Creating tuples from columns of Dataframe
Question
I have a data set as such - and I want to create a List of tuples as
(Name_of_State , Literacy_rate)
(JAMMU&KASHMIR, 89.78) #example
I had to do a bit of cleaning up,removing districts and just keeping states.
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
After that,here is my main code to focus -
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)
But the output I get is as-
(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
And its more long ahead Here is the link whole data set Where am I getting wrong? Thanks in advance.
2 answers
solution1
4 ACCPTED 2020-12-02 06:06:26
Avoid iteration if possible as it's an anti pattern for pandas. good read
import pandas as pd
data = pd.read_excel('state_dist_sc.xls')
data=data[data['Name']!='India']
data=data[data['TRU']=='Total']
states_group=data[data['Level']=='State']
#create a copy of data on which we will be calculating literacy rate.
states_group = states_group.copy()
#Calculate litracy rate using vector formula which is faster and more.
states_group['literacy_rate'] = 100*(states_group['P_LIT'] + states_group['F_LIT'])/states_group['TOT_P']
# use to_records to get list of tuples
ans = states_group[['Name','literacy_rate']].to_records(index=False)
ans
Output:
rec.array([('JAMMU & KASHMIR', 85.48483174),
('HIMACHAL PRADESH', 99.94639301), ('PUNJAB', 80.81086172),
('CHANDIGARH', 93.79363692), ('UTTARAKHAND', 89.68912284),
('HARYANA', 79.60841792), ('NCT OF DELHI', 97.53174349),
('RAJASTHAN', 67.74583313), ('UTTAR PRADESH', 69.97165068),
('BIHAR', 52.93727261), ('SIKKIM', 98.69142352),
('MANIPUR', 96.23643761), ('MIZORAM', 109.11330049),
('TRIPURA', 116.06537002), ('MEGHALAYA', 84.10832613),
('ASSAM', 96.45160871), ('WEST BENGAL', 87.43751069),
('JHARKHAND', 63.21118996), ('ODISHA', 85.26025661),
('CHHATTISGARH', 85.10488906),
('MADHYA PRADESH', 78.05530967), ('GUJARAT', 99.23621537),
('DAMAN & DIU', 121.84846506),
('DADRA & NAGAR HAVELI', 112.3019722 ),
('MAHARASHTRA', 100.96838647),
('ANDHRA PRADESH', 79.67158709), ('KARNATAKA', 81.40012899),
('GOA', 110.11041691), ('KERALA', 120.14013153),
('TAMIL NADU', 94.529868 ), ('PUDUCHERRY', 101.16541449)],
dtype=[('Name', 'O'), ('literacy_rate', '<f8')])
solution2
2 2020-12-02 06:02:57
in the for loop, how about chaging every states_group to group or there will be no meaning of doing for loop with .iterrows()
literacy_rate=[]
total_state_pop=0
total_literate_pop=0
for key,group in states_group.iterrows():
total_state_pop+=group['TOT_P']
total_literate_pop+=group['P_LIT']
total_literate_pop+=group['F_LIT']
rate=(total_literate_pop/total_state_pop)*100
literacy_rate.append((group['Name'],rate))
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