pandas dataframe rename column with code examples

Pandas DataFrame is a powerful and versatile tool for working with data in Python. One of the most common tasks when working with DataFrames is renaming columns. In this article, we will go over different methods to rename columns in a DataFrame using code examples.

The first method to rename columns in a DataFrame is using the rename() function. This function takes a dictionary as an argument where the keys are the old column names and the values are the new column names. Here is an example of how to use the rename() function to rename a single column:

import pandas as pd

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

# Print the original DataFrame
print(df)

# Rename column 'A' to 'X'
df = df.rename(columns={'A': 'X'})

# Print the DataFrame with the renamed column
print(df)

The output of this code will be:

   A  B
0  1  4
1  2  5
2  3  6

   X  B
0  1  4
1  2  5
2  3  6

In this example, the column named 'A' is renamed to 'X'.

You can also rename multiple columns at once by passing a dictionary with multiple key-value pairs to the rename() function. Here is an example of how to rename multiple columns:

import pandas as pd

# Create a DataFrame
df = pd.DataFrame({'A': [1, 2, 3], 'B': [4, 5, 6], 'C': [7, 8, 9]})

# Print the original DataFrame
print(df)

# Rename columns 'A' to 'X', 'B' to 'Y', and 'C' to 'Z'
df = df.rename(columns={'A': 'X', 'B': 'Y', 'C': 'Z'})

# Print the DataFrame with the renamed columns
print(df)

The output of this code will be:

   A  B  C
0  1  4  7
1  2  5  8
2  3  6  9

   X  Y  Z
0  1  4  7
1  2  5  8
2  3  6  9

In this example, the columns named 'A', 'B', and 'C' are renamed to 'X', 'Y', and 'Z', respectively.

Another method to rename columns in a DataFrame is by directly assigning a new name to a column using the df.columns property. Here is an example of how to use this method to rename a single column:

import pandas as pd

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

# Print the original DataFrame
print(df)

# Rename column 'A' to 'X'
df.columns = ['X', 'B']

# Print the DataFrame with the renamed column
print(df)
Another useful function for renaming columns in a DataFrame is the `.rename()` function with the `axis` parameter set to 1. This function allows you to rename columns by passing a dictionary of key-value pairs where the keys are the old column names and the values are the new column names. Here is an example:

``` python
import pandas as pd

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

# Print the original DataFrame
print(df)

# Rename column 'A' to 'X'
df = df.rename(columns={'A': 'X'}, axis=1)

# Print the DataFrame with the renamed column
print(df)

The output of this code will be:

   A  B
0  1  4
1  2  5
2  3  6

   X  B
0  1  4
1  2  5
2  3  6

In this example, the column named 'A' is renamed to 'X'.

It is also possible to rename columns by passing a list of new column names to the .columns property. This method is particularly useful when you want to change multiple column names at once. Here is an example:

import pandas as pd

# Create a DataFrame
df = pd.DataFrame({'A': [1, 2, 3], 'B': [4, 5, 6], 'C': [7, 8, 9]})

# Print the original DataFrame
print(df)

# Rename columns 'A' to 'X', 'B' to 'Y', and 'C' to 'Z'
df.columns = ['X', 'Y', 'Z']

# Print the DataFrame with the renamed columns
print(df)

The output of this code will be:

   A  B  C
0  1  4  7
1  2  5  8
2  3  6  9

   X  Y  Z
0  1  4  7
1  2  5  8
2  3  6  9

In this example, the columns named 'A', 'B', and 'C' are renamed to 'X', 'Y', and 'Z' respectively.

It's worth noting that when you rename columns in a DataFrame, the original column names are not modified and you can still access the original values by their original names. This means that if you want to keep the original DataFrame intact, you need to create a new DataFrame with the renamed columns.

In conclusion, renaming columns in a DataFrame is a simple and straightforward task that can be accomplished using the rename(), .columns, and .rename() function with the axis parameter set to 1. Each method has its own set of advantages and disadvantages and the best method to use will depend on the specific requirements of your project.

Popular questions

1. How can you rename a single column in a DataFrame?

• You can rename a single column in a DataFrame by using the rename() function and passing a dictionary where the keys are the old column names and the values are the new column names.

2. Is it possible to rename multiple columns at once in a DataFrame?

• Yes, it is possible to rename multiple columns at once in a DataFrame by using the rename() function and passing a dictionary with multiple key-value pairs where the keys are the old column names and the values are the new column names.

3. Can the original column names be modified when renaming columns in a DataFrame?

• No, when you rename columns in a DataFrame, the original column names are not modified, and you can still access the original values by their original names.

4. Is it possible to rename columns by passing a list of new column names to the .columns property?

• Yes, it is possible to rename columns by passing a list of new column names to the .columns property. This method is particularly useful when you want to change multiple column names at once.

5. Can we use axis parameter in rename function?

• Yes, rename() function accepts axis parameter as well, so you can use it to rename columns by passing a dictionary of key-value pairs where the keys are the old column names and the values are the new column names with axis=1.

Tag

DataWrangling