DataFrame.insert() ⚬ Entries

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DataFrame.insert() ⚬｜Documentation｜1st｜20251021121234-00-⌔

pandas.DataFrame.insert — pandas 2.3.3 documentation#pandas.DataFrame.insert

DataFrame.insert(loc, column, value, allow_duplicates=<no_default>)

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

Content of the inserted column.

allow_duplicates: bool, optional, default lib.no_default

Allow duplicate column labels to be created.

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

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

Printed 2026-06-28.

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