How to sum values in a column dataframe base on values in another column

Question

I have a data set which has video games, their sales, and the year the game was released. I am only looking for the game sales per year, not the game sales per title per year.

I am using a pandas Dataframe. I have tried a groupby method. I have tried a loop with .unique() values.

df = df[["Year", "NA_Sales"]]
df.Year = df.Year.astype(int)
df2 = df
df2.Year = df.Year.unique()

df2 = df.groupby(['Year'])['NA_Sales'].sum()

The expected result would be a dataframe including one column of unique year values, and one column of all video game sales for that year

df.groupby(['Year'])['NA_Sales'].sum().reset_index() ?

Bharath M Shetty
– Bharath M Shetty

2019-10-25 14:17:09 +00:00
Commented Oct 25, 2019 at 14:17 — Bharath M Shetty
– Bharath M Shetty, Commented Oct 25, 2019 at 14:17

moys · Accepted Answer · 2019-10-25 14:24:12Z

1

You can use

df.groupby('Year', as_index=False)['NA_Sales'].sum()

answered Oct 25, 2019 at 14:24

moys

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NOhs · Accepted Answer · 2019-10-25 14:50:45Z

0

This worked for me:

import pandas as pd

path = r'your path'
wb = pd.read_excel(path)
df =  pd.DataFrame(wb)
df.style.hide_index()
df1 = df[['YEAR', 'NA_SALES']]
GB=df1.groupby([df1['YEAR']]).sum()

Make sure that when you create the DataFrame the dtype is not a str.

edited Oct 25, 2019 at 14:50

NOhs

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answered Oct 25, 2019 at 14:44

SofiaChalk

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