pandas.DataFrame.set_index¶
-
DataFrame.
set_index
(keys, drop=True, append=False, inplace=False, verify_integrity=False)[source]¶ Set the DataFrame index using existing columns.
Set the DataFrame index (row labels) using one or more existing columns or arrays (of the correct length). The index can replace the existing index or expand on it.
Parameters: - keys : label or array-like or list of labels/arrays
This parameter can be either a single column key, a single array of the same length as the calling DataFrame, or a list containing an arbitrary combination of column keys and arrays. Here, “array” encompasses
Series
,Index
andnp.ndarray
.- drop : bool, default True
Delete columns to be used as the new index.
- append : bool, default False
Whether to append columns to existing index.
- inplace : bool, default False
Modify the DataFrame in place (do not create a new object).
- verify_integrity : bool, default False
Check the new index for duplicates. Otherwise defer the check until necessary. Setting to False will improve the performance of this method.
Returns: - DataFrame
Changed row labels.
See also
DataFrame.reset_index
- Opposite of set_index.
DataFrame.reindex
- Change to new indices or expand indices.
DataFrame.reindex_like
- Change to same indices as other DataFrame.
Examples
>>> df = pd.DataFrame({'month': [1, 4, 7, 10], ... 'year': [2012, 2014, 2013, 2014], ... 'sale': [55, 40, 84, 31]}) >>> df month year sale 0 1 2012 55 1 4 2014 40 2 7 2013 84 3 10 2014 31
Set the index to become the ‘month’ column:
>>> df.set_index('month') year sale month 1 2012 55 4 2014 40 7 2013 84 10 2014 31
Create a MultiIndex using columns ‘year’ and ‘month’:
>>> df.set_index(['year', 'month']) sale year month 2012 1 55 2014 4 40 2013 7 84 2014 10 31
Create a MultiIndex using an Index and a column:
>>> df.set_index([pd.Index([1, 2, 3, 4]), 'year']) month sale year 1 2012 1 55 2 2014 4 40 3 2013 7 84 4 2014 10 31
Create a MultiIndex using two Series:
>>> s = pd.Series([1, 2, 3, 4]) >>> df.set_index([s, s**2]) month year sale 1 1 1 2012 55 2 4 4 2014 40 3 9 7 2013 84 4 16 10 2014 31