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rename columns pandas
df.rename(columns={'oldName1': 'newName1',
'oldName2': 'newName2'},
inplace=True, errors='raise')
# Make sure you set inplace to True if you want the change
# to be applied to the dataframe
rename df column
import pandas as pd
data = pd.read_csv(file)
data.rename(columns={'original':'new_name'}, inplace=True)
pandas rename column
df.rename(columns={"old_col1": "new_col1", "old_col2": "new_col2"}, inplace=True)
rename column name pandas dataframe
df.rename(columns={"old_col1": "new_col1", "old_col2": "new_col2"})
rename column in dataframe
df.rename({"current": "updated"}, axis=1, inplace=True)
print(df.dtypes)
pandas dataframe column rename
>>> df = pd.DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]})
>>> df.rename(columns={"A": "a", "B": "c"})
a c
0 1 4
1 2 5
2 3 6
pandas dataframe rename column
df = df.rename(columns={'oldName1': 'newName1', 'oldName2': 'newName2'})
# Or rename the existing DataFrame (rather than creating a copy)
df.rename(columns={'oldName1': 'newName1', 'oldName2': 'newName2'}, inplace=True)
pandas rename column
df.rename({'current':'updated'},axis = 1, inplace = True)
Renaming Column Name Dataframe
df = df.rename(columns={'oldName1': 'newName1', 'oldName2': 'newName2'})
rename columns in dataframe
df.rename(columns = {'old_col1':'new_col1', 'old_col2':'new_col2'}, inplace = True)
how to rename columns in python
#how to rename columns with:
data = data.rename(columns={'Old_column' : 'New_column'})
dataframe rename column
# Define df
df = pd.DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]})
# Option 1
df = df.rename({"A": "a", "B": "c"}, axis=1)
# or
df.rename({"A": "a", "B": "c"}, axis=1, inplace=True)
# Option 2
df = df.rename(columns={"A": "a", "B": "c"})
# or
df.rename(columns={"A": "a", "B": "c"}, inplace=True)
# Result
>>> df
a c
0 1 4
1 2 5
2 3 6
rename column pandas
df_new = df.rename(columns={'A': 'a'}, index={'ONE': 'one'})
print(df_new)
# a B C
# one 11 12 13
# TWO 21 22 23
# THREE 31 32 33
print(df)
# A B C
# ONE 11 12 13
# TWO 21 22 23
# THREE 31 32 33
renaming column in dataframe pandas
df.rename({'a': 'X', 'b': 'Y'}, axis=1, inplace=True)
df
X Y c d e
0 x x x x x
1 x x x x x
2 x x x x x
Rename columns
df.rename({0: 'links'}, axis=1, inplace=True)
df rename columns
df.rename(columns = {'col1':'new_name', 'col2':'newcol2',
'col3':'newcol3'}, inplace = True)
rename column pandas
# Simple use case for pd.rename()
'''
old parameter = 'Data.Population'
new parameter = 'Population'
df.rename(columns={'old parameter': 'new parameter'}, inplace = True)
inplace = True : means to change object in real time
'''
# view below for visual aids
df.rename(columns={'Data.Population': 'Population'}, inplace = True)
# old columns
|'Data.Population'|
|_________________|
| 0 |
|_________________|
# new output:
# new rename column
|'Population' |
|_____________|
| 0 |
|_____________|
rename column pandas
>>> df.rename({1: 2, 2: 4}, axis='index')
A B
0 1 4
2 2 5
4 3 6
rename column pandas
>>> df.rename(index={0: "x", 1: "y", 2: "z"})
A B
x 1 4
y 2 5
z 3 6
rename columns
df.columns = ['V', 'W', 'X', 'Y', 'Z']
rename column pandas
>>> df.rename(columns={"A": "a", "B": "b", "C": "c"}, errors="raise")
Traceback (most recent call last):
KeyError: ['C'] not found in axis
Rename columns
# 20. Rename a column
df.rename(columns={"Airline": "Airline_Code", "AirportFrom":"Airport_From"})
rename column pandas
>>> df.rename(str.lower, axis='columns')
a b
0 1 4
1 2 5
2 3 6
Renaming and replacing the column variable name
income.columns = income.columns.str.replace('Y' , 'Year ')
income.columns
Renaming a column
ALTER TABLE table_name
RENAME COLUMN column_name TO new_column_name;
Code language: SQL (Structured Query Language) (sql)
rename column in dataframe
DataFrame.rename() method
Rename a column
df.rename(columns={"Airline": "Airline_Code", "AirportFrom":"Airport_From"})
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