CODEWITHSUNDEEP
pythonpandasfrequency
runningbirds
runningbirds

Reputation: 6615

frequency table as a data frame in pandas

I'm looking for a more efficient way to do this as I am new to python. I want a data frame of the cyl value and the counts - ideally without having to go and do the rename column. I'm coming from R.

What is happening is 'cyl' is the index if i don't use the to-frame.reset-index piece of code and when I do use the reset-index code it becomes a column called 'index' - which is really the cyl values, while the the 2nd column 'cyl' is really the frequency counts..

import pandas as pd 

new_df = pd.value_counts(mtcars.cyl).to_frame().reset_index()
new_df.columns = ['cyl', 'frequency']

Upvotes: 1

Views: 2959

Answers (1)

jezrael
jezrael

Reputation: 862661

I think you can omit to_frame():

new_df = pd.value_counts(mtcars.cyl).reset_index()
new_df.columns = ['cyl', 'frequency']

Sample:

mtcars = pd.DataFrame({'cyl':[1, 2, 2, 4, 4]})
print (mtcars)
   cyl
0    1
1    2
2    2
3    4
4    4

new_df = pd.value_counts(mtcars.cyl).reset_index()
new_df.columns = ['cyl', 'frequency']
print (new_df)
   cyl  frequency
0    4          2
1    2          2
2    1          1

Upvotes: 1

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