ENH: Fix for #1512, added StataReader and StataWriter to pandas.io.parsers

RELEASE.rst

@@ -33,6 +33,7 @@ pandas 0.11.1
   - pd.read_html() can now parse HTML string, files or urls and return dataframes
     courtesy of @cpcloud. (GH3477_)
   - Support for reading Amazon S3 files. (GH3504_)
+  - Added module for reading and writing Stata files: pandas.io.stata (GH1512_)
 
 **Improvements to existing features**
 
@@ -166,6 +167,7 @@ pandas 0.11.1
 .. _GH3610: https://github.com/pydata/pandas/issues/3610
 .. _GH3596: https://github.com/pydata/pandas/issues/3596
 .. _GH3435: https://github.com/pydata/pandas/issues/3435
+.. _GH1512: https://github.com/pydata/pandas/issues/1512
 
 
 pandas 0.11.0

doc/source/io.rst

@@ -1829,3 +1829,44 @@ There are a few other available functions:
 
    For now, writing your DataFrame into a database works only with
    **SQLite**. Moreover, the **index** will currently be **dropped**.
+
+
+Reading from STATA format
+~~~~~~~~~~~~~~~~~~~~~~
+
+.. _io.StataReader:
+
+.. versionadded:: 0.11.1
+
+The class StataReader will read the header of the given dta file at 
+initialization. Its function :func:'~pandas.io.StataReader.data' will 
+read the observations, converting them to a DataFrame which is returned:
+
+.. ipython:: python
+   reader = StataReader(dta_filepath)
+   dataframe = reader.data()
+
+The parameter convert_categoricals indicates wheter value labels should be 
+read and used to create a Categorical variable from them. Value labels can 
+also be retrieved by the function variable_labels, which requires data to be 
+called before.
+The StataReader supports .dta Formats 104, 105, 108, 113-115.
+
+Alternatively, the function :func:'~pandas.io.read_stata' can be used:
+
+.. ipython:: python
+   dataframe = read_stata(dta_filepath)
+
+
+Writing to STATA format
+~~~~~~~~~~~~~~~~~~~~~~
+
+.. _io.StataWriter:
+
+The function :func:'~pandas.io.StataWriter.write_file' will write a DataFrame 
+into a .dta file. The format version of this file is always the latest one, 
+115.
+
+.. ipython:: python
+   writer = StataWriter(filename, dataframe)
+   writer.write_file()

doc/source/v0.11.1.txt

@@ -54,6 +54,7 @@ Enhancements
     - support datelike columns with a timezone as data_columns (GH2852_)
   - ``fillna`` methods now raise a ``TypeError`` if the ``value`` parameter is
     a list or tuple.
+  - Added module for reading and writing Stata files: pandas.io.stata (GH1512_)
 
 See the `full release notes
 <https://github.com/pydata/pandas/blob/master/RELEASE.rst>`__ or issue tracker
@@ -68,3 +69,4 @@ on GitHub for a complete list.
 .. _GH3596: https://github.com/pydata/pandas/issues/3596
 .. _GH3590: https://github.com/pydata/pandas/issues/3590
 .. _GH3435: https://github.com/pydata/pandas/issues/3435
+.. _GH1512: https://github.com/pydata/pandas/issues/1512

pandas/core/frame.py

@@ -1280,6 +1280,35 @@ def from_csv(cls, path, header=0, sep=',', index_col=0,
                           parse_dates=parse_dates, index_col=index_col,
                           encoding=encoding)
 
+    @classmethod
+    def from_dta(dta, path, parse_dates=True, convert_categoricals=True, encoding=None, index_col=None):
+        """
+        Read Stata file into DataFrame
+
+        Parameters
+        ----------
+        path : string file path or file handle / StringIO
+        parse_dates : boolean, default True
+            Convert date variables to DataFrame time values
+        convert_categoricals : boolean, default True
+            Read value labels and convert columns to Categorical/Factor variables
+        encoding : string, None or encoding, default None
+            Encoding used to parse the files. Note that Stata doesn't
+            support unicode. None defaults to cp1252.
+        index_col : int or sequence, default None
+            Column to use for index. If a sequence is given, a MultiIndex
+            is used. Different default from read_table
+
+        Notes
+        -----
+
+        Returns
+        -------
+        y : DataFrame
+        """
+        from pandas.io.stata import read_stata
+        return read_stata(path, parse_dates=parse_dates, convert_categoricals=convert_categoricals, encoding=encoding, index=index_col)
+
     def to_sparse(self, fill_value=None, kind='block'):
         """
         Convert to SparseDataFrame