DOC: Updated to mention axis='index' and axis='columns

Updated docs throughout DataFrame methods to mention
that axis can be set to 'index' or 'column' instead of 0 or 1
which improves readability significantly.

Author: robintw

pandas/core/frame.py

@@ -2745,7 +2745,7 @@ def dropna(self, axis=0, how='any', thresh=None, subset=None,
 
         Parameters
         ----------
-        axis : {0, 1}, or tuple/list thereof
+        axis : {0 or 'index', 1 or 'columns'}, or tuple/list thereof
             Pass tuple or list to drop on multiple axes
         how : {'any', 'all'}
             * any : if any NA values are present, drop that label
@@ -2890,7 +2890,7 @@ def sort(self, columns=None, axis=0, ascending=True,
         ascending : boolean or list, default True
             Sort ascending vs. descending. Specify list for multiple sort
             orders
-        axis : {0, 1}
+        axis : {0 or 'index', 1 or 'columns'}, default 0
             Sort index/rows versus columns
         inplace : boolean, default False
             Sort the DataFrame without creating a new instance
@@ -2919,7 +2919,7 @@ def sort_index(self, axis=0, by=None, ascending=True, inplace=False,
 
         Parameters
         ----------
-        axis : {0, 1}
+        axis : {0 or 'index', 1 or 'columns'}, default 0
             Sort index/rows versus columns
         by : object
             Column name(s) in frame. Accepts a column name or a list
@@ -3027,7 +3027,7 @@ def sortlevel(self, level=0, axis=0, ascending=True,
         Parameters
         ----------
         level : int
-        axis : {0, 1}
+        axis : {0 or 'index', 1 or 'columns'}, default 0
         ascending : boolean, default True
         inplace : boolean, default False
             Sort the DataFrame without creating a new instance
@@ -3639,9 +3639,9 @@ def apply(self, func, axis=0, broadcast=False, raw=False, reduce=None,
         ----------
         func : function
             Function to apply to each column/row
-        axis : {0, 1}
-            * 0 : apply function to each column
-            * 1 : apply function to each row
+        axis : {0 or 'index', 1 or 'columns'}, default 0
+            * 0 or 'index': apply function to each column
+            * 1 or 'columns': apply function to each row
         broadcast : boolean, default False
             For aggregation functions, return object of same size with values
             propagated
@@ -4162,8 +4162,8 @@ def corrwith(self, other, axis=0, drop=False):
         Parameters
         ----------
         other : DataFrame
-        axis : {0, 1}
-            0 to compute column-wise, 1 for row-wise
+        axis : {0 or 'index', 1 or 'columns'}, default 0
+            0 or 'index' to compute column-wise, 1 or 'columns' for row-wise
         drop : boolean, default False
             Drop missing indices from result, default returns union of all
 
@@ -4214,8 +4214,8 @@ def count(self, axis=0, level=None, numeric_only=False):
 
         Parameters
         ----------
-        axis : {0, 1}
-            0 for row-wise, 1 for column-wise
+        axis : {0 or 'index', 1 or 'columns'}, default 0
+            0 or 'index' for row-wise, 1 or 'columns' for column-wise
         level : int or level name, default None
             If the axis is a MultiIndex (hierarchical), count along a
             particular level, collapsing into a DataFrame
@@ -4368,8 +4368,8 @@ def idxmin(self, axis=0, skipna=True):
 
         Parameters
         ----------
-        axis : {0, 1}
-            0 for row-wise, 1 for column-wise
+        axis : {0 or 'index', 1 or 'columns'}, default 0
+            0 or 'index' for row-wise, 1 or 'columns' for column-wise
         skipna : boolean, default True
             Exclude NA/null values. If an entire row/column is NA, the result
             will be NA
@@ -4399,8 +4399,8 @@ def idxmax(self, axis=0, skipna=True):
 
         Parameters
         ----------
-        axis : {0, 1}
-            0 for row-wise, 1 for column-wise
+        axis : {0 or 'index', 1 or 'columns'}, default 0
+            0 or 'index' for row-wise, 1 or 'columns' for column-wise
         skipna : boolean, default True
             Exclude NA/null values. If an entire row/column is NA, the result
             will be first index.
@@ -4446,9 +4446,9 @@ def mode(self, axis=0, numeric_only=False):
 
         Parameters
         ----------
-        axis : {0, 1, 'index', 'columns'} (default 0)
-            * 0/'index' : get mode of each column
-            * 1/'columns' : get mode of each row
+        axis : {0 or 'index', 1 or 'columns'}, default 0
+            * 0 or 'index' : get mode of each column
+            * 1 or 'columns' : get mode of each row
         numeric_only : boolean, default False
             if True, only apply to numeric columns
 
@@ -4553,7 +4553,7 @@ def rank(self, axis=0, numeric_only=None, method='average',
 
         Parameters
         ----------
-        axis : {0, 1}, default 0
+        axis : {0 or 'index', 1 or 'columns'}, default 0
             Ranks over columns (0) or rows (1)
         numeric_only : boolean, default None
             Include only float, int, boolean data
@@ -4605,7 +4605,7 @@ def to_timestamp(self, freq=None, how='start', axis=0, copy=True):
         how : {'s', 'e', 'start', 'end'}
             Convention for converting period to timestamp; start of period
             vs. end
-        axis : {0, 1} default 0
+        axis : {0 or 'index', 1 or 'columns'}, default 0
             The axis to convert (the index by default)
         copy : boolean, default True
             If false then underlying input data is not copied
@@ -4636,7 +4636,7 @@ def to_period(self, freq=None, axis=0, copy=True):
         Parameters
         ----------
         freq : string, default
-        axis : {0, 1}, default 0
+        axis : {0 or 'index', 1 or 'columns'}, default 0
             The axis to convert (the index by default)
         copy : boolean, default True
             If False then underlying input data is not copied