How to calculate the average of one or more columns in a Pandas DataFrame?

In order to find the average of a single or multiple pandas columns we use the DataFrame mean() function. Here are two simple examples, that assume your DataFrame name is mydf and you columns are col_1 and col_2:

# one column

# multiple
mydf[['col_1', 'col_2']].mean()

Compute average of selected pandas columns – Example

Let’s get started by prepping our test DataFrame. As usual, we’ll use the auto-generated candidates data.

Here we go:

import pandas as pd
data = pd.read_csv('survey.csv')


Here’s the result.


Note that if you want to follow along this example, you can copy the following table and use the pd.read_clipboard() method to populate your own dataframe.

import pandas as pd
your_df = pd.read_clipboard()

Find the mean / average of one column

To find the average of one column (Series), we simply type:


The result will be 126.

Calculate mean of multiple columns

In our case, we can simply invoke the mean() method on the DataFrame itself.


The result will be:

salary            126.0
num_candidates     80.5
dtype: float64

Chances are that your DataFrame will be wider, and contains several columns. In that case, we’ll first subset our DataFrame by the relevant columns and then calculate the mean.

cols = ['salary', 'num_candidates']


The result will be similar.

Find pandas columns average with describe()

We typically use the describe() DataFrame method in order to quickly look into our dataset descriptive statistical figures – such as the cont, minimum and maximum values, standard deviation etc’.

We can use the following snippet to get a Series representing the mean of each numeric column in our DataFrame:

stats = data.describe()

This will return the following Series:

salary            126.0
num_candidates     80.5
Name: mean, dtype: float64

Creating a DataFrame or list from your columns mean values

You can easily turn your mean values into a new DataFrame or to a Python list object:

data_mean = pd.DataFrame(data.mean(), columns=['mean_values'])

#create list of mean values
mean_lst = data.mean().to_list

Plot column average in Pandas

As the Pandas library contains basic methods for plotting, making a simple chart to visualize multiple column averages is a breeze:


Here’s the chart:

Calculate the mean of you Series with df.describe()

We can use the DataFrame method pd.describe to quickly look into the key statistical calculations of our DataFrame numeric columns – including the mean.


And the result:

Calculate the median of a DataFrame

For completeness, here’s a simple snippet to calculate the median of multiple DataFrame columns:


This will render the following results, which represent the median observation of each columns of the dataset.

salary            122.0
num_candidates     79.5
dtype: float64