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How to Rename Column and Index with Pandas

Unlock the power of Pandas, the leading data analysis library in Python, as we delve into the process of renaming columns and indexes in DataFrames. This comprehensive guide demonstrates various methods and tips to help you manage your data efficiently and effectively
By Saturn Cloud | | Miscellaneous

How to Rename Column and Index with Pandas

Pandas is a popular data analysis library in Python. It provides powerful tools for data manipulation and analysis. One of the essential features of Pandas is the ability to rename columns and indexes of a DataFrame. In this tutorial, we will learn how to rename columns and indexes with Pandas.

Renaming Columns

Renaming columns in Pandas is a straightforward process. We can use the rename() method to rename one or more columns of a DataFrame. The rename() method takes a dictionary as an argument, where the keys are the old column names, and the values are the new column names.

Let’s take an example DataFrame:

import pandas as pd

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

print(df)

Output:

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

Suppose we want to rename column A to X and column B to Y. We can do it as follows:

df = df.rename(columns={'A': 'X', 'B': 'Y'})

print(df)

Output:

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

As we can see, the columns A and B have been renamed to X and Y, respectively.

Renaming Indexes

Renaming indexes in Pandas is similar to renaming columns. We can use the rename() method to rename the index of a DataFrame. The rename() method takes a dictionary as an argument, where the key is the old index name, and the value is the new index name.

Let’s take an example DataFrame:

import pandas as pd

df = pd.DataFrame({
    'A': [1, 2, 3],
    'B': [4, 5, 6],
    'C': [7, 8, 9]
}, index=['X', 'Y', 'Z'])

print(df)

Output:

   A  B  C
X  1  4  7
Y  2  5  8
Z  3  6  9

Suppose we want to rename the index X to W. We can do it as follows:

df = df.rename(index={'X': 'W'})

print(df)

Output:

   A  B  C
W  1  4  7
Y  2  5  8
Z  3  6  9

As we can see, the index X has been renamed to W.

Renaming Columns and Indexes in Place

By default, the rename() method returns a new DataFrame with the renamed columns and indexes. However, we can also rename columns and indexes in place by setting the inplace parameter to True.

Let’s take an example DataFrame:

import pandas as pd

df = pd.DataFrame({
    'A': [1, 2, 3],
    'B': [4, 5, 6],
    'C': [7, 8, 9]
}, index=['X', 'Y', 'Z'])

print(df)

Output:

   A  B  C
X  1  4  7
Y  2  5  8
Z  3  6  9

Suppose we want to rename column A to X and index X to W in place. We can do it as follows:

df.rename(columns={'A': 'X'}, index={'X': 'W'}, inplace=True)

print(df)

Output:

   X  B  C
W  1  4  7
Y  2  5  8
Z  3  6  9

As we can see, the column A has been renamed to X, and the index X has been renamed to W in place.

Conclusion

Renaming columns and indexes is a common operation in data analysis. Pandas provides a simple and powerful way to rename columns and indexes with the rename() method. We can rename one or more columns and indexes by passing a dictionary as an argument, where the keys are the old names, and the values are the new names. We can also rename columns and indexes in place by setting the inplace parameter to True.

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