How to calculate skewness and kurtosis using pandas?
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How to calculate skewness and kurtosis using pandas?

How to calculate skewness and kurtosis using pandas?

This recipe helps you calculate skewness and kurtosis using pandas

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Recipe Objective

Skewness is a measure of asymmetry of a distribution. Kurtosis describes the peakedness of the distribution.

So this recipe is a short example on How to calculate skewness and kurtosis using pandas. Let's get started.

Step 1 - Import the library

import pandas as pd import seaborn as sb

Let's pause and look at these imports. Pandas is generally used for performing mathematical operation and preferably over arrays. Seaborn is just used in here to import dataset.

Step 2 - Setup the Data

df = sb.load_dataset('tips')

Here we have imported tips dataset from seaborn library.

Now our dataset is ready.

Step 3 - Calculating

print(df['total_bill'].astype(float).skew()) print(df['total_bill'].astype(float).kurt())

Using skew() and kurt() function we have drawn the skewness and kurtosis of total_bill distribution.

Step 4 - Let's look at our dataset now

Once we run the above code snippet, we will see:

1.1332130376158205
1.2184840156638854

Results of our calculation can be seen in here.

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