pandas.DataFrame.to_sparse¶
-
DataFrame.
to_sparse
(self, fill_value=None, kind='block')[source]¶ Convert to SparseDataFrame.
Deprecated since version 0.25.0.
Implement the sparse version of the DataFrame meaning that any data matching a specific value it’s omitted in the representation. The sparse DataFrame allows for a more efficient storage.
Parameters: - fill_value : float, default None
The specific value that should be omitted in the representation.
- kind : {‘block’, ‘integer’}, default ‘block’
The kind of the SparseIndex tracking where data is not equal to the fill value:
- ‘block’ tracks only the locations and sizes of blocks of data.
- ‘integer’ keeps an array with all the locations of the data.
In most cases ‘block’ is recommended, since it’s more memory efficient.
Returns: - SparseDataFrame
The sparse representation of the DataFrame.
See also
DataFrame.to_dense
- Converts the DataFrame back to the its dense form.
Examples
>>> df = pd.DataFrame([(np.nan, np.nan), ... (1., np.nan), ... (np.nan, 1.)]) >>> df 0 1 0 NaN NaN 1 1.0 NaN 2 NaN 1.0 >>> type(df) <class 'pandas.core.frame.DataFrame'>
>>> sdf = df.to_sparse() # doctest: +SKIP >>> sdf # doctest: +SKIP 0 1 0 NaN NaN 1 1.0 NaN 2 NaN 1.0 >>> type(sdf) # doctest: +SKIP <class 'pandas.core.sparse.frame.SparseDataFrame'>