{"id":201508,"date":"2025-04-02T05:33:02","date_gmt":"2025-04-02T05:33:02","guid":{"rendered":"https:\/\/namso-gen.co\/blog\/how-to-get-index-value-of-a-row-in-pandas\/"},"modified":"2025-04-02T05:33:02","modified_gmt":"2025-04-02T05:33:02","slug":"how-to-get-index-value-of-a-row-in-pandas","status":"publish","type":"post","link":"https:\/\/namso-gen.co\/blog\/how-to-get-index-value-of-a-row-in-pandas\/","title":{"rendered":"How to get index value of a row in pandas?"},"content":{"rendered":"

When working with pandas, you may encounter scenarios where you need to retrieve the index value of a specific row in a DataFrame or Series. There are a few different ways to accomplish this task, depending on your specific use case.<\/p>\n

One common method to get the index value of a row in pandas is by using the `.iloc[]` method along with the `.index` attribute. This allows you to access the numerical index of a row by providing the integer location of the row within the dataset.<\/p>\n

Here’s how you can get the index value of a row in pandas using the `.iloc[]` method:<\/p>\n

“`python
\nimport pandas as pd<\/p>\n

# Create a sample DataFrame
\ndata = {‘A’: [1, 2, 3, 4, 5],
\n ‘B’: [‘a’, ‘b’, ‘c’, ‘d’, ‘e’]}
\ndf = pd.DataFrame(data)<\/p>\n

# Get the index value of the second row
\nindex_value = df.index[1]<\/p>\n

print(index_value)
\n“`<\/p>\n

In this example, we are retrieving the index value of the second row in the DataFrame `df`. The output will be `1`, which is the index value of the second row in the DataFrame.<\/p>\n

**Another way to get the index value of a row in pandas is by using a boolean mask based on specific conditions. By filtering the DataFrame using a condition that matches the row you are interested in, you can access the index value of that row.**<\/p>\n

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