emp_master= {"Emp_Name": ["Adam", "Mark", "Deb", "Antony", "Joseph"],
"Title": ["Manager", "Team Lead", "Member", "Member", "Member"],
"Attendence%": [70, 82, 70, 95, 99],
"BMI": [35, 34, 16.5, 20, 22] }
import numpy as np
import pandas as pd
empmaster_table = pd.DataFrame(emp_master)
print(empmaster_table)
Emp_Name Title Attendence% BMI 0 Adam Manager 70 35.0 1 Mark Team Lead 82 34.0 2 Deb Member 70 16.5 3 Antony Member 95 20.0 4 Joseph Member 99 22.0
empmaster_table.index=["E001", "E028", "E392", "E009", "E983"]
print(empmaster_table)
Emp_Name Title Attendence% BMI E001 Adam Manager 70 35.0 E028 Mark Team Lead 82 34.0 E392 Deb Member 70 16.5 E009 Antony Member 95 20.0 E983 Joseph Member 99 22.0
empmaster_table.index.name='Emp No'
print(empmaster_table)
Emp_Name Title Attendence% BMI Emp No E001 Adam Manager 70 35.0 E028 Mark Team Lead 82 34.0 E392 Deb Member 70 16.5 E009 Antony Member 95 20.0 E983 Joseph Member 99 22.0
DS=pd.read_excel("F:/2019 GB Python/GB Pandas Data Frame.xls")
DS.head()
S.No. | Unnamed: 1 | PurType | PayVal | WaitList | Process | WaitTime | ApproveTime | Disbursement Time | Overall | Day of week | |
---|---|---|---|---|---|---|---|---|---|---|---|
0 | 1 | NaN | A | 155.0 | 9 | 2.0 | 5.5 | 6.5 | 5.0 | 25 | Monday |
1 | 2 | NaN | B | 175.0 | 13 | 1.2 | 5.6 | 9.5 | 6.5 | 55 | Wednesday |
2 | 3 | NaN | C | 98.0 | 10 | 2.3 | 6.3 | 6.3 | 6.0 | 40 | Friday |
3 | 4 | NaN | D | 125.0 | 8 | 2.0 | 4.9 | 5.4 | 5.5 | 35 | Monday |
4 | 5 | NaN | B | 450.0 | 15 | 1.5 | 7.2 | 10 | 8.0 | 65 | Monday |
DS=pd.read_excel("F:/2019 GB Python/GB Pandas Data Frame.xls", index_col=0)
print(DS.index.name)
S.No.
DS.shape
(90, 10)
DS.dtypes
Unnamed: 1 float64 PurType object PayVal float64 WaitList int64 Process float64 WaitTime float64 ApproveTime object Disbursement Time float64 Overall int64 Day of week object dtype: object
DS.isna().any()
Unnamed: 1 True PurType False PayVal True WaitList False Process False WaitTime False ApproveTime False Disbursement Time False Overall False Day of week False dtype: bool
DS1=DS.dropna(axis=1)
DS1.head()
PurType | WaitList | Process | WaitTime | ApproveTime | Disbursement Time | Overall | Day of week | |
---|---|---|---|---|---|---|---|---|
S.No. | ||||||||
1 | A | 9 | 2.0 | 5.5 | 6.5 | 5.0 | 25 | Monday |
2 | B | 13 | 1.2 | 5.6 | 9.5 | 6.5 | 55 | Wednesday |
