diff --git a/README.md b/README.md index 3fb7713..701d0da 100644 --- a/README.md +++ b/README.md @@ -3103,7 +3103,7 @@ Name: a, dtype: int64 ```python = ><== # Returns a Series of bools. - = +-*/ # Non-matching keys get value NaN. + = +-*/ # Items with non-matching keys get value NaN. ``` ```python @@ -3176,7 +3176,7 @@ b 3 4 ```python = ><== # Returns DataFrame of bools. - = +-*/ # Non-matching keys get value NaN. + = +-*/ # Items with non-matching keys get value NaN. ``` ```python @@ -3298,7 +3298,7 @@ c 7 8 ```python = .groupby(column_key/s) # DF is split into groups based on passed column. - = .get_group(group_key) # Selects a group by value of grouping column. + = .get_group(group_key/s) # Selects a group by value of grouping column. ``` #### Aggregate, Transform, Map: diff --git a/index.html b/index.html index 32d2e81..c7ed4f2 100644 --- a/index.html +++ b/index.html @@ -2650,7 +2650,7 @@ Name: a, dtype: int64 <Sr> = <Sr>[bools] # Or: <Sr>.i/loc[bools]
<Sr> = <Sr> ><== <el/Sr>                      # Returns a Series of bools.
-<Sr> = <Sr> +-*/ <el/Sr>                      # Non-matching keys get value NaN.
+<Sr> = <Sr> +-*/ <el/Sr>                      # Items with non-matching keys get value NaN.
 
<Sr> = <Sr>.append(<Sr>)                      # Or: pd.concat(<coll_of_Sr>)
 <Sr> = <Sr>.combine_first(<Sr>)               # Adds items that are not yet present.
@@ -2706,7 +2706,7 @@ b  3  4
 <DF>    = <DF>[<DF_of_bools>]                 # Assigns NaN to False values.
 
<DF>    = <DF> ><== <el/Sr/DF>                # Returns DataFrame of bools.
-<DF>    = <DF> +-*/ <el/Sr/DF>                # Non-matching keys get value NaN.
+<DF>    = <DF> +-*/ <el/Sr/DF>                # Items with non-matching keys get value NaN.
 
<DF>    = <DF>.set_index(column_key)          # Replaces row keys with values from a column.
 <DF>    = <DF>.reset_index()                  # Moves row keys to their own column.
@@ -2809,7 +2809,7 @@ c  7  8
 
 
 
<GB> = <DF>.groupby(column_key/s)             # DF is split into groups based on passed column.
-<DF> = <GB>.get_group(group_key)              # Selects a group by value of grouping column.
+<DF> = <GB>.get_group(group_key/s)            # Selects a group by value of grouping column.
 

Aggregate, Transform, Map:

<DF> = <GB>.sum/max/mean/idxmax/all()         # Or: <GB>.apply/agg(<agg_func>)
 <DF> = <GB>.rank/diff/cumsum/ffill()          # Or: <GB>.aggregate(<trans_func>)