Rename Specific Column(S) in Pandas

Rename specific column(s) in pandas

data.rename(columns={'gdp':'log(gdp)'}, inplace=True)

The rename show that it accepts a dict as a param for columns so you just pass a dict with a single entry.

Also see related

Renaming column names in Pandas

Just assign it to the .columns attribute:

>>> df = pd.DataFrame({'$a':[1,2], '$b': [10,20]})
>>> df
   $a  $b
0   1  10
1   2  20

>>> df.columns = ['a', 'b']
>>> df
   a   b
0  1  10
1  2  20

Changing a specific column name in pandas DataFrame

A one liner does exist:

In [27]: df=df.rename(columns = {'two':'new_name'})

In [28]: df
Out[28]: 
  one three  new_name
0    1     a         9
1    2     b         8
2    3     c         7
3    4     d         6
4    5     e         5

Following is the docstring for the rename method.

Definition: df.rename(self, index=None, columns=None, copy=True, inplace=False)
Docstring:
Alter index and / or columns using input function or
functions. Function / dict values must be unique (1-to-1). Labels not
contained in a dict / Series will be left as-is.

Parameters
----------
index : dict-like or function, optional
    Transformation to apply to index values
columns : dict-like or function, optional
    Transformation to apply to column values
copy : boolean, default True
    Also copy underlying data
inplace : boolean, default False
    Whether to return a new DataFrame. If True then value of copy is
    ignored.

See also
--------
Series.rename

Returns
-------
renamed : DataFrame (new object)

Renaming specific columns of pandas dataframe

df.rename by default returns the renamed DataFrame and leaves the original DataFrame unchanged. So you can either use

df.rename(..., inplace=True)

to do the column renames in place or reassign the returned, renamed DataFrame:

df = df.rename(...)

Rename specific columns in excel with pandas

Here is my try:

import pandas as pd
excelList = pd.read_excel("participantsList.xlsx", sheet_name="Table1")
#participatedList = open('participated.txt','r')
#CODE TO CHANGE THE PARAMETER
#excelList.to_excel(r'newList.xlsx')

data = pd.read_csv('participated.txt', sep=" ", header=None)
data.columns = ["First Name", "Last Name"]

newList = excelList.copy()

txt = 0
while txt < len(data):
    i = 0
    while i < len(excelList):
        if data['Last Name'][txt] == excelList['Last Name'][i]:
            newList.loc[i,'Participated'] = "Yes"
        i += 1
    txt += 1

newList.to_excel(r'newList.xlsx')

print(newList)

Pandas rename column by position?

try this

df.rename(columns={ df.columns[1]: "your value" }, inplace = True)

Rename column values using pandas DataFrame

If I am understanding your question correctly, you are trying to change the values in a column and not the column name itself.

Given you have mixed data type there, I assume that column is of type object and thus the number is read as string.

df['col_name'] = df['col_name'].str.replace('G', '1')

How to rename columns in Pandas automatically?

You can use:

df.columns = df.columns.map(lambda x: f'column_{x+1}')

Example output:

   column_1  column_2  column_3  column_4  column_5  column_6  column_7  column_8  column_9  column_10
0         0         1         2         3         4         5         6         7         8          9

Used input:

df = pd.DataFrame([range(10)])

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