3 | C | 10 | 2.3 | 6.3 | 6.3 | 6.0 | 40 | Friday |
4 | D | 8 | 2.0 | 4.9 | 5.4 | 5.5 | 35 | Monday |
5 | B | 15 | 1.5 | 7.2 | 10 | 8.0 | 65 | Monday |
DS1.shape
(90, 8)
DS.dropna(axis=1, inplace=True)
DS
PurType | WaitList | Process | WaitTime | ApproveTime | Disbursement Time | Overall | Day of week | |
---|---|---|---|---|---|---|---|---|
S.No. | ||||||||
1 | A | 9 | 2.0 | 5.5 | 6.5 | 5.0 | 25 | Monday |
2 | B | 13 | 1.2 | 5.6 | 9.5 | 6.5 | 55 | Wednesday |
3 | C | 10 | 2.3 | 6.3 | 6.3 | 6.0 | 40 | Friday |
4 | D | 8 | 2.0 | 4.9 | 5.4 | 5.5 | 35 | Monday |
5 | B | 15 | 1.5 | 7.2 | 10 | 8.0 | 65 | Monday |
6 | B | 18 | 2.4 | 8.5 | 12 | 8.0 | 75 | Tuesday |
7 | A | 9 | 2.5 | 6.0 | 7 | 4.5 | 22 | Monday |
8 | A | 8 | 4.0 | 4.6 | 5.6 | 4.0 | 35 | Tuesday |
9 | B | 20 | 3.0 | 11.0 | 14 | 8.0 | 88 | Wednesday |
10 | C | 10 | 4.0 | 5.6 | 5.6 | 6.7 | 52 | Monday |
11 | D | 7 | 2.4 | 3.5 | 4 | 6.5 | 26 | Tuesday |
12 | A | 6 | 3.5 | 3.5 | 4.5 | 5.0 | 28 | Monday |
13 | B | 12 | 4.2 | 7.0 | 10 | 8.0 | 56 | Wednesday |
14 | A | 5 | 3.0 | 4.1 | 5 | 5.4 | 37 | Monday |
15 | D | 10 | 4.2 | 6.0 | 6.5 | 5.6 | 38 | Wednesday |
16 | D | 14 | 1.3 | 7.2 | 8 | 7.3 | 45 | Monday |
17 | B | 9 | 1.9 | 6.8 | 9.5 | 6.5 | 54 | Wednesday |
18 | B | 14 | 1.3 | 5.4 | 8.3 | 8.0 | 49 | Friday |
19 | D | 14 | 1.6 | 7.0 | 7.6 | 8.0 | 47 | Friday |
20 | B | 9 | 1.3 | 5.6 | 8.3 | 6.0 | 35 | Monday |
21 | B | 15 | 2.1 | 6.0 | 9.8 | 8.3 | 55 | Tuesday |
22 | A | 7 | 1.8 | 4.3 | 5 | 6.0 | 0 | Wednesday |
23 | C | 16 | 2.1 | 7.8 | 7.8 | 7.0 | 48 | Wednesday |
24 | C | 3 | 2.0 | 5.6 | 5.6 | 6.5 | 37 | Wednesday |
25 | D | 13 | 2.3 | 7.5 | 8 | 8.5 | 45 | Monday |
26 | A | 9 | 2.5 | 6.0 | 6.8 | 5.0 | 34 | Thursday |
27 | C | 11 | 2.6 | 7.4 | 7.4 | 4.5 | 43 | Monday |
28 | B | 17 | 1.2 | 9.5 | 14.5 | 8.0 | 85 | Tuesday |
29 | C | 9 | 2.3 | 8.0 | 8 | 9.0 | 38 | Wednesday |
30 | B | 13 | 3.4 | 6.8 | 9.5 | 6.0 | 53 | Friday |
... | ... | ... | ... | ... | ... | ... | ... | ... |
61 | C | 13 | 2.0 | 8.0 | 8 | 8.0 | 47 | Wednesday |
62 | D | 12 | 2.3 | 6.5 | 7 | 9.0 | 48 | Wednesday |
63 | D | 14 | 2.3 | 11.0 | 12 | 8.0 | 54 | Friday |
64 | A | 8 | 2.0 | 5.0 | 5 | 6.5 | 29 | Friday |
65 | C | 8 | 1.7 | 6.5 | 6.5 | 7.8 | 33 | Monday |
66 | D | 12 | 1.5 | 8.0 | 8.5 | 7.0 | 46 | Tuesday |
67 | D | 10 | 3.0 | 5.0 | 5.6 | 7.0 | 46 | Tuesday |
