我有一个这样的数据集,我想创建一个List of tuples
as
(Name_of_State , Literacy_rate)
(JAMMU&KASHMIR, 89.78) #example
我不得不做一些清理工作,清除一些地区,只是保留一些州
data=data[data['Name']!='India'] #removing the India's row
data=data[data['TRU']=='Total']
#Only keeping total and excluding the rural and urban rows
states_group=data[data['Level']=='State']
states_group
之后,这里是我要关注的主要代码-
literacy_rate=[]
total_state_pop=0
total_literate_pop=0
for key,group in states_group.iterrows():
total_state_pop+=states_group['TOT_P']
total_literate_pop+=states_group['P_LIT']
total_literate_pop+=states_group['F_LIT']
rate=(total_literate_pop/total_state_pop)*100
literacy_rate.append((states_group['Name'],rate))
print(literacy_rate)
但我得到的结果是——
(3 JAMMU & KASHMIR
72 HIMACHAL PRADESH
111 PUNJAB
174 CHANDIGARH
180 UTTARAKHAND
222 HARYANA
288 NCT OF DELHI
318 RAJASTHAN
420 UTTAR PRADESH
636 BIHAR
753 SIKKIM
768 MANIPUR
798 MIZORAM
825 TRIPURA
840 MEGHALAYA
864 ASSAM
948 WEST BENGAL
1008 JHARKHAND
1083 ODISHA
1176 CHHATTISGARH
1233 MADHYA PRADESH
1386 GUJARAT
1467 DAMAN & DIU
1476 DADRA & NAGAR HAVELI
1482 MAHARASHTRA
1590 ANDHRA PRADESH
1662 KARNATAKA
1755 GOA
1764 KERALA
1809 TAMIL NADU
1908 PUDUCHERRY
Name: Name, dtype: object, 3 85.484832
72 99.946393
111 80.810862
174 93.793637
180 89.689123
222 79.608418
288 97.531743
318 67.745833
420 69.971651
636 52.937273
753 98.691424
768 96.236438
798 109.113300
825 116.065370
840 84.108326
864 96.451609
948 87.437511
1008 63.211190
1083 85.260257
1176 85.104889
1233 78.055310
1386 99.236215
1467 121.848465
1476 112.301972
1482 100.968386
1590 79.671587
1662 81.400129
1755 110.110417
1764 120.140132
1809 94.529868
1908 101.165414
dtype: float64), (3 JAMMU & KASHMIR
72 HIMACHAL PRADESH
111 PUNJAB
174 CHANDIGARH
180 UTTARAKHAND
222 HARYANA
288 NCT OF DELHI
318 RAJASTHAN
420 UTTAR PRADESH
636 BIHAR
753 SIKKIM
768 MANIPUR
798 MIZORAM
825 TRIPURA
840 MEGHALAYA
864 ASSAM
948 WEST BENGAL
1008 JHARKHAND
1083 ODISHA
1176 CHHATTISGARH
1233 MADHYA PRADESH
1386 GUJARAT
1467 DAMAN & DIU
1476 DADRA & NAGAR HAVELI
1482 MAHARASHTRA
1590 ANDHRA PRADESH
1662 KARNATAKA
1755 GOA
1764 KERALA
1809 TAMIL NADU
1908 PUDUCHERRY
Name: Name, dtype: object, 3 85.484832
72 99.946393
111 80.810862
174 93.793637
180 89.689123
222 79.608418
288 97.531743
318 67.745833
420 69.971651
636 52.937273
753 98.691424
768 96.236438
798 109.113300
825 116.065370
840 84.108326
864 96.451609
948 87.437511
1008 63.211190
1083 85.260257
1176 85.104889
1233 78.055310
1386 99.236215
1467 121.848465
1476 112.301972
1482 100.968386
1590 79.671587
1662 81.400129
1755 110.110417
1764 120.140132
1809 94.529868
1908 101.165414
dtype: float64), (3 JAMMU & KASHMIR
72 HIMACHAL PRADESH
111 PUNJAB
174 CHANDIGARH
180 UTTARAKHAND
222 HARYANA
288 NCT OF DELHI
318 RAJASTHAN
420 UTTAR PRADESH
636 BIHAR
753 SIKKIM
768 MANIPUR
798 MIZORAM
825 TRIPURA
840 MEGHALAYA
864 ASSAM
948 WEST BENGAL
1008 JHARKHAND
1083 ODISHA
1176 CHHATTISGARH
1233 MADHYA PRADESH
1386 GUJARAT
1467 DAMAN & DIU
1476 DADRA & NAGAR HAVELI
1482 MAHARASHTRA
1590 ANDHRA PRADESH
1662 KARNATAKA
1755 GOA
1764 KERALA
1809 TAMIL NADU
1908 PUDUCHERRY
Name: Name, dtype: object, 3 85.484832
72 99.946393
111 80.810862
174 93.793637
180 89.689123
222 79.608418
288 97.531743
318 67.745833
420 69.971651
636 52.937273
753 98.691424
768 96.236438
798 109.113300
825 116.065370
840 84.108326
864 96.451609
948 87.437511
1008 63.211190
1083 85.260257
1176 85.104889
1233 78.055310
1386 99.236215
1467 121.848465
1476 112.301972
未来的日子会更漫长 这是link整个数据集 我哪里做错了?提前谢谢
在
for
循环中,如何将每个states_group
更改为group
或者,使用.iterrows()
进行for
循环没有任何意义尽可能避免迭代,因为这是熊猫的反模式good read
输出:
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