How to use groupby() to calculate the frequency of unique value In Python Pandas

Using values_counts() to calculate the frequency of unique value

Using apply().fillna() function to calculate the frequency of unique value

Here we are using the groupby() function to group all the same values and then calculate their frequencies.

Python3

import pandas as pd
 
technologies = {
    "data":[2, 3, 4, 5, 5, 6, 
            7, 8, 9, 5, 3]
               }
df = pd.DataFrame(technologies)
 
df['frequency'] = df.groupby('data')
                  ['data'].transform('count')
print(df)

Output:

Calculate the frequency counts of each unique value

Calculate the frequency counts of each unique value of a Pandas series

Let us see how to find the frequency counts of each unique value of a Pandas series. We will use these methods to calculate the frequency counts of each unique value of a Pandas series.

Tags:

#Python pandas-series #Python-pandas #Python #python

Using values_counts() to calculate the frequency of unique value

Using apply().fillna() function to calculate the frequency of unique value

How to use groupby() to calculate the frequency of unique value In Python Pandas

Python3

Calculate the frequency counts of each unique value of a Pandas series

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