How to select dataframe columns with lists and ranges combined
Please consider this df:
df = pd.DataFrame({'a':[1,2], 'b':[1,2], 'c':[1,2], 'd':[1,2], 'e':[1,2], 'f':[1,2], 'g':[1,2], 'h':[1,2]})
a b c d e f g h
0 1 1 1 1 1 1 1 1
1 2 2 2 2 2 2 2 2
How can I select the 1st, 4th, and 5th-7th columns?
What I tried:
df.iloc[:, [0, 3, np.arange(5,8)]]
ValueError: setting an array element with a sequence.
python pandas dataframe indexing
edited Mar 18 '18 at 1:37
jpp
99.5k2161110
asked Mar 18 '18 at 1:25
SaeedSaeed
497411
add a comment |
Please consider this df:
df = pd.DataFrame({'a':[1,2], 'b':[1,2], 'c':[1,2], 'd':[1,2], 'e':[1,2], 'f':[1,2], 'g':[1,2], 'h':[1,2]})
a b c d e f g h
0 1 1 1 1 1 1 1 1
1 2 2 2 2 2 2 2 2
How can I select the 1st, 4th, and 5th-7th columns?
What I tried:
df.iloc[:, [0, 3, np.arange(5,8)]]
ValueError: setting an array element with a sequence.
python pandas dataframe indexing
edited Mar 18 '18 at 1:37
jpp
99.5k2161110
asked Mar 18 '18 at 1:25
SaeedSaeed
497411
1
You may also find this post useful.
– pault
Mar 18 '18 at 1:31
add a comment |
Please consider this df:
df = pd.DataFrame({'a':[1,2], 'b':[1,2], 'c':[1,2], 'd':[1,2], 'e':[1,2], 'f':[1,2], 'g':[1,2], 'h':[1,2]})
a b c d e f g h
0 1 1 1 1 1 1 1 1
1 2 2 2 2 2 2 2 2
How can I select the 1st, 4th, and 5th-7th columns?
What I tried:
df.iloc[:, [0, 3, np.arange(5,8)]]
ValueError: setting an array element with a sequence.
python pandas dataframe indexing
edited Mar 18 '18 at 1:37
jpp
99.5k2161110
asked Mar 18 '18 at 1:25
SaeedSaeed
497411
Please consider this df:
df = pd.DataFrame({'a':[1,2], 'b':[1,2], 'c':[1,2], 'd':[1,2], 'e':[1,2], 'f':[1,2], 'g':[1,2], 'h':[1,2]})
a b c d e f g h
0 1 1 1 1 1 1 1 1
1 2 2 2 2 2 2 2 2
How can I select the 1st, 4th, and 5th-7th columns?
What I tried:
df.iloc[:, [0, 3, np.arange(5,8)]]
ValueError: setting an array element with a sequence.
python pandas dataframe indexing
python pandas dataframe indexing
edited Mar 18 '18 at 1:37
jpp
99.5k2161110
asked Mar 18 '18 at 1:25
SaeedSaeed
497411
edited Mar 18 '18 at 1:37
jpp
99.5k2161110
asked Mar 18 '18 at 1:25
SaeedSaeed
497411
edited Mar 18 '18 at 1:37
jpp
99.5k2161110
edited Mar 18 '18 at 1:37
jpp
99.5k2161110
edited Mar 18 '18 at 1:37
jpp
99.5k2161110
99.5k2161110
asked Mar 18 '18 at 1:25
SaeedSaeed
497411
asked Mar 18 '18 at 1:25
SaeedSaeed
497411
asked Mar 18 '18 at 1:25
SaeedSaeed
497411
497411
1
You may also find this post useful.
– pault
Mar 18 '18 at 1:31
add a comment |
1
You may also find this post useful.
– pault
Mar 18 '18 at 1:31
1
1
You may also find this post useful.
– pault
Mar 18 '18 at 1:31
You may also find this post useful.