68 | A | 6 | 2.5 | 4.8 | 5.6 | 5.0 | 27 | Tuesday |
69 | D | 11 | 2.4 | 10.5 | 11.2 | 8.0 | 56 | Tuesday |
70 | D | 13 | 1.8 | 8.0 | 9 | 7.0 | 48 | Wednesday |
71 | A | 7 | 1.9 | 5.4 | 5.4 | 6.0 | 23 | Friday |
72 | B | 9 | 2.0 | 5.5 | 7 | 9.0 | 34 | Monday |
73 | A | 11 | 2.3 | 4.0 | 4 | 5.0 | 23 | Monday |
74 | B | 10 | 2.2 | 3.0 | 4 | 6.5 | 24 | Monday |
75 | D | 8 | 1.7 | 6.0 | 6 | 6.5 | 29 | Wednesday |
76 | C | 12 | 2.2 | 5.0 | 5 | 5.0 | 22 | Thursday |
77 | B | 6 | 2.1 | 8.5 | 11 | 8.0 | 58 | Wednesday |
78 | D | 10 | 1.8 | 6.0 | 6.5 | 6.0 | 33 | Wednesday |
79 | B | 9 | 1.5 | 5.5 | 7 | 7.0 | 34 | Monday |
80 | C | 10 | 2.4 | 6.5 | 6.5 | 7.0 | 31 | Monday |
81 | A | 8 | 2.1 | 6.0 | 6.5 | 5.0 | 23 | Monday |
82 | D | 6 | 1.9 | 3.0 | 3 | 4.0 | 18 | Monday |
83 | D | 8 | 2.0 | 5.4 | 5.4 | 8.0 | 31 | Friday |
84 | A | 7 | 5.4 | 6.4 | 6.4 | 7.0 | 28 | Wednesday |
85 | D | 14 | 3.2 | 6.5 | 6.5 | 9.0 | 51 | Tuesday |
86 | B | 6 | 2.3 | 8.5 | 11 | 8.0 | 51 | Tuesday |
87 | C | 5 | 2.0 | 3.5 | 3.5 | 3.0 | 18 | Monday |
88 | A | 14 | 3.0 | 4.2 | 4.8 | 5.0 | 25 | Monday |
89 | D | 10 | 2.0 | 7.5 | 8 | 8.0 | 57 | Tuesday |
90 | B | 5 | 2.0 | 6.5 | 8 | 9.0 | 38 | Thursday |
90 rows × 8 columns
DS=pd.read_excel("F:/2019 GB Python/GB Pandas Data Frame.xls", index_col=0)
DS1=DS.drop("Unnamed: 1", axis=1)
DS1
PurType | PayVal | WaitList | Process | WaitTime | ApproveTime | Disbursement Time | Overall | Day of week | |
---|---|---|---|---|---|---|---|---|---|
S.No. | |||||||||
1 | A | 155.0 | 9 | 2.0 | 5.5 | 6.5 | 5.0 | 25 | Monday |
2 | B | 175.0 | 13 | 1.2 | 5.6 | 9.5 | 6.5 | 55 | Wednesday |
3 | C | 98.0 | 10 | 2.3 | 6.3 | 6.3 | 6.0 | 40 | Friday |
4 | D | 125.0 | 8 | 2.0 | 4.9 | 5.4 | 5.5 | 35 | Monday |
5 | B | 450.0 | 15 | 1.5 | 7.2 | 10 | 8.0 | 65 | Monday |
6 | B | 350.0 | 18 | 2.4 | 8.5 | 12 | 8.0 | 75 | Tuesday |
7 | A | 176.0 | 9 | 2.5 | 6.0 | 7 | 4.5 | 22 | Monday |
8 | A | 154.0 | 8 | 4.0 | 4.6 | 5.6 | 4.0 | 35 | Tuesday |
9 | B | 134.0 | 20 | 3.0 | 11.0 | 14 | 8.0 | 88 | Wednesday |
10 | C | 235.0 | 10 | 4.0 | 5.6 | 5.6 | 6.7 | 52 | Monday |
11 | D | 245.0 | 7 | 2.4 | 3.5 | 4 | 6.5 | 26 | Tuesday |
12 | A | 123.0 | 6 | 3.5 | 3.5 | 4.5 | 5.0 | 28 | Monday |
13 | B | NaN | 12 | 4.2 | 7.0 | 10 | 8.0 | 56 | Wednesday |
14 | A | 180.0 | 5 | 3.0 | 4.1 | 5 | 5.4 | 37 | Monday |
15 | D | 210.0 | 10 | 4.2 | 6.0 | 6.5 | 5.6 | 38 | Wednesday |
