如何在DataFrame中使用另一列中的值减去一列中的值？

Question

I have the following dataframe:

I want to see which country has the biggest difference between the column "Gold" and "Gold 1". The index currently is the countries.

As an example, with Afghanistan, it would be 0 - 0 = 0. I do this with every country and than the highest number in that list is my response. That's how I figured I want to do it.

Does anyone know how I can do that? Or is there a built-in function that can calculate that?

Answer 1

您可以使用内置向量减法减去这两列：

df1['Gold'] - df2['Gold 1']

Answer 2

The country with biggest difference is

df.Gold.sub(df['Gold 1']).idxmax()

The biggest absolute difference

df.Gold.sub(df['Gold 1']).abs().idxmax()

You can also sort this by the difference

df.loc[df.Gold.sub(df['Gold 1']).sort_values().index]

Or the absolute differences

df.loc[df.Gold.sub(df['Gold 1']).abs().sort_values().index]

Answer 3

you can try out the code below:

import pandas as pd
df = pd.DataFrame([['Afgh',0,0],['Agnt',18,0]], columns = ['Country','Gold','Gold1'])
df['GoldDiff'] = df['Gold'] - df['Gold1']
df.sort_values(by = 'GoldDiff', ascending = False)

df is just a test dataframe based on yours above. df['GoldDiff'] creates a new column to store differences.

Then you can simply sort the values by using the sort_values function from pandas. You can also add the option inplace = True if you want to modify your dataframe as the sorted one.