Two conditional checks inside a Panda data frame access
0
The command below works fine
idx = np.asarray(df.loc[df['lat1'] != '.'].ix[:,0].index)
but I'm trying to do something like this (with 2 conditions):
idx = np.asarray(df.loc[df['lat1'] != '.' and df['state'] == df['state'][0]].ix[:,0].index)
This throws the following traceback:
Traceback (most recent call last):
File "<ipython-input-274-c07cda0be195>", line 1, in <module>
idx = np.asarray(df.loc[df['lat1'] != '.' and df['state'] == df['state'][0]].ix[:,0].index)
File "/anaconda3/lib/python3.6/site-packages/pandas/core/generic.py", line 1573, in __nonzero__
.format(self.__class__.__name__))
ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().
I've looked it up but not able to find a suitable tweak for this case. Any leads would be appreciated.
[EDIT]: Based on the suggestion below, when I try this:
df[(df['lat1']!='.') & (df['state']== df['state'][0])]
I get
lat1 long1 ... state county
5 34 11 ... AK Anchorage
7 1 -3 ... AK Anchorage
14 1 -5 ... AK Anchorage
30 7 -3 ... AK Anchorage
44 1 -4 ... AK Anchorage
47 1 -3 ... AK Anchorage
75 1 -4 ... AK Juneau
82 5 -1 ... AK Kenai Peninsula
102 4 -1 ... AK Fairbanks North Star
106 4 -1 ... AK Matanuska Susitna
137 3 -3 ... AK Matanuska Susitna
[11 rows x 5 columns]
How do I extract only the first column containing the indices?
python pandas dataframe
asked Nov 21 at 0:34
db18
1467
add a comment |
0
The command below works fine
idx = np.asarray(df.loc[df['lat1'] != '.'].ix[:,0].index)
but I'm trying to do something like this (with 2 conditions):
idx = np.asarray(df.loc[df['lat1'] != '.' and df['state'] == df['state'][0]].ix[:,0].index)
This throws the following traceback:
Traceback (most recent call last):
File "<ipython-input-274-c07cda0be195>", line 1, in <module>
idx = np.asarray(df.loc[df['lat1'] != '.' and df['state'] == df['state'][0]].ix[:,0].index)
File "/anaconda3/lib/python3.6/site-packages/pandas/core/generic.py", line 1573, in __nonzero__
.format(self.__class__.__name__))
ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().
I've looked it up but not able to find a suitable tweak for this case. Any leads would be appreciated.
[EDIT]: Based on the suggestion below, when I try this:
df[(df['lat1']!='.') & (df['state']== df['state'][0])]
I get
lat1 long1 ... state county
5 34 11 ... AK Anchorage
7 1 -3 ... AK Anchorage
14 1 -5 ... AK Anchorage
30 7 -3 ... AK Anchorage
44 1 -4 ... AK Anchorage
47 1 -3 ... AK Anchorage
75 1 -4 ... AK Juneau
82 5 -1 ... AK Kenai Peninsula
102 4 -1 ... AK Fairbanks North Star
106 4 -1 ... AK Matanuska Susitna
137 3 -3 ... AK Matanuska Susitna
[11 rows x 5 columns]
How do I extract only the first column containing the indices?
python pandas dataframe
asked Nov 21 at 0:34
db18
1467
add a comment |
0
0
0
The command below works fine
idx = np.asarray(df.loc[df['lat1'] != '.'].ix[:,0].index)
but I'm trying to do something like this (with 2 conditions):
idx = np.asarray(df.loc[df['lat1'] != '.' and df['state'] == df['state'][0]].ix[:,0].index)
This throws the following traceback:
Traceback (most recent call last):
File "<ipython-input-274-c07cda0be195>", line 1, in <module>
idx = np.asarray(df.loc[df['lat1'] != '.' and df['state'] == df['state'][0]].ix[:,0].index)
File "/anaconda3/lib/python3.6/site-packages/pandas/core/generic.py", line 1573, in __nonzero__
.format(self.__class__.__name__))
ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().
I've looked it up but not able to find a suitable tweak for this case. Any leads would be appreciated.
