Mixing
Convert the continuous values of grades into classes
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I have the following dataframe int_stdf (Fig. 1) and I need to do the following:
Consider the values in G1, G2 and G3 being >= 10 as pass(1) and < 10 as fail(0) and encode them into binary values. Print head of dataframe to check the values.
G1 G2 G3
number
0 5 6 6
1 5 5 6
2 7 8 10
3 15 14 15
4 6 10 10
5 15 15 15
Fig. 1
G1 G2 G3
number
0 0 0 0
1 0 0 0
2 0 0 1
3 1 1 1
4 0 1 1
5 1 1 1
Fig. 2
So I should get something like (Fig. 2):
Please advise how to achieve this.
python pandas
edited Jan 3 at 16:30
DYZ
28.4k62352
asked Jan 3 at 16:29
Mohammad Amir AshraffMohammad Amir Ashraff
254
add a comment |
I have the following dataframe int_stdf (Fig. 1) and I need to do the following:
Consider the values in G1, G2 and G3 being >= 10 as pass(1) and < 10 as fail(0) and encode them into binary values. Print head of dataframe to check the values.
G1 G2 G3
number
0 5 6 6
1 5 5 6
2 7 8 10
3 15 14 15
4 6 10 10
5 15 15 15
Fig. 1
G1 G2 G3
number
0 0 0 0
1 0 0 0
2 0 0 1
3 1 1 1
4 0 1 1
5 1 1 1
Fig. 2
So I should get something like (Fig. 2):
Please advise how to achieve this.
python pandas
edited Jan 3 at 16:30
DYZ
28.4k62352
asked Jan 3 at 16:29
Mohammad Amir AshraffMohammad Amir Ashraff
254
5
df.ge(10).astype(int)
– ALollz
Jan 3 at 16:31
3
Sounds like a homework assignment of some sort. What have you done? Please post your code and explain why you are not happy with it.
– DYZ
Jan 3 at 16:31
add a comment |
I have the following dataframe int_stdf (Fig. 1) and I need to do the following:
Consider the values in G1, G2 and G3 being >= 10 as pass(1) and < 10 as fail(0) and encode them into binary values. Print head of dataframe to check the values.
G1 G2 G3
number
0 5 6 6
1 5 5 6
2 7 8 10
3 15 14 15
4 6 10 10
5 15 15 15
Fig. 1
G1 G2 G3
number
0 0 0 0
1 0 0 0
2 0 0 1
3 1 1 1
4 0 1 1
5 1 1 1
Fig. 2
So I should get something like (Fig. 2):
Please advise how to achieve this.
python pandas
edited Jan 3 at 16:30
DYZ
28.4k62352
asked Jan 3 at 16:29
Mohammad Amir AshraffMohammad Amir Ashraff
254
I have the following dataframe int_stdf (Fig. 1) and I need to do the following:
Consider the values in G1, G2 and G3 being >= 10 as pass(1) and < 10 as fail(0) and encode them into binary values. Print head of dataframe to check the values.
G1 G2 G3
number
0 5 6 6
1 5 5 6
2 7 8 10
3 15 14 15
4 6 10 10
5 15 15 15
Fig. 1
G1 G2 G3
number
0 0 0 0
1 0 0 0
2 0 0 1
3 1 1 1
4 0 1 1
5 1 1 1
Fig. 2
So I should get something like (Fig. 2):
Please advise how to achieve this.
python pandas
python pandas
edited Jan 3 at 16:30
DYZ
28.4k62352
asked Jan 3 at 16:29
Mohammad Amir AshraffMohammad Amir Ashraff
254
edited Jan 3 at 16:30
DYZ
28.4k62352
asked Jan 3 at 16:29
Mohammad Amir AshraffMohammad Amir Ashraff
254
edited Jan 3 at 16:30
DYZ
28.4k62352
edited Jan 3 at 16:30
DYZ
28.4k62352
edited Jan 3 at 16:30
DYZ
28.4k62352
28.4k62352
asked Jan 3 at 16:29
Mohammad Amir AshraffMohammad Amir Ashraff
254
asked Jan 3 at 16:29
Mohammad Amir AshraffMohammad Amir Ashraff
254
asked Jan 3 at 16:29
Mohammad Amir AshraffMohammad Amir Ashraff
254
254
5
df.ge(10).astype(int)
– ALollz
Jan 3 at 16:31
3
Sounds like a homework assignment of some sort. What have you done? Please post your code and explain why you are not happy with it.
– DYZ
Jan 3 at 16:31
add a comment |
5
df.ge(10).astype(int)
– ALollz
Jan 3 at 16:31
3
Sounds like a homework assignment of some sort. What have you done? Please post your code and explain why you are not happy with it.
– DYZ
Jan 3 at 16:31
5
5
df.ge(10).astype(int)– ALollz
Jan 3 at 16:31
df.ge(10).astype(int)– ALollz
Jan 3 at 16:31
3
3
Sounds like a homework assignment of some sort. What have you done? Please post your code and explain why you are not happy with it.
– DYZ
Jan 3 at 16:31
Sounds like a homework assignment of some sort. What have you done? Please post your code and explain why you are not happy with it.
– DYZ
Jan 3 at 16:31
add a comment |
1 Answer
1
active
oldest
votes
You could use np.where:
pd.DataFrame(np.where(df >= 10, 1, 0), columns=df.columns)
G1 G2 G3
0 0 0 0
1 0 0 0
2 0 0 1
3 1 1 1
4 0 1 1
5 1 1 1
answered Jan 3 at 16:31
yatuyatu
15.8k41642
add a comment |
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1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
You could use np.where:
pd.DataFrame(np.where(df >= 10, 1, 0), columns=df.columns)
G1 G2 G3
0 0 0 0
1 0 0 0
2 0 0 1
3 1 1 1
4 0 1 1
5 1 1 1
answered Jan 3 at 16:31
yatuyatu
15.8k41642
add a comment |
You could use np.where:
pd.DataFrame(np.where(df >= 10, 1, 0), columns=df.columns)
G1 G2 G3
0 0 0 0
1 0 0 0
2 0 0 1
3 1 1 1
4 0 1 1
5 1 1 1
answered Jan 3 at 16:31
yatuyatu
15.8k41642
add a comment |
You could use np.where:
pd.DataFrame(np.where(df >= 10, 1, 0), columns=df.columns)
G1 G2 G3
0 0 0 0
1 0 0 0
2 0 0 1
3 1 1 1
4 0 1 1
5 1 1 1
answered Jan 3 at 16:31
yatuyatu
15.8k41642
You could use np.where:
pd.DataFrame(np.where(df >= 10, 1, 0), columns=df.columns)
G1 G2 G3
0 0 0 0
1 0 0 0
2 0 0 1
3 1 1 1
4 0 1 1
5 1 1 1
answered Jan 3 at 16:31
yatuyatu
15.8k41642
answered Jan 3 at 16:31
yatuyatu
15.8k41642
answered Jan 3 at 16:31
yatuyatu
15.8k41642
answered Jan 3 at 16:31
yatuyatu
15.8k41642
15.8k41642
add a comment |
add a comment |
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5
df.ge(10).astype(int)– ALollz
Jan 3 at 16:31
3
Sounds like a homework assignment of some sort. What have you done? Please post your code and explain why you are not happy with it.
– DYZ
Jan 3 at 16:31