DEPR: Warn about Series.to_csv signature alignment

Warns about aligning Series.to_csv's signature
with that of DataFrame.to_csv's.

In anticipation, we have moved DataFrame.to_csv
to generic.py so that we can later delete the
Series.to_csv implementation, and allow it
to automatically adopt DataFrame's to_csv
due to inheritance.

Closes pandas-devgh-19745.

Author: gfyoung

doc/source/whatsnew/v0.24.0.txt

@@ -245,7 +245,7 @@ Deprecations
 - :meth:`DataFrame.to_stata`, :meth:`read_stata`, :class:`StataReader` and :class:`StataWriter` have deprecated the ``encoding`` argument.  The encoding of a Stata dta file is determined by the file type and cannot be changed (:issue:`21244`).
 - :meth:`MultiIndex.to_hierarchical` is deprecated and will be removed in a future version  (:issue:`21613`)
 - :meth:`Series.ptp` is deprecated. Use ``numpy.ptp`` instead (:issue:`21614`)
--
+- The signature in :meth:`Series.to_csv` has been deprecated. Please follow the signature in :meth:`DataFrame.to_csv` instead (:issue:`19745`)
 
 .. _whatsnew_0240.prior_deprecations:
 

pandas/core/frame.py

@@ -1710,103 +1710,6 @@ def to_panel(self):
 
         return self._constructor_expanddim(new_mgr)
 
-    def to_csv(self, path_or_buf=None, sep=",", na_rep='', float_format=None,
-               columns=None, header=True, index=True, index_label=None,
-               mode='w', encoding=None, compression=None, quoting=None,
-               quotechar='"', line_terminator='\n', chunksize=None,
-               tupleize_cols=None, date_format=None, doublequote=True,
-               escapechar=None, decimal='.'):
-        r"""Write DataFrame to a comma-separated values (csv) file
-
-        Parameters
-        ----------
-        path_or_buf : string or file handle, default None
-            File path or object, if None is provided the result is returned as
-            a string.
-        sep : character, default ','
-            Field delimiter for the output file.
-        na_rep : string, default ''
-            Missing data representation
-        float_format : string, default None
-            Format string for floating point numbers
-        columns : sequence, optional
-            Columns to write
-        header : boolean or list of string, default True
-            Write out the column names. If a list of strings is given it is
-            assumed to be aliases for the column names
-        index : boolean, default True
-            Write row names (index)
-        index_label : string or sequence, or False, default None
-            Column label for index column(s) if desired. If None is given, and
-            `header` and `index` are True, then the index names are used. A
-            sequence should be given if the DataFrame uses MultiIndex.  If
-            False do not print fields for index names. Use index_label=False
-            for easier importing in R
-        mode : str
-            Python write mode, default 'w'
-        encoding : string, optional
-            A string representing the encoding to use in the output file,
-            defaults to 'ascii' on Python 2 and 'utf-8' on Python 3.
-        compression : {'infer', 'gzip', 'bz2', 'xz', None}, default None
-            If 'infer' and `path_or_buf` is path-like, then detect compression
-            from the following extensions: '.gz', '.bz2' or '.xz'
-            (otherwise no compression).
-        line_terminator : string, default ``'\n'``
-            The newline character or character sequence to use in the output
-            file
-        quoting : optional constant from csv module
-            defaults to csv.QUOTE_MINIMAL. If you have set a `float_format`
-            then floats are converted to strings and thus csv.QUOTE_NONNUMERIC
-            will treat them as non-numeric
-        quotechar : string (length 1), default '\"'
-            character used to quote fields
-        doublequote : boolean, default True
-            Control quoting of `quotechar` inside a field
-        escapechar : string (length 1), default None
-            character used to escape `sep` and `quotechar` when appropriate
-        chunksize : int or None
-            rows to write at a time
-        tupleize_cols : boolean, default False
-            .. deprecated:: 0.21.0
-               This argument will be removed and will always write each row
-               of the multi-index as a separate row in the CSV file.
-
-            Write MultiIndex columns as a list of tuples (if True) or in
-            the new, expanded format, where each MultiIndex column is a row
-            in the CSV (if False).
-        date_format : string, default None
-            Format string for datetime objects
-        decimal: string, default '.'
-            Character recognized as decimal separator. E.g. use ',' for
-            European data
-
-        """
-
-        if tupleize_cols is not None:
-            warnings.warn("The 'tupleize_cols' parameter is deprecated and "
-                          "will be removed in a future version",
-                          FutureWarning, stacklevel=2)
-        else:
-            tupleize_cols = False
-
-        from pandas.io.formats.csvs import CSVFormatter
-        formatter = CSVFormatter(self, path_or_buf,
-                                 line_terminator=line_terminator, sep=sep,
-                                 encoding=encoding,
-                                 compression=compression, quoting=quoting,
-                                 na_rep=na_rep, float_format=float_format,
-                                 cols=columns, header=header, index=index,
-                                 index_label=index_label, mode=mode,
-                                 chunksize=chunksize, quotechar=quotechar,
-                                 tupleize_cols=tupleize_cols,
-                                 date_format=date_format,
-                                 doublequote=doublequote,
-                                 escapechar=escapechar, decimal=decimal)
-        formatter.save()
-
-        if path_or_buf is None:
-            return formatter.path_or_buf.getvalue()
-
     @Appender(_shared_docs['to_excel'] % _shared_doc_kwargs)
     def to_excel(self, excel_writer, sheet_name='Sheet1', na_rep='',
                  float_format=None, columns=None, header=True, index=True,

