在熊猫数据框中订购一列

Question

I need to create a dataframe filtering out the five most frequently listed countries in the Nationality column and the total amount of times they are listed. I've been trying to use groupby, but have been unsuccessful. The code i've used it

df.groupby(['Nationality']).sum() 

I also need to determine what percent of those listed as participating in the program have at least one referral. I'm not sure the code for this either though.

Answer 1

检查这个问题及其答案，它与您要求的相似。

Answer 2

Filter out rows which contain Nationality that is in top 5 nationalities:

df[df['Nationality'].isin(df['Nationality'].value_counts().index[:6]) == False]

See how many times they're listed by looking at shape of df where rows contain Nationality that is in top 5:

df[df['Nationality'].isin(df['Nationality'].value_counts().index[:6])].shape

Quick way to see what percent of Number_of_Referalls has value > or = to 1:

(df['Number_of_Referalls '] >= 1).value_counts(normalize=True) * 100