@@ -1326,9 +1326,10 @@ def _from_arrays(cls, arrays, columns, index, dtype=None):
13261326 def from_csv (cls , path , header = 0 , sep = ',' , index_col = 0 , parse_dates = True ,
13271327 encoding = None , tupleize_cols = None ,
13281328 infer_datetime_format = False ):
1329- """
1330- Read CSV file (DEPRECATED, please use :func:`pandas.read_csv`
1331- instead).
1329+ """Read CSV file.
1330+
1331+ .. deprecated:: 0.21.0
1332+ Use :func:`pandas.read_csv` instead.
13321333
13331334 It is preferable to use the more powerful :func:`pandas.read_csv`
13341335 for most general purposes, but ``from_csv`` makes for an easy
@@ -1979,12 +1980,10 @@ def _unpickle_matrix_compat(self, state): # pragma: no cover
19791980 # Getting and setting elements
19801981
19811982 def get_value (self , index , col , takeable = False ):
1982- """
1983- Quickly retrieve single value at passed column and index
1983+ """Quickly retrieve single value at passed column and index
19841984
19851985 .. deprecated:: 0.21.0
1986-
1987- Please use .at[] or .iat[] accessors.
1986+ Use .at[] or .iat[] accessors instead.
19881987
19891988 Parameters
19901989 ----------
@@ -2024,12 +2023,10 @@ def _get_value(self, index, col, takeable=False):
20242023 _get_value .__doc__ = get_value .__doc__
20252024
20262025 def set_value (self , index , col , value , takeable = False ):
2027- """
2028- Put single value at passed column and index
2026+ """Put single value at passed column and index
20292027
20302028 .. deprecated:: 0.21.0
2031-
2032- Please use .at[] or .iat[] accessors.
2029+ Use .at[] or .iat[] accessors instead.
20332030
20342031 Parameters
20352032 ----------
@@ -3737,12 +3734,13 @@ def sort_index(self, axis=0, level=None, ascending=True, inplace=False,
37373734
37383735 def sortlevel (self , level = 0 , axis = 0 , ascending = True , inplace = False ,
37393736 sort_remaining = True ):
3740- """
3741- DEPRECATED: use :meth:`DataFrame.sort_index`
3742-
3743- Sort multilevel index by chosen axis and primary level. Data will be
3737+ """Sort multilevel index by chosen axis and primary level. Data will be
37443738 lexicographically sorted by the chosen level followed by the other
3745- levels (in order)
3739+ levels (in order).
3740+
3741+ .. deprecated:: 0.20.0
3742+ Use :meth:`DataFrame.sort_index`
3743+
37463744
37473745 Parameters
37483746 ----------
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