#df.rename() will only return a new df with the new headers

#df = df.rename() will change the heders of the current dataframe 

df = df.rename(columns={"old_col1": "new_col1", "old_col2": "new_col2"})

df = df.rename(columns = {'myvar':'myvar_new'})

df.rename(columns={"old_col1": "new_col1", "old_col2": "new_col2"})

df = df.rename(columns={'oldName1': 'newName1', 'oldName2': 'newName2'})

df.rename({'current':'updated'},axis = 1, inplace = True)

import pandas as pd

​

# Create a sample dataframe

data = {'A': [1, 2, 3], 'B': [4, 5, 6], 'C': [7, 8, 9]}

df = pd.DataFrame(data)

​

# Rename column 'A' to 'New Column'

df.rename(columns={'A': 'New Column'}, inplace=True)

​

# Print the modified dataframe

print(df)

import pandas as pd

​

# Assuming the dataframe is already created and stored in a variable called 'df'

​

# Print the current column names

print(df.columns)

​

# Rename a specific column

df.rename(columns={'current_column_name': 'new_column_name'}, inplace=True)

​

# Print the updated column names

print(df.columns)

import pandas as pd

# Example DataFrame

df = pd.DataFrame({'A': [1, 2, 3], 'B': [4, 5, 6]})

​

# Rename column 'A' to 'NewColumn'

df = df.rename(columns={'A': 'NewColumn'})

​

# Print the updated DataFrame

print(df)

print(df.rename(columns={'A': 'a', 'C': 'c'}))

#         a   B   c

# ONE    11  12  13

# TWO    21  22  23

# THREE  31  32  33

​

import pandas as pd

​

# Creating a sample DataFrame

df = pd.DataFrame({'A': [1, 2, 3], 'B': [4, 5, 6]})

​

# Displaying the DataFrame before changing column names

print(df)

​

# Renaming a single column

df = df.rename(columns={'A': 'NewA'})

​

# Renaming multiple columns

df = df.rename(columns={'A': 'NewA', 'B': 'NewB'})

​

# Displaying the DataFrame after changing column names

print(df)