[EDIT]: Based on the suggestion below, when I try this:
df[(df['lat1']!='.') & (df['state']== df['state'][0])]
I get
lat1 long1 ... state county
5 34 11 ... AK Anchorage
7 1 -3 ... AK Anchorage
14 1 -5 ... AK Anchorage
30 7 -3 ... AK Anchorage
44 1 -4 ... AK Anchorage
47 1 -3 ... AK Anchorage
75 1 -4 ... AK Juneau
82 5 -1 ... AK Kenai Peninsula
102 4 -1 ... AK Fairbanks North Star
106 4 -1 ... AK Matanuska Susitna
137 3 -3 ... AK Matanuska Susitna
[11 rows x 5 columns]
How do I extract only the first column containing the indices?
python pandas dataframe
asked Nov 21 at 0:34
db18
1467
The command below works fine
idx = np.asarray(df.loc[df['lat1'] != '.'].ix[:,0].index)
but I'm trying to do something like this (with 2 conditions):
idx = np.asarray(df.loc[df['lat1'] != '.' and df['state'] == df['state'][0]].ix[:,0].index)
This throws the following traceback:
Traceback (most recent call last):
File "<ipython-input-274-c07cda0be195>", line 1, in <module>
idx = np.asarray(df.loc[df['lat1'] != '.' and df['state'] == df['state'][0]].ix[:,0].index)
File "/anaconda3/lib/python3.6/site-packages/pandas/core/generic.py", line 1573, in __nonzero__
.format(self.__class__.__name__))
ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().
I've looked it up but not able to find a suitable tweak for this case. Any leads would be appreciated.
[EDIT]: Based on the suggestion below, when I try this:
df[(df['lat1']!='.') & (df['state']== df['state'][0])]
I get
lat1 long1 ... state county
5 34 11 ... AK Anchorage
7 1 -3 ... AK Anchorage
14 1 -5 ... AK Anchorage
30 7 -3 ... AK Anchorage
44 1 -4 ... AK Anchorage
47 1 -3 ... AK Anchorage
75 1 -4 ... AK Juneau
82 5 -1 ... AK Kenai Peninsula
102 4 -1 ... AK Fairbanks North Star
106 4 -1 ... AK Matanuska Susitna
137 3 -3 ... AK Matanuska Susitna
[11 rows x 5 columns]
How do I extract only the first column containing the indices?
python pandas dataframe
python pandas dataframe
asked Nov 21 at 0:34
db18
1467
asked Nov 21 at 0:34
db18
1467
edited Nov 21 at 1:33
asked Nov 21 at 0:34
db18
1467
asked Nov 21 at 0:34
db18
1467
asked Nov 21 at 0:34
db18
1467
1467
add a comment |
add a comment |
1 Answer
1
active
oldest
votes
1
I'm pretty sure this question has already been asked somewhere... But with pandas you can look at two conditions like this.
df[(df['lat1']!='.') & (df['state']== df['state'][0])]
You have to do bitwise operations
answered Nov 21 at 0:52
kradja
486
If you actually run it on a dataset, you'd find it gives an error like this: TypeError: ufunc 'isnan' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe''
– db18
Nov 21 at 1:11
If you post your dataset then it would be easier to understand. But you can probably just fill nas. df = df.fillna('')
– kradja
Nov 21 at 1:14
Please see EDIT above.
– db18
Nov 21 at 1:33
I don't understand your question. With the resulting dataframe you only want the first column containing indices? What does that mean? Also if my answer has helped you please upvote.
– kradja
Nov 21 at 5:36
I was able to solve the problem with your command. Thanks.
– db18
Nov 21 at 18:09
add a comment |
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1 Answer
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active
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votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
1
I'm pretty sure this question has already been asked somewhere... But with pandas you can look at two conditions like this.
df[(df['lat1']!='.') & (df['state']== df['state'][0])]
You have to do bitwise operations
answered Nov 21 at 0:52
kradja
486
If you actually run it on a dataset, you'd find it gives an error like this: TypeError: ufunc 'isnan' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe''
– db18
Nov 21 at 1:11
If you post your dataset then it would be easier to understand. But you can probably just fill nas. df = df.fillna('')
– kradja
Nov 21 at 1:14
Please see EDIT above.
– db18
Nov 21 at 1:33
I don't understand your question. With the resulting dataframe you only want the first column containing indices? What does that mean? Also if my answer has helped you please upvote.
