pandas.HDFStore.put#
- HDFStore.put(key, value, format=None, index=True, append=False, complib=None, complevel=None, min_itemsize=None, nan_rep=None, data_columns=None, encoding=None, errors='strict', track_times=True, dropna=False)[source]#
Store object in HDFStore.
- Parameters:
- keystr
Key of object to store in file.
- value{Series, DataFrame}
Value of object to store in file.
- format‘fixed(f)|table(t)’, default is ‘fixed’
Format to use when storing object in HDFStore. Value can be one of:
'fixed'
Fixed format. Fast writing/reading. Not-appendable, nor searchable.
'table'
Table format. Write as a PyTables Table structure which may perform worse but allow more flexible operations like searching / selecting subsets of the data.
- indexbool, default True
Write DataFrame index as a column.
- appendbool, default False
This will force Table format, append the input data to the existing.
- complibdefault None
This parameter is currently not accepted.
- complevelint, 0-9, default None
Specifies a compression level for data. A value of 0 or None disables compression.
- min_itemsizeint, dict, or None
Dict of columns that specify minimum str sizes.
- nan_repstr
Str to use as str nan representation.
- data_columnslist of columns or True, default None
List of columns to create as data columns, or True to use all columns. See here.
- encodingstr, default None
Provide an encoding for strings.
- errorsstr, default ‘strict’
The error handling scheme to use for encoding errors. The default is ‘strict’ meaning that encoding errors raise a UnicodeEncodeError. Other possible values are ‘ignore’, ‘replace’ and ‘xmlcharrefreplace’ as well as any other name registered with codecs.register_error that can handle UnicodeEncodeErrors.
- track_timesbool, default True
Parameter is propagated to ‘create_table’ method of ‘PyTables’. If set to False it enables to have the same h5 files (same hashes) independent on creation time.
- dropnabool, default False, optional
Remove missing values.
See also
HDFStore.info
Prints detailed information on the store.
HDFStore.get_storer
Returns the storer object for a key.
Examples
>>> df = pd.DataFrame([[1, 2], [3, 4]], columns=["A", "B"]) >>> store = pd.HDFStore("store.h5", "w") >>> store.put("data", df)