How to RANK in a Pandas DataFrame in Python
Next, you can use the rank() function to assign a rank to each value in the ‘price’ column, based on their order.
For example, to assign a rank to each value in the ‘price’ column, you can use the following code:
df['rank'] = df['price'].rank()
You can also use the rank() function with method parameter, it can take ‘average’,’min’,’max’,’first’,’dense’ methods to define the way of ranking
df['rank'] = df['price'].rank(method='min')
You can also use the ascending parameter in rank() function, to define if ranking should be in ascending or descending order
df['rank'] = df['price'].rank(ascending = False)
By using the rank() function, you can easily assign a rank to each value in a column of a Pandas DataFrame in Python. This can be useful for data analysis and can help you understand how different values compare to each other. It can also be used for competition analysis where you want to see how a particular value ranks with respect to other values in the dataset.
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