# pandas.read_stata

`pandas.``read_stata`(filepath_or_buffer, convert_dates=True, convert_categoricals=True, encoding=None, index_col=None, convert_missing=False, preserve_dtypes=True, columns=None, order_categoricals=True, chunksize=None, iterator=False)

  Read Stata file into DataFrame.

  Parameters:

  filepath_or_buffer : str, path object or file-like object

  > Any valid string path is acceptable. The string could be a URL. Valid URL schemes include http, ftp, s3, and file. For file URLs, a host is expected. A local file could be: `file://localhost/path/to/table.dta`.

  > If you want to pass in a path object, pandas accepts any `os.PathLike`.

  > By file-like object, we refer to objects with a `read()` method, such as a file handler (e.g. via builtin `open` function) or `StringIO`.

  convert_dates : boolean, defaults to True

  > Convert date variables to DataFrame time values.

  convert_categoricals : boolean, defaults to True

  > Read value labels and convert columns to Categorical/Factor variables.

  encoding : string, None or encoding

  > Encoding used to parse the files. None defaults to latin-1.

  index_col : string, optional, default: None

  > Column to set as index.

  convert_missing : boolean, defaults to False

  > Flag indicating whether to convert missing values to their Stata representations. If False, missing values are replaced with nan. If True, columns containing missing values are returned with object data types and missing values are represented by StataMissingValue objects.

  preserve_dtypes : boolean, defaults to True

  > Preserve Stata datatypes. If False, numeric data are upcast to pandas default types for foreign data (float64 or int64).

  columns : list or None

  > Columns to retain. Columns will be returned in the given order. None returns all columns.

  order_categoricals : boolean, defaults to True

  > Flag indicating whether converted categorical data are ordered.

  chunksize : int, default None

  > Return StataReader object for iterations, returns chunks with given number of lines.

  iterator : boolean, default False

  > Return StataReader object.

  Returns: | DataFrame or StataReader

  See also

  `io.stata.StataReader`
    Low-level reader for Stata data files.
  `DataFrame.to_stata`
    Export Stata data files.

  Examples

  Read a Stata dta file:

      >>> df = pd.read_stata('filename.dta')

  Read a Stata dta file in 10,000 line chunks:

      >>> itr = pd.read_stata('filename.dta', chunksize=10000)
      >>> for chunk in itr:
      ...     do_something(chunk)

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