Pandas Dataframe - select columns with a specific value in a specific row
up vote
1
down vote
favorite
I want to select columns with a specific value (say 1) in a specific row (say first row) for Pandas Dataframe
python pandas dataframe
asked Nov 8 at 11:09
ghos-h
718717
add a comment |
up vote
1
down vote
favorite
I want to select columns with a specific value (say 1) in a specific row (say first row) for Pandas Dataframe
python pandas dataframe
asked Nov 8 at 11:09
ghos-h
718717
add a comment |
up vote
1
down vote
favorite
up vote
1
down vote
favorite
I want to select columns with a specific value (say 1) in a specific row (say first row) for Pandas Dataframe
python pandas dataframe
asked Nov 8 at 11:09
ghos-h
718717
I want to select columns with a specific value (say 1) in a specific row (say first row) for Pandas Dataframe
python pandas dataframe
python pandas dataframe
asked Nov 8 at 11:09
ghos-h
718717
asked Nov 8 at 11:09
ghos-h
718717
asked Nov 8 at 11:09
ghos-h
718717
asked Nov 8 at 11:09
ghos-h
718717
asked Nov 8 at 11:09
ghos-h
718717
718717
add a comment |
add a comment |
2 Answers
2
active
oldest
votes
up vote
0
down vote
accepted
Use iloc with boolean indexing, for performance is better filtering index not DataFrame and then select index (see performance):
df = pd.DataFrame({
'A':list('abcdef'),
'B':[4,5,4,5,5,4],
'C':[7,8,9,4,2,3],
'D':[1,3,5,7,1,0],
'E':[5,3,6,9,2,4],
'F':list('aaabbb')
})
print (df)
A B C D E F
0 a 4 7 1 5 a
1 b 5 8 3 3 a
2 c 4 9 5 6 a
3 d 5 4 7 9 b
4 e 5 2 1 2 b
5 f 4 3 0 4 b
s = df.iloc[0]
a = s.index[s == 1]
print (a)
Index(['D'], dtype='object')
a = s.index.values[(s == 1)]
print (a)
['D']
answered Nov 8 at 11:16
jezrael
306k20240316
add a comment |
up vote
0
down vote
You can use iloc to extract a row as a series, then apply your condition:
row = df.iloc[0] # extract first row as series
res = row[res == 1].index # filter for values equal to 1 and get columns via index
answered Nov 8 at 11:14
jpp
81.7k194795
add a comment |
2 Answers
2
active
oldest
votes
2 Answers
2
active
oldest
votes
active
oldest
votes
active
oldest
votes
up vote
0
down vote
accepted
Use iloc with boolean indexing, for performance is better filtering index not DataFrame and then select index (see performance):
df = pd.DataFrame({
'A':list('abcdef'),
'B':[4,5,4,5,5,4],
'C':[7,8,9,4,2,3],
'D':[1,3,5,7,1,0],
'E':[5,3,6,9,2,4],
'F':list('aaabbb')
})
print (df)
A B C D E F
0 a 4 7 1 5 a
1 b 5 8 3 3 a
2 c 4 9 5 6 a
3 d 5 4 7 9 b
4 e 5 2 1 2 b
5 f 4 3 0 4 b
s = df.iloc[0]
a = s.index[s == 1]
print (a)
Index(['D'], dtype='object')
a = s.index.values[(s == 1)]
print (a)
['D']
answered Nov 8 at 11:16
jezrael
306k20240316
add a comment |
up vote
0
down vote
accepted
Use iloc with boolean indexing, for performance is better filtering index not DataFrame and then select index (see performance):
df = pd.DataFrame({
'A':list('abcdef'),
'B':[4,5,4,5,5,4],
'C':[7,8,9,4,2,3],
'D':[1,3,5,7,1,0],
'E':[5,3,6,9,2,4],
'F':list('aaabbb')
})
print (df)
A B C D E F
0 a 4 7 1 5 a
1 b 5 8 3 3 a
2 c 4 9 5 6 a
3 d 5 4 7 9 b
4 e 5 2 1 2 b
5 f 4 3 0 4 b
s = df.iloc[0]