pandas/core/generic.py

@@ -9161,6 +9161,107 @@ def first_valid_index(self):
     def last_valid_index(self):
         return self._find_valid_index('last')
 
+    def to_csv(self, path_or_buf=None, sep=",", na_rep='', float_format=None,
+               columns=None, header=True, index=True, index_label=None,
+               mode='w', encoding=None, compression=None, quoting=None,
+               quotechar='"', line_terminator='\n', chunksize=None,
+               tupleize_cols=None, date_format=None, doublequote=True,
+               escapechar=None, decimal='.'):
+        r"""Export to a comma-separated values (CSV) file
+
+        Parameters
+        ----------
+        path_or_buf : string or file handle, default None
+            File path or object, if None is provided the result is returned as
+            a string.
+        sep : character, default ','
+            Field delimiter for the output file.
+        na_rep : string, default ''
+            Missing data representation
+        float_format : string, default None
+            Format string for floating point numbers
+        columns : sequence, optional
+            Columns to write
+        header : boolean or list of string, default True
+            Write out the column names. If a list of strings is given it is
+            assumed to be aliases for the column names
+        index : boolean, default True
+            Write row names (index)
+        index_label : string or sequence, or False, default None
+            Column label for index column(s) if desired. If None is given, and
+            `header` and `index` are True, then the index names are used. A
+            sequence should be given if the DataFrame uses MultiIndex.  If
+            False do not print fields for index names. Use index_label=False
+            for easier importing in R
+        mode : str
+            Python write mode, default 'w'
+        encoding : string, optional
+            A string representing the encoding to use in the output file,
+            defaults to 'ascii' on Python 2 and 'utf-8' on Python 3.
+        compression : {'infer', 'gzip', 'bz2', 'xz', None}, default None
+            If 'infer' and `path_or_buf` is path-like, then detect compression
+            from the following extensions: '.gz', '.bz2' or '.xz'
+            (otherwise no compression).
+        line_terminator : string, default ``'\n'``
+            The newline character or character sequence to use in the output
+            file
+        quoting : optional constant from csv module
+            defaults to csv.QUOTE_MINIMAL. If you have set a `float_format`
+            then floats are converted to strings and thus csv.QUOTE_NONNUMERIC
+            will treat them as non-numeric
+        quotechar : string (length 1), default '\"'
+            character used to quote fields
+        doublequote : boolean, default True
+            Control quoting of `quotechar` inside a field
+        escapechar : string (length 1), default None
+            character used to escape `sep` and `quotechar` when appropriate
+        chunksize : int or None
+            rows to write at a time
+        tupleize_cols : boolean, default False
+            .. deprecated:: 0.21.0
+               This argument will be removed and will always write each row
+               of the multi-index as a separate row in the CSV file.
+
+            Write MultiIndex columns as a list of tuples (if True) or in
+            the new, expanded format, where each MultiIndex column is a row
+            in the CSV (if False).
+        date_format : string, default None
+            Format string for datetime objects
+        decimal: string, default '.'
+            Character recognized as decimal separator. E.g. use ',' for
+            European data
+
+        """
+
+        from pandas.core.frame import DataFrame
+        from pandas.io.formats.csvs import CSVFormatter
+
+        df = self if isinstance(self, DataFrame) else DataFrame(self)
+
+        if tupleize_cols is not None:
+            warnings.warn("The 'tupleize_cols' parameter is deprecated and "
+                          "will be removed in a future version",
+                          FutureWarning, stacklevel=2)
+        else:
+            tupleize_cols = False
+
+        formatter = CSVFormatter(df, path_or_buf,
+                                 line_terminator=line_terminator, sep=sep,
+                                 encoding=encoding,
+                                 compression=compression, quoting=quoting,
+                                 na_rep=na_rep, float_format=float_format,
+                                 cols=columns, header=header, index=index,
+                                 index_label=index_label, mode=mode,
+                                 chunksize=chunksize, quotechar=quotechar,
+                                 tupleize_cols=tupleize_cols,
+                                 date_format=date_format,
+                                 doublequote=doublequote,
+                                 escapechar=escapechar, decimal=decimal)
+        formatter.save()
+
+        if path_or_buf is None:
+            return formatter.path_or_buf.getvalue()
+
 
 def _doc_parms(cls):
     """Return a tuple of the doc parms."""

