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a guest Aug 21st, 2019 57 Never
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  1. pd.read_csv(
  2.     "data.csv.gz",
  3.     delimiter = "^",
  4.     # line numbers to skip (i.e. headers in an excel report)
  5.     skiprows = 2,
  6.     # used to denote the start and end of a quoted item
  7.     quotechar = "|",
  8.     # return a subset of columns
  9.     usecols = ["return_date", "company", "sales"],
  10.     # data type for data or columns
  11.     dtype = { "sales": np.float64 },
  12.     # additional strings to recognize as NA/NaN
  13.     na_values = [".", "?"],
  14.     # convert to datetime, instead of object
  15.     parse_dates = ["return_date"],
  16.     # for on-the-fly decompression of on-disk data
  17.     # options - gzip, bz2, zip, xz
  18.     compression = "gzip",
  19.     # encoding to use for reading
  20.     encoding = "latin1",
  21.     # read in a subset of data
  22.     nrows = 100
  23. )
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