a = s.index[s == 1]
print (a)
Index(['D'], dtype='object')
a = s.index.values[(s == 1)]
print (a)
['D']
answered Nov 8 at 11:16
jezrael
306k20240316
add a comment |
up vote
0
down vote
accepted
up vote
0
down vote
accepted
Use iloc with boolean indexing, for performance is better filtering index not DataFrame and then select index (see performance):
df = pd.DataFrame({
'A':list('abcdef'),
'B':[4,5,4,5,5,4],
'C':[7,8,9,4,2,3],
'D':[1,3,5,7,1,0],
'E':[5,3,6,9,2,4],
'F':list('aaabbb')
})
print (df)
A B C D E F
0 a 4 7 1 5 a
1 b 5 8 3 3 a
2 c 4 9 5 6 a
3 d 5 4 7 9 b
4 e 5 2 1 2 b
5 f 4 3 0 4 b
s = df.iloc[0]
a = s.index[s == 1]
print (a)
Index(['D'], dtype='object')
a = s.index.values[(s == 1)]
print (a)
['D']
answered Nov 8 at 11:16
jezrael
306k20240316
Use iloc with boolean indexing, for performance is better filtering index not DataFrame and then select index (see performance):
df = pd.DataFrame({
'A':list('abcdef'),
'B':[4,5,4,5,5,4],
'C':[7,8,9,4,2,3],
'D':[1,3,5,7,1,0],
'E':[5,3,6,9,2,4],
'F':list('aaabbb')
})
print (df)
A B C D E F
0 a 4 7 1 5 a
1 b 5 8 3 3 a
2 c 4 9 5 6 a
3 d 5 4 7 9 b
4 e 5 2 1 2 b
5 f 4 3 0 4 b
s = df.iloc[0]
a = s.index[s == 1]
print (a)
Index(['D'], dtype='object')
a = s.index.values[(s == 1)]
print (a)
['D']
answered Nov 8 at 11:16
jezrael
306k20240316
edited Nov 8 at 11:27
answered Nov 8 at 11:16
jezrael
306k20240316
answered Nov 8 at 11:16
jezrael
306k20240316
answered Nov 8 at 11:16
jezrael
306k20240316
306k20240316
add a comment |
add a comment |
up vote
0
down vote
You can use iloc to extract a row as a series, then apply your condition:
row = df.iloc[0] # extract first row as series
res = row[res == 1].index # filter for values equal to 1 and get columns via index
answered Nov 8 at 11:14
jpp
81.7k194795
add a comment |
up vote
0
down vote
You can use iloc to extract a row as a series, then apply your condition:
row = df.iloc[0] # extract first row as series
res = row[res == 1].index # filter for values equal to 1 and get columns via index
answered Nov 8 at 11:14
jpp
81.7k194795
add a comment |
up vote
0
down vote
up vote
0
down vote
You can use iloc to extract a row as a series, then apply your condition:
row = df.iloc[0] # extract first row as series
res = row[res == 1].index # filter for values equal to 1 and get columns via index
answered Nov 8 at 11:14
jpp
81.7k194795
You can use iloc to extract a row as a series, then apply your condition:
row = df.iloc[0] # extract first row as series
res = row[res == 1].index # filter for values equal to 1 and get columns via index
answered Nov 8 at 11:14
jpp
81.7k194795
answered Nov 8 at 11:14
jpp
81.7k194795
answered Nov 8 at 11:14
jpp
81.7k194795
answered Nov 8 at 11:14
jpp
81.7k194795
81.7k194795
add a comment |
add a comment |
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
StackExchange.ready(
function () {
StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fstackoverflow.com%2fquestions%2f53206536%2fpandas-dataframe-select-columns-with-a-specific-value-in-a-specific-row%23new-answer', 'question_page');
}
);
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
