Replace Using Mean, Median, or Mode

A common approach to replacing empty cells is by calculating the mean, median, or mode of the column. Pandas provides the mean(), median(), and mode() methods to compute these values for a given column.

Example

Calculate the mean and use it to replace any empty values.

import pandas as pd

df = pd.read_csv(‘data.csv’)

x = df[“Calories”].mean()

df[“Calories”].fillna(x, inplace = True)

The mean is the average value, calculated by dividing the sum of all values by the number of values.

Example

Calculate the median and replace any empty values with it.

import pandas as pd

df = pd.read_csv(‘data.csv’)

x = df[“Calories”].median()

df[“Calories”].fillna(x, inplace = True)

The median is the middle value after sorting all the values in ascending order.

Example

Calculate the mode and replace any empty values with it.

import pandas as pd

df = pd.read_csv(‘data.csv’)

x = df[“Calories”].mode()[0]

df[“Calories”].fillna(x, inplace = True)

The mode is the value that occurs most frequently in a dataset.