PR06 doc string fixes

pandas/core/computation/eval.py

@@ -198,14 +198,14 @@ def eval(
         <https://docs.python.org/3/reference/simple_stmts.html#simple-statements>`__,
         only Python `expressions
         <https://docs.python.org/3/reference/simple_stmts.html#expression-statements>`__.
-    parser : string, default 'pandas', {'pandas', 'python'}
+    parser : {'pandas', 'python'}, default 'pandas'
         The parser to use to construct the syntax tree from the expression. The
         default of ``'pandas'`` parses code slightly different than standard
         Python. Alternatively, you can parse an expression using the
         ``'python'`` parser to retain strict Python semantics.  See the
         :ref:`enhancing performance <enhancingperf.eval>` documentation for
         more details.
-    engine : string or None, default 'numexpr', {'python', 'numexpr'}
+    engine : {'python', 'numexpr'}, optional, default 'numexpr'
 
         The engine used to evaluate the expression. Supported engines are
 

pandas/core/frame.py

@@ -6238,7 +6238,7 @@ def unstack(self, level=-1, fill_value=None):
         ----------
         level : int, str, or list of these, default -1 (last level)
             Level(s) of index to unstack, can pass level name.
-        fill_value : int, string or dict
+        fill_value : int, str or dict
             Replace NaN with this value if the unstack produces missing values.
 
         Returns

pandas/core/generic.py

@@ -2353,7 +2353,7 @@ def to_json(
 
             .. versionadded:: 0.23.0
 
-        indent : integer, optional
+        indent : int, optional
            Length of whitespace used to indent each record.
 
            .. versionadded:: 1.0.0

pandas/core/groupby/generic.py

@@ -1644,7 +1644,7 @@ def nunique(self, dropna=True):
 
         Parameters
         ----------
-        dropna : boolean, default True
+        dropna : bool, default True
             Don't include NaN in the counts.
 
         Returns

pandas/core/indexes/base.py

@@ -4531,7 +4531,7 @@ def shift(self, periods=1, freq=None):
         periods : int, default 1
             Number of periods (or increments) to shift by,
             can be positive or negative.
-        freq : pandas.DateOffset, pandas.Timedelta or string, optional
+        freq : pandas.DateOffset, pandas.Timedelta or str, optional
             Frequency increment to shift by.
             If None, the index is shifted by its own `freq` attribute.
             Offset aliases are valid strings, e.g., 'D', 'W', 'M' etc.

pandas/core/indexes/category.py

@@ -77,7 +77,7 @@ class CategoricalIndex(Index, accessor.PandasDelegate):
         Whether or not this categorical is treated as an ordered
         categorical. If not given here or in `dtype`, the resulting
         categorical will be unordered.
-    dtype : CategoricalDtype or the string "category", optional
+    dtype : CategoricalDtype or "category", optional
         If :class:`CategoricalDtype`, cannot be used together with
         `categories` or `ordered`.
 

pandas/core/indexes/datetimes.py

@@ -1328,7 +1328,7 @@ def indexer_at_time(self, time, asof=False):
 
         Parameters
         ----------
-        time : datetime.time or string
+        time : datetime.time or str
             datetime.time or string in appropriate format ("%H:%M", "%H%M",
             "%I:%M%p", "%I%M%p", "%H:%M:%S", "%H%M%S", "%I:%M:%S%p",
             "%I%M%S%p").

pandas/core/indexes/interval.py

@@ -1412,11 +1412,11 @@ def interval_range(
         Right bound for generating intervals
     periods : int, default None
         Number of periods to generate
-    freq : numeric, string, or DateOffset, default None
+    freq : numeric, str, or DateOffset, default None
         The length of each interval. Must be consistent with the type of start
         and end, e.g. 2 for numeric, or '5H' for datetime-like.  Default is 1
         for numeric and 'D' for datetime-like.
-    name : string, default None
+    name : str, default None
         Name of the resulting IntervalIndex
     closed : {'left', 'right', 'both', 'neither'}, default 'right'
         Whether the intervals are closed on the left-side, right-side, both

pandas/core/indexes/multi.py

@@ -1650,7 +1650,7 @@ def to_frame(self, index=True, name=None):
 
         Parameters
         ----------
-        index : boolean, default True
+        index : bool, default True
             Set the index of the returned DataFrame as the original MultiIndex.
 
