Join multiple rows having a common column Pandas-CodePudding

I'm working on Covid data from

Here's what I tried:

import time
t = time.process_time()

avg_life_exp = {}
for i in covid['location']:
    count = 0
    avg = 0
    loc = i
    if i == loc:
        avg  = covid['life_expectancy']
        count  = 1
    else:
        avg = avg/count
    avg_life_exp[i] = avg

print(avg_life_exp)

elapsed_time = time.process_time() - t
print(elapsed_time)

Output (I got repeated values of the added screenshot):

CodePudding user response：

Use groupby and compute mean on life_expectancy,:

out = df.groupby('location')['life_expectancy'].mean().reset_index()
print(out)

# Output
              location  life_expectancy
0          Afghanistan            64.83
1               Africa              NaN
2              Albania            78.57
3              Algeria            76.88
4              Andorra            83.73
..                 ...              ...
233  Wallis and Futuna            79.94
234              World            72.58
235              Yemen            66.12
236             Zambia            63.89
237           Zimbabwe            61.49

[238 rows x 2 columns]