How to calculate the percentage of the sum value of the column?

Question

I have a pandas dataframe which looks like this:

Country  Sold
 Japan   3432
 Japan   4364
 Korea   2231
 India   1130
 India   2342
  USA    4333
  USA    2356
  USA    3423

I have use the code below and get the sum of the "sold" column

df1= df.groupby(df['Country'])
df2 = df1.sum()

I want to ask how to calculate the percentage of the sum of "sold" column.

Answer 1

You can get the percentage by adding this code

df2["percentage"] = df2['Sold']*100 / df2['Sold'].sum()

In the output dataframe, a column with the percentage of each country is added.

Answer 2

We can divide the original Sold column by a new column consisting of the grouped sums but keeping the same length as the original DataFrame, by using transform

df.assign(
    pct_per=df['Sold'] / df.groupby('Country').transform(pd.DataFrame.sum)['Sold']
    )

  Country  Sold   pct_per
0   Japan  3432  0.440226
1   Japan  4364  0.559774
2   Korea  2231  1.000000
3   India  1130  0.325461
4   India  2342  0.674539
5     USA  4333  0.428501
6     USA  2356  0.232991
7     USA  3423  0.338509

Answer 3

Simple Solution

You were almost there.

1. First you need to group by country
2. Then create the new percentage column (by dividing grouped sales with sum of all sales)

# reset_index() is only there because the groupby makes the grouped column the index
df_grouped_countries = df.groupby(df.Country).sum().reset_index()
df_grouped_countries['pct_sold'] = df_grouped_countries.Sold / df.Sold.sum()

Answer 4

Are you looking for the percentage after or before aggregation?

import pandas as pd
countries = [['Japan',3432],['Japan',4364],['Korea',2231],['India',1130],    ['India',2342],['USA',4333],['USA',2356],['USA',3423]]
df = pd.DataFrame(countries,columns=['Country','Sold'])
df1 = df.groupby(df['Country'])
df2 = df1.sum()
df2['percentage'] = (df2['Sold']/df2['Sold'].sum()) * 100
df2