pandas_streaming.df.dataframe_io¶
- pandas_streaming.df.dataframe_io.read_zip(zipfilename, zname=None, **kwargs)[source][source]¶
Reads a dataframe from a zip file. It can be saved by
to_zip()
.- Parameters:
zipfilename – a
zipfile.ZipFile
or a filenamezname – a filename in zipfile, if None, takes the first one
kwargs – parameters for
pandas.read_csv()
- Returns:
- pandas_streaming.df.dataframe_io.to_zip(df, zipfilename, zname='df.csv', **kwargs)[source][source]¶
Saves a Dataframe into a zip file. It can be read by
read_zip()
.- Parameters:
df – dataframe or
numpy.ndarray
zipfilename – a
zipfile.ZipFile
or a filenamezname – a filename in the zipfile
kwargs – parameters for
pandas.DataFrame.to_csv()
ornumpy.save()
- Returns:
zipfilename
Saves and reads a dataframe in a zip file
This shows an example on how to save and read a
pandas.DataFrame
directly into a zip file.<<<
import pandas from pandas_streaming.df import to_zip, read_zip df = pandas.DataFrame([dict(a=1, b="e"), dict(b="f", a=5.7)]) name = "dfs.zip" to_zip(df, name, encoding="utf-8", index=False) df2 = read_zip(name, encoding="utf-8") print(df2)
>>>
a b 0 1.0 e 1 5.7 f
Saves and reads a numpy array in a zip file
This shows an example on how to save and read a
numpy.ndarray
directly into a zip file.<<<
import numpy from pandas_streaming.df import to_zip, read_zip arr = numpy.array([[0.5, 1.5], [0.4, 1.6]]) name = "dfsa.zip" to_zip(arr, name, "arr.npy") arr2 = read_zip(name, "arr.npy") print(arr2)
>>>
[[0.5 1.5] [0.4 1.6]]