[英]Creating a new column based on condition on other columns
我正在嘗試根據其他列中的條件創建一列。
一個房子里有5個人年齡。 我需要按不同性別和年齡組計算那所房子里的人數。
我寫的代碼不起作用
from pandas import DataFrame
df1 = pd.DataFrame({'member':[1,2], 'M1':[20,35],'M2':[27,42], 'M3':[77,62],'M4':[20,0],'M5':[0,35],
'G1':['M','F'],'G2':['M','F'],'G3':['M','F'],'G4':['M',0],'G5':[0,'F']})
#CODE WRITTEN
df1['M_20_to_30'] = ((df1[df1.columns[1:5]] >= 20) & (df1[df1.columns[1:5]] <= 30) & (df1[df1.columns[6:10]] == "M")).sum(1)
# EXPECTED OUTPUT
df1 = pd.DataFrame({'member':[1,2], 'M1':[20,35],'M2':[27,42], 'M3':[77,62],'M4':[20,0],'M5':[0,35],
'G1':['M','F'],'G2':['M','F'],'G3':['M','F'],'G4':['M',0],'G5':[0,'F'],'M_20_to_30':[2,0]})
你可以這樣做:
df1['M_20_to_30'] = (df1
.iloc[:,df1.columns.str.startswith('M')]
.apply(lambda x: sum(x.ge(20) & x.le(30))), 1))
member M1 M2 M3 M4 M5 G1 G2 G3 G4 G5 M_20_to_30
0 1 20 27 77 20 0 M M M M 0 3
1 2 35 42 62 0 35 F F F 0 F 0
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