16 | D | 340.0 | 14 | 1.3 | 7.2 | 8 | 7.3 | 45 | Monday |
17 | B | 542.0 | 9 | 1.9 | 6.8 | 9.5 | 6.5 | 54 | Wednesday |
18 | B | 143.0 | 14 | 1.3 | 5.4 | 8.3 | 8.0 | 49 | Friday |
19 | D | 176.0 | 14 | 1.6 | 7.0 | 7.6 | 8.0 | 47 | Friday |
20 | B | 154.0 | 9 | 1.3 | 5.6 | 8.3 | 6.0 | 35 | Monday |
21 | B | 234.0 | 15 | 2.1 | 6.0 | 9.8 | 8.3 | 55 | Tuesday |
22 | A | 159.0 | 7 | 1.8 | 4.3 | 5 | 6.0 | 0 | Wednesday |
23 | C | 245.0 | 16 | 2.1 | 7.8 | 7.8 | 7.0 | 48 | Wednesday |
24 | C | 345.0 | 3 | 2.0 | 5.6 | 5.6 | 6.5 | 37 | Wednesday |
25 | D | 450.0 | 13 | 2.3 | 7.5 | 8 | 8.5 | 45 | Monday |
26 | A | 187.0 | 9 | 2.5 | 6.0 | 6.8 | 5.0 | 34 | Thursday |
27 | C | 146.0 | 11 | 2.6 | 7.4 | 7.4 | 4.5 | 43 | Monday |
28 | B | NaN | 17 | 1.2 | 9.5 | 14.5 | 8.0 | 85 | Tuesday |
29 | C | 453.0 | 9 | 2.3 | 8.0 | 8 | 9.0 | 38 | Wednesday |
30 | B | 245.0 | 13 | 3.4 | 6.8 | 9.5 | 6.0 | 53 | Friday |
... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
61 | C | 543.0 | 13 | 2.0 | 8.0 | 8 | 8.0 | 47 | Wednesday |
62 | D | 123.0 | 12 | 2.3 | 6.5 | 7 | 9.0 | 48 | Wednesday |
63 | D | 100.0 | 14 | 2.3 | 11.0 | 12 | 8.0 | 54 | Friday |
64 | A | 150.0 | 8 | 2.0 | 5.0 | 5 | 6.5 | 29 | Friday |
65 | C | 123.0 | 8 | 1.7 | 6.5 | 6.5 | 7.8 | 33 | Monday |
66 | D | 246.0 | 12 | 1.5 | 8.0 | 8.5 | 7.0 | 46 | Tuesday |
67 | D | 234.0 | 10 | 3.0 | 5.0 | 5.6 | 7.0 | 46 | Tuesday |
68 | A | 120.0 | 6 | 2.5 | 4.8 | 5.6 | 5.0 | 27 | Tuesday |
69 | D | 187.0 | 11 | 2.4 | 10.5 | 11.2 | 8.0 | 56 | Tuesday |
70 | D | 146.0 | 13 | 1.8 | 8.0 | 9 | 7.0 | 48 | Wednesday |
71 | A | 203.0 | 7 | 1.9 | 5.4 | 5.4 | 6.0 | 23 | Friday |
72 | B | 210.0 | 9 | 2.0 | 5.5 | 7 | 9.0 | 34 | Monday |
73 | A | 230.0 | 11 | 2.3 | 4.0 | 4 | 5.0 | 23 | Monday |
74 | B | 330.0 | 10 | 2.2 | 3.0 | 4 | 6.5 | 24 | Monday |
75 | D | 230.0 | 8 | 1.7 | 6.0 | 6 | 6.5 | 29 | Wednesday |
76 | C | 340.0 | 12 | 2.2 | 5.0 | 5 | 5.0 | 22 | Thursday |
77 | B | 432.0 | 6 | 2.1 | 8.5 | 11 | 8.0 | 58 | Wednesday |
78 | D | 134.0 | 10 | 1.8 | 6.0 | 6.5 | 6.0 | 33 | Wednesday |
79 | B | 165.0 | 9 | 1.5 | 5.5 | 7 | 7.0 | 34 | Monday |
80 | C | 176.0 | 10 | 2.4 | 6.5 | 6.5 | 7.0 | 31 | Monday |
81 | A | 231.0 | 8 | 2.1 | 6.0 | 6.5 | 5.0 | 23 | Monday |
82 | D | 320.0 | 6 | 1.9 | 3.0 | 3 | 4.0 | 18 | Monday |
83 | D | 156.0 | 8 | 2.0 | 5.4 | 5.4 | 8.0 | 31 | Friday |
