modin.pandas.DataFrame.insert¶

DataFrame.insert(loc: int, column: Hashable, value: Scalar | AnyArrayLike, allow_duplicates: bool | NoDefault = _NoDefault.no_default) → None[source]¶

Insert column into DataFrame at specified location.

Raises a ValueError if column is already contained in the DataFrame, unless allow_duplicates is set to True.

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) –

  • allow_duplicates (bool, optional, default lib.no_default) –

See also

Index.insert

Insert new item by index.

Examples

>>> df = pd.DataFrame({'col1': [1, 2], 'col2': [3, 4]})
>>> df
   col1  col2
0     1     3
1     2     4
>>> df.insert(1, "newcol", [99, 99])
>>> df
   col1  newcol  col2
0     1      99     3
1     2      99     4
>>> df.insert(0, "col1", [100, 100], allow_duplicates=True)
>>> df
   col1  col1  newcol  col2
0   100     1      99     3
1   100     2      99     4
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Notice that pandas uses index alignment in case of value from type Series:

>>> df.insert(0, "col0", pd.Series([5, 6], index=[1, 2]))
>>> df
   col0  col1  col1  newcol  col2
0   NaN   100     1      99     3
1   5.0   100     2      99     4
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