How to find rank in a pandas dataframe?

How to find rank in a pandas dataframe?

How to find rank in a pandas dataframe?

This recipe helps you find rank in a pandas dataframe

Recipe Objective

The rank() function is used to compute numerical data ranks (1 through n) along axis. By default, equal values are assigned a rank that is the average of the ranks of those values.

So this recipe is a short example on How to find rank in a pandas dataframe. Let's get started.

Step 1 - Import the library

import pandas as pd

Let's pause and look at these imports. Pandas is generally used for performing mathematical operation and preferably over arrays.

Step 2 - Setup the Data

df = pd.DataFrame({"A":[0, 1, 2, 3, 5, 9], "B":[11, 5, 8, 6, 7, 8], "C":[2, 5, 10, 11, 9, 8]})

Here we have setup a random dataset with some random values in it.

Step 3 - Finding rank

df['default_rank'] = df['B'].rank() print(df)

Here we are applied rank to find out the rank order of column B.

Step 4 - Let's look at our dataset now

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

Scroll down to the ipython file to look at the results.

We can see the how the rank are assigned. Equal values takes equal ranks, midway between other ranks.

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