84 | A | 546.0 | 7 | 5.4 | 6.4 | 6.4 | 7.0 | 28 | Wednesday |
85 | D | 324.0 | 14 | 3.2 | 6.5 | 6.5 | 9.0 | 51 | Tuesday |
86 | B | 234.0 | 6 | 2.3 | 8.5 | 11 | 8.0 | 51 | Tuesday |
87 | C | 121.0 | 5 | 2.0 | 3.5 | 3.5 | 3.0 | 18 | Monday |
88 | A | 187.0 | 14 | 3.0 | 4.2 | 4.8 | 5.0 | 25 | Monday |
89 | D | 120.0 | 10 | 2.0 | 7.5 | 8 | 8.0 | 57 | Tuesday |
90 | B | 140.0 | 5 | 2.0 | 6.5 | 8 | 9.0 | 38 | Thursday |
90 rows × 9 columns
DS1.loc[(DS1==0).any(axis=1)]
PurType | PayVal | WaitList | Process | WaitTime | ApproveTime | Disbursement Time | Overall | Day of week | |
---|---|---|---|---|---|---|---|---|---|
S.No. | |||||||||
22 | A | 159.0 | 7 | 1.8 | 4.3 | 5 | 6.0 | 0 | Wednesday |
33 | C | 98.0 | 14 | 1.5 | 6.3 | 6.3 | 6.0 | 0 | Tuesday |
35 | A | 231.0 | 9 | 1.7 | 5.0 | 5.6 | 6.9 | 0 | Monday |
DS2=DS1[DS1[' Overall'] !=0]
DS2
PurType | PayVal | WaitList | Process | WaitTime | ApproveTime | Disbursement Time | Overall | Day of week | |
---|---|---|---|---|---|---|---|---|---|
S.No. | |||||||||
1 | A | 155.0 | 9 | 2.0 | 5.5 | 6.5 | 5.0 | 25 | Monday |
2 | B | 175.0 | 13 | 1.2 | 5.6 | 9.5 | 6.5 | 55 | Wednesday |
3 | C | 98.0 | 10 | 2.3 | 6.3 | 6.3 | 6.0 | 40 | Friday |
4 | D | 125.0 | 8 | 2.0 | 4.9 | 5.4 | 5.5 | 35 | Monday |
5 | B | 450.0 | 15 | 1.5 | 7.2 | 10 | 8.0 | 65 | Monday |
6 | B | 350.0 | 18 | 2.4 | 8.5 | 12 | 8.0 | 75 | Tuesday |
7 | A | 176.0 | 9 | 2.5 | 6.0 | 7 | 4.5 | 22 | Monday |
8 | A | 154.0 | 8 | 4.0 | 4.6 | 5.6 | 4.0 | 35 | Tuesday |
9 | B | 134.0 | 20 | 3.0 | 11.0 | 14 | 8.0 | 88 | Wednesday |
10 | C | 235.0 | 10 | 4.0 | 5.6 | 5.6 | 6.7 | 52 | Monday |
11 | D | 245.0 | 7 | 2.4 | 3.5 | 4 | 6.5 | 26 | Tuesday |
12 | A | 123.0 | 6 | 3.5 | 3.5 | 4.5 | 5.0 | 28 | Monday |
13 | B | NaN | 12 | 4.2 | 7.0 | 10 | 8.0 | 56 | Wednesday |
14 | A | 180.0 | 5 | 3.0 | 4.1 | 5 | 5.4 | 37 | Monday |
15 | D | 210.0 | 10 | 4.2 | 6.0 | 6.5 | 5.6 | 38 | Wednesday |
16 | D | 340.0 | 14 | 1.3 | 7.2 | 8 | 7.3 | 45 | Monday |
17 | B | 542.0 | 9 | 1.9 | 6.8 | 9.5 | 6.5 | 54 | Wednesday |
18 | B | 143.0 | 14 | 1.3 | 5.4 | 8.3 | 8.0 | 49 | Friday |
19 | D | 176.0 | 14 | 1.6 | 7.0 | 7.6 | 8.0 | 47 | Friday |
20 | B | 154.0 | 9 | 1.3 | 5.6 | 8.3 | 6.0 | 35 | Monday |
21 | B | 234.0 | 15 | 2.1 | 6.0 | 9.8 | 8.3 | 55 | Tuesday |
23 | C | 245.0 | 16 | 2.1 | 7.8 | 7.8 | 7.0 | 48 | Wednesday |