pandas/core/series.py

@@ -3760,24 +3760,30 @@ def from_csv(cls, path, sep=',', parse_dates=True, header=None,
 
         return result
 
-    def to_csv(self, path=None, index=True, sep=",", na_rep='',
-               float_format=None, header=False, index_label=None,
+    def to_csv(self, path_or_buf=None, index=True, sep=",", na_rep='',
+               float_format=None, header=None, index_label=None,
                mode='w', encoding=None, compression=None, date_format=None,
-               decimal='.'):
-        """
-        Write Series to a comma-separated values (csv) file
+               decimal='.', **kwargs):
+        """Export to a comma-separated values (CSV) file
+
+        .. deprecated:: 0.24.0
+            The signature will aligned to that of :func:`DataFrame.to_csv`.
+
+        :func:`Series.to_csv` will align its signature with that of
+        `DataFrame.to_csv`. Please pass in keyword arguments in accordance
+        with that signature instead.
 
         Parameters
         ----------
-        path : string or file handle, default None
+        path_or_buf : string or file handle, default None
             File path or object, if None is provided the result is returned as
             a string.
         na_rep : string, default ''
             Missing data representation
         float_format : string, default None
             Format string for floating point numbers
-        header : boolean, default False
-            Write out series name
+        header : boolean, default None
+            Write out Series name. By default, the name will be omitted.
         index : boolean, default True
             Write row names (index)
         index_label : string or sequence, default None
@@ -3800,15 +3806,47 @@ def to_csv(self, path=None, index=True, sep=",", na_rep='',
             Character recognized as decimal separator. E.g. use ',' for
             European data
         """
+
         from pandas.core.frame import DataFrame
         df = DataFrame(self)
-        # result is only a string if no path provided, otherwise None
-        result = df.to_csv(path, index=index, sep=sep, na_rep=na_rep,
-                           float_format=float_format, header=header,
-                           index_label=index_label, mode=mode,
-                           encoding=encoding, compression=compression,
-                           date_format=date_format, decimal=decimal)
-        if path is None:
+
+        new_path_key = "path_or_buf"
+        old_path_key = "path"
+        emit_warning = False
+
+        # For backwards compatibility, override the `path_of_buf`
+        # argument if a `path` keyword argument is provided.
+        if kwargs.get(old_path_key, None) is not None:
+            kwargs[new_path_key] = kwargs.pop(old_path_key)
+            emit_warning = True
+
+        if header is None:
+            emit_warning = True
+            header = False
+
+        if emit_warning:
+            warnings.warn("The signature of `Series.to_csv` will be "
+                          "aligned to that of `DataFrame.to_csv` in the "
+                          "future. Note that some of the default arguments "
+                          "and argument names are different, so please refer "
+                          "to the documentation for `DataFrame.to_csv` when "
+                          "changing your function calls.",
+                          FutureWarning, stacklevel=2)
+            header = False
+
+        to_csv_kwargs = dict(path_or_buf=path_or_buf, index=index, sep=sep,
+                             na_rep=na_rep, float_format=float_format,
+                             header=header, index_label=index_label,
+                             mode=mode, encoding=encoding,
+                             compression=compression,
+                             date_format=date_format,
+                             decimal=decimal)
+        to_csv_kwargs.update(**kwargs)
+
+        # Result is only a string if no path provided, otherwise None.
+        result = df.to_csv(**to_csv_kwargs)
+
+        if to_csv_kwargs[new_path_key] is None:
             return result
 
     @Appender(generic._shared_docs['to_excel'] % _shared_doc_kwargs)

pandas/tests/frame/test_to_csv.py

@@ -893,14 +893,16 @@ def test_to_csv_line_terminators(self):
 
     def test_to_csv_from_csv_categorical(self):
 
-        # CSV with categoricals should result in the same output as when one
-        # would add a "normal" Series/DataFrame.
+        # CSV with Categoricals should result in the same output
+        # as when one would add a "normal" Series/DataFrame.
         s = Series(pd.Categorical(['a', 'b', 'b', 'a', 'a', 'c', 'c', 'c']))
         s2 = Series(['a', 'b', 'b', 'a', 'a', 'c', 'c', 'c'])
         res = StringIO()
-        s.to_csv(res)
+
+        s.to_csv(res, header=False)
         exp = StringIO()
-        s2.to_csv(exp)
+
+        s2.to_csv(exp, header=False)
         assert res.getvalue() == exp.getvalue()
 
         df = DataFrame({"s": s})