– kradja
Nov 21 at 5:36
I was able to solve the problem with your command. Thanks.
– db18
Nov 21 at 18:09
add a comment |
1
I'm pretty sure this question has already been asked somewhere... But with pandas you can look at two conditions like this.
df[(df['lat1']!='.') & (df['state']== df['state'][0])]
You have to do bitwise operations
answered Nov 21 at 0:52
kradja
486
If you actually run it on a dataset, you'd find it gives an error like this: TypeError: ufunc 'isnan' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe''
– db18
Nov 21 at 1:11
If you post your dataset then it would be easier to understand. But you can probably just fill nas. df = df.fillna('')
– kradja
Nov 21 at 1:14
Please see EDIT above.
– db18
Nov 21 at 1:33
I don't understand your question. With the resulting dataframe you only want the first column containing indices? What does that mean? Also if my answer has helped you please upvote.
– kradja
Nov 21 at 5:36
I was able to solve the problem with your command. Thanks.
– db18
Nov 21 at 18:09
add a comment |
1
1
1
I'm pretty sure this question has already been asked somewhere... But with pandas you can look at two conditions like this.
df[(df['lat1']!='.') & (df['state']== df['state'][0])]
You have to do bitwise operations
answered Nov 21 at 0:52
kradja
486
I'm pretty sure this question has already been asked somewhere... But with pandas you can look at two conditions like this.
df[(df['lat1']!='.') & (df['state']== df['state'][0])]
You have to do bitwise operations
answered Nov 21 at 0:52
kradja
486
answered Nov 21 at 0:52
kradja
486
answered Nov 21 at 0:52
kradja
486
answered Nov 21 at 0:52
kradja
486
486
If you actually run it on a dataset, you'd find it gives an error like this: TypeError: ufunc 'isnan' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe''
– db18
Nov 21 at 1:11
If you post your dataset then it would be easier to understand. But you can probably just fill nas. df = df.fillna('')
– kradja
Nov 21 at 1:14
Please see EDIT above.
– db18
Nov 21 at 1:33
I don't understand your question. With the resulting dataframe you only want the first column containing indices? What does that mean? Also if my answer has helped you please upvote.
– kradja
Nov 21 at 5:36
I was able to solve the problem with your command. Thanks.
– db18
Nov 21 at 18:09
add a comment |
If you actually run it on a dataset, you'd find it gives an error like this: TypeError: ufunc 'isnan' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe''
– db18
Nov 21 at 1:11
If you post your dataset then it would be easier to understand. But you can probably just fill nas. df = df.fillna('')
– kradja
Nov 21 at 1:14
Please see EDIT above.
– db18
Nov 21 at 1:33
I don't understand your question. With the resulting dataframe you only want the first column containing indices? What does that mean? Also if my answer has helped you please upvote.
– kradja
Nov 21 at 5:36
I was able to solve the problem with your command. Thanks.
– db18
Nov 21 at 18:09
If you actually run it on a dataset, you'd find it gives an error like this: TypeError: ufunc 'isnan' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe''
– db18
Nov 21 at 1:11
If you actually run it on a dataset, you'd find it gives an error like this: TypeError: ufunc 'isnan' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe''
– db18
Nov 21 at 1:11
If you post your dataset then it would be easier to understand. But you can probably just fill nas. df = df.fillna('')
– kradja
Nov 21 at 1:14
If you post your dataset then it would be easier to understand. But you can probably just fill nas. df = df.fillna('')
– kradja
Nov 21 at 1:14
Please see EDIT above.
– db18
Nov 21 at 1:33
Please see EDIT above.
– db18
Nov 21 at 1:33
I don't understand your question. With the resulting dataframe you only want the first column containing indices? What does that mean? Also if my answer has helped you please upvote.
– kradja
Nov 21 at 5:36
I don't understand your question. With the resulting dataframe you only want the first column containing indices? What does that mean? Also if my answer has helped you please upvote.
– kradja
Nov 21 at 5:36
I was able to solve the problem with your command. Thanks.
– db18
Nov 21 at 18:09
I was able to solve the problem with your command. Thanks.
– db18
Nov 21 at 18:09
add a comment |
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