– pault
Mar 18 '18 at 1:31
add a comment |
1 Answer
1
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You can do this:
df.iloc[:, [0, 3] + list(range(5,8))]
[0, 3] + list(range(5,8)) concatenates 2 lists, combining your explicit list with a list derived from your desired range.
Alternatively, you can use numpy.r to build an indexing array for you:
import numpy as np
df.iloc[:, np.r_[0,3,5:8]]
np.r_[0,3,5:8] # array([0, 3, 5, 6, 7])
This would be useful, for example, if you have multiple ranges.
answered Mar 18 '18 at 1:28
jppjpp
99.5k2161110
1
2nd approach is exactly what I needed. Thanks
– Saeed
Mar 18 '18 at 17:06
add a comment |
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1 Answer
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1 Answer
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active
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You can do this:
df.iloc[:, [0, 3] + list(range(5,8))]
[0, 3] + list(range(5,8)) concatenates 2 lists, combining your explicit list with a list derived from your desired range.
Alternatively, you can use numpy.r to build an indexing array for you:
import numpy as np
df.iloc[:, np.r_[0,3,5:8]]
np.r_[0,3,5:8] # array([0, 3, 5, 6, 7])
This would be useful, for example, if you have multiple ranges.
answered Mar 18 '18 at 1:28
jppjpp
99.5k2161110
1
2nd approach is exactly what I needed. Thanks
– Saeed
Mar 18 '18 at 17:06
add a comment |
You can do this:
df.iloc[:, [0, 3] + list(range(5,8))]
[0, 3] + list(range(5,8)) concatenates 2 lists, combining your explicit list with a list derived from your desired range.
Alternatively, you can use numpy.r to build an indexing array for you:
import numpy as np
df.iloc[:, np.r_[0,3,5:8]]
np.r_[0,3,5:8] # array([0, 3, 5, 6, 7])
This would be useful, for example, if you have multiple ranges.
answered Mar 18 '18 at 1:28
jppjpp
99.5k2161110
1
2nd approach is exactly what I needed. Thanks
– Saeed
Mar 18 '18 at 17:06
add a comment |
You can do this:
df.iloc[:, [0, 3] + list(range(5,8))]
[0, 3] + list(range(5,8)) concatenates 2 lists, combining your explicit list with a list derived from your desired range.
Alternatively, you can use numpy.r to build an indexing array for you:
import numpy as np
df.iloc[:, np.r_[0,3,5:8]]
np.r_[0,3,5:8] # array([0, 3, 5, 6, 7])
This would be useful, for example, if you have multiple ranges.
answered Mar 18 '18 at 1:28
jppjpp
99.5k2161110
You can do this:
df.iloc[:, [0, 3] + list(range(5,8))]
[0, 3] + list(range(5,8)) concatenates 2 lists, combining your explicit list with a list derived from your desired range.
Alternatively, you can use numpy.r to build an indexing array for you:
import numpy as np
df.iloc[:, np.r_[0,3,5:8]]
np.r_[0,3,5:8] # array([0, 3, 5, 6, 7])
This would be useful, for example, if you have multiple ranges.
answered Mar 18 '18 at 1:28
jppjpp
99.5k2161110
edited Mar 18 '18 at 1:35
answered Mar 18 '18 at 1:28
jppjpp
99.5k2161110
answered Mar 18 '18 at 1:28
jppjpp
99.5k2161110
answered Mar 18 '18 at 1:28
jppjpp
99.5k2161110
99.5k2161110
1
2nd approach is exactly what I needed. Thanks
– Saeed
Mar 18 '18 at 17:06
add a comment |
1
2nd approach is exactly what I needed. Thanks
– Saeed
Mar 18 '18 at 17:06
1
1
2nd approach is exactly what I needed. Thanks
– Saeed
Mar 18 '18 at 17:06
2nd approach is exactly what I needed. Thanks
– Saeed
Mar 18 '18 at 17:06
add a comment |
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You may also find this post useful.
– pault
Mar 18 '18 at 1:31