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Finding Null Values

DataFrames often contain missing values, represented as None or NaN. When working with DataFrames, it's essential to identify these missing values because they can distort calculations, lead to inaccurate analyses, and compromise the reliability of results.

Addressing them ensures data integrity and improves the performance of tasks like statistical analysis and machine learning. For this purpose, pandas offers specific methods.

The first of these is isna(), which returns a boolean DataFrame. In this context, a True value indicates a missing value within the DataFrame, while a False value suggests the value is present.

For clarity, we'll apply this method on the animals DataFrame. The isna() method will return a DataFrame filled with True/False values, where each True value represents a missing value in the animals DataFrame.


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import pandas as pd
import numpy as np

animals_data = {'animal': [np.NaN, 'Dog', np.NaN, 'Cat','Parrot', None],
'name': ['Dolly', None, 'Erin', 'Kelly', None, 'Odie']}
animals = pd.DataFrame(animals_data)
# Find missing values
missing_values = animals.isna()
print(missing_values)

The second method is isnull(). It behaves identically to the previous one, with no discernible difference between them.

Task

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You are given a DataFrame named wine_data.

Retrieve the missing values in this DataFrame and store the result in the missing_values variable.

Solution

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Section 3. Chapter 6

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Finding Null Values

Addressing them ensures data integrity and improves the performance of tasks like statistical analysis and machine learning. For this purpose, pandas offers specific methods.


              123456789
            
import pandas as pd
import numpy as np

animals_data = {'animal': [np.NaN, 'Dog', np.NaN, 'Cat','Parrot', None],
'name': ['Dolly', None, 'Erin', 'Kelly', None, 'Odie']}
animals = pd.DataFrame(animals_data)
# Find missing values
missing_values = animals.isna()
print(missing_values)

The second method is isnull(). It behaves identically to the previous one, with no discernible difference between them.

Task

Swipe to start coding

You are given a DataFrame named wine_data.

Retrieve the missing values in this DataFrame and store the result in the missing_values variable.

Solution

Switch to desktop for real-world practiceContinue from where you are using one of the options below

Everything was clear?

Thanks for your feedback!

Section 3. Chapter 6

Switch to desktop for real-world practiceContinue from where you are using one of the options below