Handling missing values in Series in Data Analysis Python

Introduction

Sometimes data is incomplete or missing. Handling missing values helps us clean data so we can analyze it correctly.

When you have a list of survey answers but some people skipped questions.

When sensor data has gaps because of connection problems.

When you want to calculate averages but some numbers are missing.

When preparing data for machine learning and missing values can cause errors.

Syntax

Data Analysis Python

series.isna()
series.dropna()
series.fillna(value)

isna() checks which values are missing.

dropna() removes missing values.

fillna(value) replaces missing values with a given value.

Examples

This shows True where values are missing.

Data Analysis Python

import pandas as pd
s = pd.Series([1, 2, None, 4])
print(s.isna())

This removes the missing value and returns a Series without it.

Data Analysis Python

print(s.dropna())

This replaces missing values with 0.

Data Analysis Python

print(s.fillna(0))

Sample Program

This program shows how to find missing values, remove them, and replace them with the average of the existing numbers.

Data Analysis Python

import pandas as pd

# Create a Series with some missing values
s = pd.Series([10, None, 20, None, 30])

# Check which values are missing
missing = s.isna()
print('Missing values in Series:')
print(missing)

# Remove missing values
cleaned = s.dropna()
print('\nSeries after removing missing values:')
print(cleaned)

# Replace missing values with the mean of existing values
mean_value = s.mean()
filled = s.fillna(mean_value)
print(f'\nSeries after filling missing values with mean ({mean_value}):')
print(filled)

Important Notes

Missing values are shown as NaN in pandas.

Use fillna() carefully; replacing with mean works for numbers but not for text.

Removing missing values with dropna() reduces data size.

Summary

Missing values can cause problems in data analysis.

Use isna() to find missing values.

Use dropna() to remove or fillna() to replace missing values.