I have a dataframe like
import pandas as pd
student_dict = {
"ID":[101,102,103,104,105,101,102,103,104,105,106,107],
"Student":["AAA","BBB","CCC","DDD","EEE","AAA","BBB","CCC","DDD","EEE","YYY","ZZZ"],
"Mark":[50,100,99,60,80,50,100,99,60,80,100,80],
"Address":["St.AAA","St.BBB","St.CCC","St.DDD","St.EEE","St.AAA","St.BBB","St.CCC","St.DDD","St.EEE","St.AYE","St.ZZZ"],
"PhoneNo":[1111111111,2222222222,3333333333,4444444444,5555555555,1111111111,2222222222,3333333333,4444444444,5555555555,6666666666,7777777777]
}
df = pd.DataFrame(student_dict)
#print(df)
rmv = df.drop_duplicates()
print(rmv)
ID Student Mark Address PhoneNo
0 101 AAA 50 St.AAA 1111111111
1 102 BBB 100 St.BBB 2222222222
2 103 CCC 99 St.CCC 3333333333
3 104 DDD 60 St.DDD 4444444444
4 105 EEE 80 St.EEE 5555555555
5 101 AAA 50 St.AAA 1111111111
6 102 BBB 100 St.BBB 2222222222
7 103 CCC 99 St.CCC 3333333333
8 104 DDD 60 St.DDD 4444444444
9 105 EEE 80 St.EEE 5555555555
10 106 YYY 100 St.AYE 6666666666
11 107 ZZZ 80 St.ZZZ 7777777777
Most of the rows are duplicates, except ID 106 & ID 107
I tried df.drop_duplicates()
ID Student Mark Address PhoneNo
0 101 AAA 50 St.AAA 1111111111
1 102 BBB 100 St.BBB 2222222222
2 103 CCC 99 St.CCC 3333333333
3 104 DDD 60 St.DDD 4444444444
4 105 EEE 80 St.EEE 5555555555
10 106 YYY 100 St.AYE 6666666666
11 107 ZZZ 80 St.ZZZ 7777777777
it removed the duplicates.
But I need only the odd rows like,
ID Student Mark Address PhoneNo
106 YYY 100 St.AYE 6666666666
107 ZZZ 80 St.ZZZ 7777777777
is there any way to find the odd rows from a dataframe without passing any values(like ID,Student... from the student_dict) Or is there any inbuild function to find these odd rows?
