[英]Sum specific dataframe rows by columns
I have a multi index dataframe (df):我有一个多索引数据框(df):
working_pattern Full-time Part-time
sex Male Female Male Female
salary_band
Up to 15000 630 208 403 348
15001 - 20000 741 279 170 401
20001 - 25000 929 722 320 596
25001 - 30000 818 571 725 587
30001 - 35000 175 273 711 383
35001 - 40000 212 928 855 929
40001 - 45000 586 937 577 141
45001 - 50000 876 382 995 786
I am trying to sum rows 40001 - 45000
and 45001 - 50000
.我正在尝试对40001 - 45000
和45001 - 50000
行求和。 So the output looks like:所以输出看起来像:
working_pattern Full-time Part-time
sex Male Female Male Female
salary_band
Up to 15000 630 208 403 348
15001 - 20000 741 279 170 401
20001 - 25000 929 722 320 596
25001 - 30000 818 571 725 587
30001 - 35000 175 273 711 383
35001 - 40000 212 928 855 929
40001 + 1462 1319 1572 927
I have tried:我努力了:
df["40001 +"] = df.loc[['40001 - 45000','45001 - 50000']].sum()
without success没有成功
Use DataFrame.loc
for add new row:使用DataFrame.loc
添加新行:
df.loc["40001 +"] = df.loc[['40001 - 45000','45001 - 50000']].sum()
print (df)
working_pattern Full-time Part-time
sex Male Female Male Female
salary_band
Up to 15000 630 208 403 348
15001 - 20000 741 279 170 401
20001 - 25000 929 722 320 596
25001 - 30000 818 571 725 587
30001 - 35000 175 273 711 383
35001 - 40000 212 928 855 929
40001 - 45000 586 937 577 141
45001 - 50000 876 382 995 786
40001 + 1462 1319 1572 927
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