added rename

Author: hansalemaos

README.md

@@ -29,6 +29,8 @@ df = pd.read_csv("https://github.com/pandas-dev/pandas/raw/main/doc/data/air_qua
 - df.d_natsort_index 
 - df.d_natort_columns 
 - df.d_natsort_df_by_column 
+- d_rename_index
+- d_rename_columns
 
 **All methods added to pandas have one of this prefixes:**
 
@@ -79,7 +81,6 @@ Index(['country', 'city', 'date.utc', 'location', 'parameter', 'value',
 5270      GB     London  2019-04-09 03:00:00+00:00  ...       no2  67.0  µg/m³
 5271      GB     London  2019-04-09 02:00:00+00:00  ...       no2  67.0  µg/m³
 [5272 rows x 7 columns]
-
 ```
 
 ### df.ds_sort_by_str_length
@@ -115,7 +116,6 @@ print(df2)
 3548  Antwerpen      BE  2019-05-19 21:00:00+00:00  ...       no2  12.5  µg/m³
 0     Antwerpen      BE  2019-06-18 06:00:00+00:00  ...      pm25  18.0  µg/m³
 [5272 rows x 7 columns]
-
 ```
 
 ### d_insert_column_before_another
@@ -151,7 +151,6 @@ Out[7]:
 5270     London      GB  2019-04-09 03:00:00+00:00  ...     LondonGB  67.0  µg/m³
 5271     London      GB  2019-04-09 02:00:00+00:00  ...     LondonGB  67.0  µg/m³
 [5272 rows x 8 columns]
-
 ```
 
 ### df.ds_reverse
@@ -384,7 +383,6 @@ Index(['pm25', 'pm25', 'pm25', 'pm25', 'pm25', 'pm25', 'pm25', 'pm25', 'pm25',
        ...
        'no2', 'no2', 'no2', 'no2', 'no2', 'no2', 'no2', 'no2', 'no2', 'no2'],
       dtype='object', length=5272)
-
 ```
 
 ### df.d_natsort_index
@@ -486,3 +484,61 @@ Out[4]:
 1825      Paris      FR  2019-06-21 00:00:00+00:00  ...       no2  20.0  µg/m³
 [5272 rows x 7 columns]
 ```
+
+### df.d_rename_columns / df.d_rename_index
+
+```python
+df = pd.read_csv(    "https://github.com/pandas-dev/pandas/raw/main/doc/data/titanic.csv")
+
+print(df)
+     PassengerId  Survived  Pclass  ...     Fare Cabin  Embarked
+0              1         0       3  ...   7.2500   NaN         S
+1              2         1       1  ...  71.2833   C85         C
+2              3         1       3  ...   7.9250   NaN         S
+3              4         1       1  ...  53.1000  C123         S
+4              5         0       3  ...   8.0500   NaN         S
+..           ...       ...     ...  ...      ...   ...       ...
+886          887         0       2  ...  13.0000   NaN         S
+887          888         1       1  ...  30.0000   B42         S
+888          889         0       3  ...  23.4500   NaN         S
+889          890         1       1  ...  30.0000  C148         C
+890          891         0       3  ...   7.7500   NaN         Q
+
+
+df.d_rename_columns(Fare='Embarked',Embarked='Fare',Cabin='cabin2')
+df.d_rename_index({1: 1000000,2:50022})
+print(df)
+
+         PassengerId  Survived  Pclass  ... Embarked cabin2  Fare
+0                  1         0       3  ...   7.2500    NaN     S
+1000000            2         1       1  ...  71.2833    C85     C
+50022              3         1       3  ...   7.9250    NaN     S
+3                  4         1       1  ...  53.1000   C123     S
+4                  5         0       3  ...   8.0500    NaN     S
+              ...       ...     ...  ...      ...    ...   ...
+886              887         0       2  ...  13.0000    NaN     S
+887              888         1       1  ...  30.0000    B42     S
+888              889         0       3  ...  23.4500    NaN     S
+889              890         1       1  ...  30.0000   C148     C
+890              891         0       3  ...   7.7500    NaN     Q
+[891 rows x 12 columns]
+
+df.d_rename_columns({'Embarked': 'Fare', 'Fare' : 'Embarked', 'cabin2' : 'Cabin'})
+df.index = df.index.astype('string')
+df.index = 'a' + df.index
+df.d_rename_index(a1000000= 1,a50022=2)
+print(df)
+
+      PassengerId  Survived  Pclass  ...     Fare Cabin  Embarked
+a0              1         0       3  ...   7.2500   NaN         S
+1               2         1       1  ...  71.2833   C85         C
+2               3         1       3  ...   7.9250   NaN         S
+a3              4         1       1  ...  53.1000  C123         S
+a4              5         0       3  ...   8.0500   NaN         S
+           ...       ...     ...  ...      ...   ...       ...
+a886          887         0       2  ...  13.0000   NaN         S
+a887          888         1       1  ...  30.0000   B42         S
+a888          889         0       3  ...  23.4500   NaN         S
+a889          890         1       1  ...  30.0000  C148         C
+a890          891         0       3  ...   7.7500   NaN         Q
+```

__init__.py

@@ -1,5 +1,6 @@
 import numpy as np
 import regex
+from flatten_any_dict_iterable_or_whatsoever import fla_tu
 from natsort import ns, index_natsorted, natsorted
 import pandas as pd
 from typing import Union
@@ -420,6 +421,47 @@ def sort_whole_df_with_natsort(
         )
         return df2.copy()
 
+def check_if_equal(vara, varb):
+    if str(type(vara)) == str(type(varb)):
+        if str(vara) == str(varb):
+            if len(set(dir(vara)) ^ set(dir(varb))) == 0:
+                return True
+    return False
+
+def fladicol(*args, **kwargs):
+    return {x[1][-1]:x[0] for x in (fla_tu([args, kwargs]))}
+
+def rename_columns(*args, **kwargs):
+    kwargs['______col____or____index'] = 'columns'
+    kwargs['______df___']  = args[0]
+    return rename_columnsindex(*args, **kwargs)
+
+def rename_index(*args, **kwargs):
+    kwargs['______col____or____index'] = 'index'
+    kwargs['______df___']  = args[0]
+    return rename_columnsindex(*args, **kwargs)
+
+def rename_columnsindex(*args, **kwargs):
+    df2 = kwargs['______df___']
+    iscols  = kwargs['______col____or____index'] == 'columns'
+    if iscols:
+        startcols = [x for x in df2.columns.to_list()]
+    else:
+        startcols = [x for x in df2.index.to_list()]
+    kwargs = {x[0]:x[1] for x in kwargs.items() if x[0] not in ['______col____or____index','______df___']}
+    renamedict = fladicol(*args[1:],**kwargs)
+    newdict= {}
+    for ini,col in enumerate(startcols):
+        if col not in renamedict:
+            newdict[ini] = col
+        else:
+            newdict[ini] = renamedict[col]
+    finallist = [x[1] for x in sorted(newdict.items())]
+    if iscols:
+        df2.columns = finallist
+    else:
+        df2.index = finallist
+    return df2
 
 def pd_add_index_and_columns():
     DataFrame.d_swap_2_columns = change_places_2_columns
@@ -444,3 +486,5 @@ def pd_add_index_and_columns():
     DataFrame.d_natsort_index = qq_d_sort_index
     DataFrame.d_natort_columns = qq_d_sort_columns
     DataFrame.d_natsort_df_by_column = sort_whole_df_with_natsort
+    DataFrame.d_rename_columns = rename_columns
+    DataFrame.d_rename_index = rename_index