Write the contained data to an HDF5 file using HDFStore.
Hierarchical Data Format (HDF) is self-describing, allowing an application to interpret the structure and contents of a file with no outside information. One HDF file can hold a mix of related objects which can be accessed as a group or as individual objects.
In order to add another DataFrame or Series to an existing HDF file please use append mode and a different a key.
For more information see the user guide.
| Parameters: |
-
path_or_buf : str or pandas.HDFStore -
File path or HDFStore object. -
key : str -
Identifier for the group in the store. -
mode : {‘a’, ‘w’, ‘r+’}, default ‘a’ -
Mode to open file: - ‘w’: write, a new file is created (an existing file with the same name would be deleted).
- ‘a’: append, an existing file is opened for reading and writing, and if the file does not exist it is created.
- ‘r+’: similar to ‘a’, but the file must already exist.
-
format : {‘fixed’, ‘table’}, default ‘fixed’ -
Possible values: - ‘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.
-
append : bool, default False -
For Table formats, append the input data to the existing. -
data_columns : list of columns or True, optional -
List of columns to create as indexed data columns for on-disk queries, or True to use all columns. By default only the axes of the object are indexed. See Query via data columns. Applicable only to format=’table’. -
complevel : {0-9}, optional -
Specifies a compression level for data. A value of 0 disables compression. -
complib : {‘zlib’, ‘lzo’, ‘bzip2’, ‘blosc’}, default ‘zlib’ -
Specifies the compression library to be used. As of v0.20.2 these additional compressors for Blosc are supported (default if no compressor specified: ‘blosc:blosclz’): {‘blosc:blosclz’, ‘blosc:lz4’, ‘blosc:lz4hc’, ‘blosc:snappy’, ‘blosc:zlib’, ‘blosc:zstd’}. Specifying a compression library which is not available issues a ValueError. -
fletcher32 : bool, default False -
If applying compression use the fletcher32 checksum. -
dropna : bool, default False -
If true, ALL nan rows will not be written to store. -
errors : str, default ‘strict’ -
Specifies how encoding and decoding errors are to be handled. See the errors argument for open() for a full list of options. |
Examples
>>> df = pd.DataFrame({'A': [1, 2, 3], 'B': [4, 5, 6]},
... index=['a', 'b', 'c'])
>>> df.to_hdf('data.h5', key='df', mode='w')
We can add another object to the same file:
>>> s = pd.Series([1, 2, 3, 4])
>>> s.to_hdf('data.h5', key='s')
Reading from HDF file:
>>> pd.read_hdf('data.h5', 'df')
A B
a 1 4
b 2 5
c 3 6
>>> pd.read_hdf('data.h5', 's')
0 1
1 2
2 3
3 4
dtype: int64
Deleting file with data:
>>> import os
>>> os.remove('data.h5')