         name : list / sequence of strings, optional
@@ -2334,7 +2334,7 @@ def sortlevel(self, level=0, ascending=True, sort_remaining=True):
         level : list-like, int or str, default 0
             If a string is given, must be a name of the level
             If list-like must be names or ints of levels.
-        ascending : boolean, default True
+        ascending : bool, default True
             False to sort in descending order
             Can also be a list to specify a directed ordering
         sort_remaining : sort by the remaining levels after level

pandas/core/reshape/tile.py

@@ -285,10 +285,10 @@ def qcut(x, q, labels=None, retbins=False, precision=3, duplicates="raise"):
     Parameters
     ----------
     x : 1d ndarray or Series
-    q : integer or array of quantiles
+    q : int or array of quantiles
         Number of quantiles. 10 for deciles, 4 for quartiles, etc. Alternately
         array of quantiles, e.g. [0, .25, .5, .75, 1.] for quartiles
-    labels : array or boolean, default None
+    labels : array or bool, default None
         Used as labels for the resulting bins. Must be of the same length as
         the resulting bins. If False, return only integer indicators of the
         bins.

pandas/core/tools/numeric.py

@@ -39,7 +39,7 @@ def to_numeric(arg, errors="raise", downcast=None):
         - If 'raise', then invalid parsing will raise an exception
         - If 'coerce', then invalid parsing will be set as NaN
         - If 'ignore', then invalid parsing will return the input
-    downcast : {'integer', 'signed', 'unsigned', 'float'} , default None
+    downcast : {'integer', 'signed', 'unsigned', 'float'}, default None
         If not None, and if the data has been successfully cast to a
         numerical dtype (or if the data was numeric to begin with),
         downcast that resulting data to the smallest numerical dtype

pandas/io/json/_json.py

@@ -384,7 +384,7 @@ def read_json(
         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``.
-    orient : string,
+    orient : str,
         Indication of expected JSON string format.
         Compatible JSON strings can be produced by ``to_json()`` with a
         corresponding orient value.

pandas/io/parsers.py

@@ -257,7 +257,7 @@
     arguments.
 dayfirst : bool, default False
     DD/MM format dates, international and European format.
-cache_dates : boolean, default True
+cache_dates : bool, default True
     If True, use a cache of unique, converted dates to apply the datetime
     conversion. May produce significant speed-up when parsing duplicate
     date strings, especially ones with timezone offsets.

pandas/io/pytables.py

@@ -1025,8 +1025,8 @@ def append(
                        Write as a PyTables Table structure which may perform
                        worse but allow more flexible operations like searching
                        / selecting subsets of the data
-        append       : boolean, default True, append the input data to the
-            existing
+        append       : bool, default True,
+            append the input data to the existing
         data_columns :  list of columns, or True, default None
             List of columns to create as indexed data columns for on-disk
             queries, or True to use all columns. By default only the axes
@@ -1037,8 +1037,9 @@ def append(
         chunksize    : size to chunk the writing
         expectedrows : expected TOTAL row size of this table
         encoding     : default None, provide an encoding for strings
-        dropna       : boolean, default False, do not write an ALL nan row to
-            the store settable by the option 'io.hdf.dropna_table'
+        dropna       : bool, default False,
+            do not write an ALL nan row to the store settable
+            by the option 'io.hdf.dropna_table'
 
         Notes
         -----

pandas/io/sql.py

@@ -287,7 +287,7 @@ def read_sql_query(
         If a DBAPI2 object, only sqlite3 is supported.
     index_col : string or list of strings, optional, default: None
         Column(s) to set as index(MultiIndex).
-    coerce_float : boolean, default True
+    coerce_float : bool, default True
         Attempts to convert values of non-string, non-numeric objects (like
         decimal.Decimal) to floating point. Useful for SQL result sets.
     params : list, tuple or dict, optional, default: None

pandas/io/stata.py

@@ -53,31 +53,31 @@
 )
 
 _statafile_processing_params1 = """\
-convert_dates : boolean, defaults to True
+convert_dates : bool, default True
     Convert date variables to DataFrame time values.
-convert_categoricals : boolean, defaults to True
+convert_categoricals : bool, default True
     Read value labels and convert columns to Categorical/Factor variables."""
 
 _encoding_params = """\
-encoding : string, None or encoding
+encoding : str, None or encoding
     Encoding used to parse the files. None defaults to latin-1."""
 
 _statafile_processing_params2 = """\
-index_col : string, optional, default: None
+index_col : str, optional
     Column to set as index.
-convert_missing : boolean, defaults to False
+convert_missing : bool, default 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_dtypes : bool, default 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
+order_categoricals : bool, default True
     Flag indicating whether converted categorical data are ordered."""
 
 _chunksize_params = """\
@@ -86,7 +86,7 @@
     given number of lines."""
 
 _iterator_params = """\
-iterator : boolean, default False
+iterator : bool, default False
     Return StataReader object."""
 
 _read_stata_doc = """

pandas/tseries/frequencies.py

@@ -223,7 +223,7 @@ def infer_freq(index, warn=True):
     ----------
     index : DatetimeIndex or TimedeltaIndex
       if passed a Series will use the values of the series (NOT THE INDEX)
-    warn : boolean, default True
+    warn : bool, default True
 
     Returns
     -------