Pandas DataFrame Last_valid_index Method

Introduction

The last_valid_index() method in pandas is used to get the index of the last non-null/NaN value in a DataFrame. It returns a scalar value that represents the index. If all the elements are non-null/NaN, it returns None. If the DataFrame is empty, it also returns None. This method is helpful for finding the position of the last non-null/NaN value in a DataFrame.

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Skills Graph

Create a DataFrame with null values

First, let's create a DataFrame with null values using the np.nan value and the pandas library. This DataFrame will have some non-null/NaN values as well.

## Importing pandas as pd
import pandas as pd
## Importing numpy as np
import numpy as np

df = pd.DataFrame([[np.nan, np.nan, np.nan],
                   [np.nan, 2, 5],
                   [1, 3, 4],
                   [np.nan, 3, np.nan],
                   [2, 8, 0],
                   [7, 5, 4]],
                  columns=list('ABC'))
print("-----The DataFrame is-----")
print(df)

Get the index of the last non-null/NaN value

Next, we will use the last_valid_index() method on the DataFrame to get the index of the last non-null/NaN value.

print("Index for last non-null/NaN value is:", df.last_valid_index())

Create a DataFrame with only null values

Now, let's create another DataFrame with only null values using the np.nan value and the pandas library.

## Importing pandas as pd
import pandas as pd
## Importing numpy as np
import numpy as np

df = pd.DataFrame([[np.nan, np.nan, np.nan],
                   [np.nan, np.nan, np.nan],
                   [np.nan, np.nan, np.nan],
                   [2, 8, 0],
                   [7, 5, 4],
                   [np.nan, np.nan, np.nan]],
                  columns=list('ABC'))
print("-----The DataFrame is-----")
print(df)

Get the index of the last non-null/NaN value in the second DataFrame

Similarly, we will use the last_valid_index() method on this DataFrame to get the index of the last non-null/NaN value.

print("Index for last non-null/NaN value is:", df.last_valid_index())

Create a DataFrame with only null values

Lastly, let's create a DataFrame with only null values again using the np.nan value and the pandas library.

## Importing pandas as pd
import pandas as pd
## Importing numpy as np
import numpy as np

df = pd.DataFrame([[np.nan, np.nan, np.nan],
                   [np.nan, np.nan, np.nan],
                   [np.nan, np.nan, np.nan],
                   [np.nan, np.nan, np.nan]],
                  columns=list('ABC'))
print("-----The DataFrame is-----")
print(df)

Get the index of the last non-null/NaN value in the third DataFrame

Finally, we will use the last_valid_index() method on this DataFrame to get the index of the last non-null/NaN value.

print("Index for last non-null/NaN value is:", df.last_valid_index())

Summary

In this lab, we learned about the last_valid_index() method in pandas. We saw how to use this method to get the index of the last non-null/NaN value in a DataFrame. We also observed that this method returns None if all the elements are non-null/NaN, or if the DataFrame is empty. This method is useful for finding the position of the last non-null/NaN value in a DataFrame.