pandas.Panel.to_hdf¶
-
Panel.
to_hdf
(path_or_buf, key, **kwargs)[source]¶ 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.See also
DataFrame.read_hdf
- Read from HDF file.
DataFrame.to_parquet
- Write a DataFrame to the binary parquet format.
DataFrame.to_sql
- Write to a sql table.
DataFrame.to_feather
- Write out feather-format for DataFrames.
DataFrame.to_csv
- Write out to a csv file.
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')