24 | C | 345.0 | 3 | 2.0 | 5.6 | 5.6 | 6.5 | 37 | Wednesday |
25 | D | 450.0 | 13 | 2.3 | 7.5 | 8 | 8.5 | 45 | Monday |
26 | A | 187.0 | 9 | 2.5 | 6.0 | 6.8 | 5.0 | 34 | Thursday |
27 | C | 146.0 | 11 | 2.6 | 7.4 | 7.4 | 4.5 | 43 | Monday |
28 | B | NaN | 17 | 1.2 | 9.5 | 14.5 | 8.0 | 85 | Tuesday |
29 | C | 453.0 | 9 | 2.3 | 8.0 | 8 | 9.0 | 38 | Wednesday |
30 | B | 245.0 | 13 | 3.4 | 6.8 | 9.5 | 6.0 | 53 | Friday |
31 | D | 121.0 | 12 | 2.0 | 6.0 | - | 7.0 | 50 | Monday |
... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
61 | C | 543.0 | 13 | 2.0 | 8.0 | 8 | 8.0 | 47 | Wednesday |
62 | D | 123.0 | 12 | 2.3 | 6.5 | 7 | 9.0 | 48 | Wednesday |
63 | D | 100.0 | 14 | 2.3 | 11.0 | 12 | 8.0 | 54 | Friday |
64 | A | 150.0 | 8 | 2.0 | 5.0 | 5 | 6.5 | 29 | Friday |
65 | C | 123.0 | 8 | 1.7 | 6.5 | 6.5 | 7.8 | 33 | Monday |
66 | D | 246.0 | 12 | 1.5 | 8.0 | 8.5 | 7.0 | 46 | Tuesday |
67 | D | 234.0 | 10 | 3.0 | 5.0 | 5.6 | 7.0 | 46 | Tuesday |
68 | A | 120.0 | 6 | 2.5 | 4.8 | 5.6 | 5.0 | 27 | Tuesday |
69 | D | 187.0 | 11 | 2.4 | 10.5 | 11.2 | 8.0 | 56 | Tuesday |
70 | D | 146.0 | 13 | 1.8 | 8.0 | 9 | 7.0 | 48 | Wednesday |
71 | A | 203.0 | 7 | 1.9 | 5.4 | 5.4 | 6.0 | 23 | Friday |
72 | B | 210.0 | 9 | 2.0 | 5.5 | 7 | 9.0 | 34 | Monday |
73 | A | 230.0 | 11 | 2.3 | 4.0 | 4 | 5.0 | 23 | Monday |
74 | B | 330.0 | 10 | 2.2 | 3.0 | 4 | 6.5 | 24 | Monday |
75 | D | 230.0 | 8 | 1.7 | 6.0 | 6 | 6.5 | 29 | Wednesday |
76 | C | 340.0 | 12 | 2.2 | 5.0 | 5 | 5.0 | 22 | Thursday |
77 | B | 432.0 | 6 | 2.1 | 8.5 | 11 | 8.0 | 58 | Wednesday |
78 | D | 134.0 | 10 | 1.8 | 6.0 | 6.5 | 6.0 | 33 | Wednesday |
79 | B | 165.0 | 9 | 1.5 | 5.5 | 7 | 7.0 | 34 | Monday |
80 | C | 176.0 | 10 | 2.4 | 6.5 | 6.5 | 7.0 | 31 | Monday |
81 | A | 231.0 | 8 | 2.1 | 6.0 | 6.5 | 5.0 | 23 | Monday |
82 | D | 320.0 | 6 | 1.9 | 3.0 | 3 | 4.0 | 18 | Monday |
83 | D | 156.0 | 8 | 2.0 | 5.4 | 5.4 | 8.0 | 31 | Friday |
84 | A | 546.0 | 7 | 5.4 | 6.4 | 6.4 | 7.0 | 28 | Wednesday |
85 | D | 324.0 | 14 | 3.2 | 6.5 | 6.5 | 9.0 | 51 | Tuesday |
86 | B | 234.0 | 6 | 2.3 | 8.5 | 11 | 8.0 | 51 | Tuesday |
87 | C | 121.0 | 5 | 2.0 | 3.5 | 3.5 | 3.0 | 18 | Monday |
88 | A | 187.0 | 14 | 3.0 | 4.2 | 4.8 | 5.0 | 25 | Monday |
89 | D | 120.0 | 10 | 2.0 | 7.5 | 8 | 8.0 | 57 | Tuesday |
90 | B | 140.0 | 5 | 2.0 | 6.5 | 8 | 9.0 | 38 | Thursday |
87 rows × 9 columns
DS2=DS1[DS1.Overall !=0]