame.insert(loc: int, column: blocks.Label, value: SingleItemValue, allow_duplicates: bool = False)

Insert column into DataFrame at specified location.

Examples:

>>> df = bpd.DataFrame({'col1': [1, 2], 'col2': [3, 4]})

Insert a new column named ‘col3’ between ‘col1’ and ‘col2’ with all entries set to 5.

>>> df.insert(1, 'col3', 5)
>>> df
   col1  col3  col2
0     1     5     3
1     2     5     4

[2 rows x 3 columns]

Insert another column named ‘col2’ at the beginning of the DataFrame with values [5, 6]

>>> df.insert(0, 'col2', [5, 6], allow_duplicates=True)
>>> df
   col2  col1  col3  col2
0     5     1     5     3
1     6     2     5     4

[2 rows x 4 columns]

Parameters:

• loc (int) – Insertion index. Must verify 0 <= loc <= len(columns).

• column (str, number, or hashable object) – Label of the inserted column.

• value (Scalar, Series, or array-like) – Content of the inserted column.

• allow_duplicates (bool, default False) – Allow duplicate column labels to be created.

Raises:

• IndexError – If column index is out of bounds with the total count of columns.

• ValueError – If column is already contained in the DataFrame, unless allow_duplicates is set to True.