Pandas Series: to_hdf() function
Series-to_hdf() function
The to_hdf() function is used to 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.
Syntax:
Series.to_hdf(self, path_or_buf, key, **kwargs)
Parameters:
Name | Description | Type/Default Value | Required / Optional |
---|---|---|---|
path_or_buf | File path or HDFStore object. | str or pandas.HDFStore | Required |
key | Identifier for the group in the store. | str | Required |
mode | Mode to open file:
|
{'a', 'w', 'r+'}, default 'a' | Required |
format | Possible values:
|
{‘fixed’, ‘table’}, default ‘fixed’ | Required |
append | For Table formats, append the input data to the existing. | bool, default False | Required |
data_columns | 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'. | list of columns or True | Optional |
complevel | Specifies a compression level for data. A value of 0 disables compression. | {0-9} | Optional/td> |
complib | 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. | {'zlib', 'lzo', 'bzip2', 'blosc'}, default ‘zlib’ | Required |
fletcher32 | If applying compression use the fletcher32 checksum. | bool, default False | Required |
dropna | If true, ALL nan rows will not be written to store. | bool, default False | Required |
errors | Specifies how encoding and decoding errors are to be handled. See the errors argument for open() for a full list of options. | str, default ‘strict’ | Required |
Example - We can add another object to the same file:
Reading from HDF file:
Python-Pandas Code:
import numpy as np
import pandas as pd
df = pd.DataFrame({'X': [2, 3, 4], 'Y': [5, 6, 7]},
index=['p', 'q', 'r'])
df.to_hdf('data.h5', key='df', mode='w')
s = pd.Series([2, 3, 4, 5])
s.to_hdf('data.h5', key='s')
pd.read_hdf('data.h5', 'df')
Output:
X Y p 2 5 q 3 6 r 4 7
Python-Pandas Code:
import numpy as np
import pandas as pd
df = pd.DataFrame({'X': [2, 3, 4], 'Y': [5, 6, 7]},
index=['p', 'q', 'r'])
df.to_hdf('data.h5', key='df', mode='w')
s = pd.Series([2, 3, 4, 5])
s.to_hdf('data.h5', key='s')
pd.read_hdf('data.h5', 's')
Output:
0 2 1 3 2 4 3 5 dtype: int64
Example - Deleting file with data:
Python-Pandas Code:
import os
os.remove('data.h5')
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