combining specific row values within a dataframe

Question

Here's an image of my dataframe.

I am working on a dataframe that displays the amount of offices in each state. I am looking to combine the office count value in the state of CA which is split up into 2 separate rows/indexes.

Welcome to Stack Overflow. Please read how to ask good questions. Make sure your question covers these 3 elements: 1. Problem Statement 2. Your Code (it should be Minimal, Reproducible Example 3. Error Message (preferably full Traceback to help others review and provide feedback). Sometimes the same question may have already been asked. Make sure your question is not a duplicate — Joe Ferndz
– Joe Ferndz, Commented Mar 23, 2021 at 19:47
You can use df.groupby('state')['office_count'].sum() to get you the sum by state — Joe Ferndz
– Joe Ferndz, Commented Mar 23, 2021 at 19:48
Are the two index numbers 25 and 13 important for you? If yes, what do you want to do about them? If not, the above groupby will address the problem — Joe Ferndz
– Joe Ferndz, Commented Mar 23, 2021 at 19:49
these were the original index positions so not entirely relevant. Thank you this worked great! — Jake Walther
– Jake Walther, Commented Mar 23, 2021 at 20:03

acrobat · Accepted Answer · 2021-03-23 19:48:23Z

1

You can groupby the state column and sum the office_count column.

df = df.groupby('state').agg({'office_count' : 'sum'}).reset_index()

answered Mar 23, 2021 at 19:48

acrobat

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eduardoftdo · Accepted Answer · 2021-03-23 19:49:48Z

1

You can use the groupby function for this

import pandas as pd

data = {'index': [4, 41, 26, 25, 13, 47, 20],
        'state': ['AL', 'AR', 'AZ', 'CA', 'CA', 'CO', 'CT'],
        'office_count': [28, 23, 76, 408, 374, 150, 158]}

df = pd.DataFrame(data)

df.groupby(['state']).agg({'office_count': 'sum'})

answered Mar 23, 2021 at 19:49

eduardoftdo

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