pandas.DataFrame.to_sparse¶
-
DataFrame.
to_sparse
(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() >>> sdf 0 1 0 NaN NaN 1 1.0 NaN 2 NaN 1.0 >>> type(sdf) <class 'pandas.core.sparse.frame.SparseDataFrame'>