Source code for pyquickhelper.pandashelper.readh

# -*- coding:utf-8 -*-
Various ways to import data into a dataframe

import zipfile
from io import StringIO, BytesIO
from ..filehelper import read_content_ufs

[docs]def read_csv(filepath_or_buffer, compression=None, fvalid=None, **params): """ Reads a file from a file, it adds the compression zip which was removed in the latest version, see :epkg:`pandas:read_csv`. :param filepath_or_buffer: filepath or buffer :param compression: see :epkg:`pandas:read_csv` :param params: see :epkg:`pandas:read_csv` :param fvalid: if the zip file contains many files, this function validates which one must be returned based on its name, the function returns the content of the file in that case (bytes) :return: dataframe or a dictionary (name, dataframe) See blog post :ref:`blogpost_read_csv`. :githublink:`%|py|26` """ import pandas if isinstance(filepath_or_buffer, str) and \ (compression == "zip" or (compression is None and filepath_or_buffer.endswith(".zip"))): content = read_content_ufs(filepath_or_buffer, asbytes=True) with zipfile.ZipFile(BytesIO(content)) as myzip: infos = myzip.infolist() if not infos: raise FileNotFoundError( "unable to find a file in " + filepath_or_buffer) res = {} for info in infos: name = info.filename with, "r") as f: text = if fvalid is not None and not fvalid(name): res[name] = text else: if text is None: raise FileNotFoundError( "empty file {0} in {1}".format(name, filepath_or_buffer)) text = text.decode( encoding=params.get('encoding', 'ascii')) st = StringIO(text) try: df = pandas.read_csv( st, compression=compression, **params) except pandas.errors.ParserError as e: lines = text.split("\n") end = min(len(lines), 5) mes = "Parsing errors in {0}, first lines:\n{1}".format( name, "\n".join(lines[:end])) raise Exception(mes) from e res[name] = df return res if len(res) > 1 else list(res.values())[0] else: return pandas.read_csv(filepath_or_buffer, compression=compression, **params)