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read_csv and zip files

2016-02-06

read_csv is no longer able to extract a dataframe from a zip file. The parameter format changed for compression but the zip format disappeared from the list. I assume the reason is that zip files can contains many files.

pyquickhelper now implements the function read_csv which can extract all dataframe in a zip file or falls back into the regular function if no zip format is detected. In that case, it returns a dictionary of dataframes indexed by their name in the zip file.

from pyquickhelper.pandashelper import read_csv
dfs = read_csv("url_or_filename.zip", compression="zip")
print(dfs["dataframe.txt"].head())

If only one file must be converted as a dataframe, the parameter fvalid must be used:

from pyquickhelper.pandashelper import read_csv
dfs = read_csv("url_or_filename.zip", compression="zip",
               fvalid=lambda name: name == "the_file.txt")
print(dfs["the_file.txt"].head())

The others files will be loaded as text. In more details, when it is a zip file, the function reads a dataframe from a zip file by doing:

import io, zipfile, pandas

def read_zip(local_file, encoding="utf8"):

    with open(local_file, "rb") as local_file:
        content = local_file.read()

    dfs = {}
    with zipfile.ZipFile(io.BytesIO(content)) as myzip:
        infos = myzip.infolist()

        for info in infos:
            name = info.filename
            with myzip.open(name, "r") as f:
                text = f.read()

            text = text.decode(encoding="utf8")
            st = io.StringIO(text)
            df = pandas.read_csv(st, compression=compression, **params)
            dfs[name] = df

    return dfs

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