TypeError: unhashable type: 'slice' pandas DataFrame column
This is probably simple but I cant find the explanation and it happens to me all the time.
I am trying to selected values from column Rate1E that are over 3.5 and view the rest of the rows in pandas DataFrame energy for selected rows meeting criteria as stated above. I had someone give me an answer before and have simply changed to text as follows:
energy = energy.loc[energy[:, 'Rate1E'] >= 3.5]
print(energy.loc[:, 'Rate1E'])
However once again I have found myself with the error:
TypeError: unhashable type: 'slice'
Online solutions suggest .loc is the answer. Would someone know how to fix the code or better yet explain to me why I always seem to get that error.
Thanks.
python pandas dataframe indexing series
asked Nov 14 '18 at 15:36
geds133geds133
818
add a comment |
This is probably simple but I cant find the explanation and it happens to me all the time.
I am trying to selected values from column Rate1E that are over 3.5 and view the rest of the rows in pandas DataFrame energy for selected rows meeting criteria as stated above. I had someone give me an answer before and have simply changed to text as follows:
energy = energy.loc[energy[:, 'Rate1E'] >= 3.5]
print(energy.loc[:, 'Rate1E'])
However once again I have found myself with the error:
TypeError: unhashable type: 'slice'
Online solutions suggest .loc is the answer. Would someone know how to fix the code or better yet explain to me why I always seem to get that error.
Thanks.
python pandas dataframe indexing series
asked Nov 14 '18 at 15:36
geds133geds133
818
In general,df[x, y, z]treatsx, y, zas a tuple that represents a label when the column index is aMultiIndex. In this case it's trying to use:, i.e.,slice(None)as a label.
– BallpointBen
Nov 14 '18 at 15:49
add a comment |
This is probably simple but I cant find the explanation and it happens to me all the time.
I am trying to selected values from column Rate1E that are over 3.5 and view the rest of the rows in pandas DataFrame energy for selected rows meeting criteria as stated above. I had someone give me an answer before and have simply changed to text as follows:
energy = energy.loc[energy[:, 'Rate1E'] >= 3.5]
print(energy.loc[:, 'Rate1E'])
However once again I have found myself with the error:
TypeError: unhashable type: 'slice'
Online solutions suggest .loc is the answer. Would someone know how to fix the code or better yet explain to me why I always seem to get that error.
Thanks.
python pandas dataframe indexing series
asked Nov 14 '18 at 15:36
geds133geds133
818
This is probably simple but I cant find the explanation and it happens to me all the time.
I am trying to selected values from column Rate1E that are over 3.5 and view the rest of the rows in pandas DataFrame energy for selected rows meeting criteria as stated above. I had someone give me an answer before and have simply changed to text as follows:
energy = energy.loc[energy[:, 'Rate1E'] >= 3.5]
print(energy.loc[:, 'Rate1E'])
However once again I have found myself with the error:
TypeError: unhashable type: 'slice'
Online solutions suggest .loc is the answer. Would someone know how to fix the code or better yet explain to me why I always seem to get that error.
Thanks.
python pandas dataframe indexing series
python pandas dataframe indexing series
asked Nov 14 '18 at 15:36
geds133geds133
818
asked Nov 14 '18 at 15:36
geds133geds133
818
edited Dec 12 '18 at 13:26
geds133
asked Nov 14 '18 at 15:36
geds133geds133
818
asked Nov 14 '18 at 15:36
geds133geds133
818
asked Nov 14 '18 at 15:36
geds133geds133
818
818
In general,df[x, y, z]treatsx, y, zas a tuple that represents a label when the column index is aMultiIndex. In this case it's trying to use:, i.e.,slice(None)as a label.
– BallpointBen
Nov 14 '18 at 15:49
add a comment |
In general,df[x, y, z]treatsx, y, zas a tuple that represents a label when the column index is aMultiIndex. In this case it's trying to use:, i.e.,slice(None)as a label.
– BallpointBen
Nov 14 '18 at 15:49
In general,
df[x, y, z] treats x, y, z as a tuple that represents a label when the column index is a MultiIndex. In this case it's trying to use :, i.e., slice(None) as a label.– BallpointBen
Nov 14 '18 at 15:49
In general,
df[x, y, z] treats x, y, z as a tuple that represents a label when the column index is a MultiIndex. In this case it's trying to use :, i.e., slice(None) as a label.– BallpointBen
Nov 14 '18 at 15:49
add a comment |
2 Answers
2
active
oldest
votes
Your syntax is incorrect. You need:
energy = energy.loc[energy['Rate1E'] >= 3.5]
Alternatively:
energy = energy.loc[energy.loc[:, 'Rate1E'] >= 3.5]
The crucial point is energy.loc[:, 'Rate1E'] and energy['Rate1E'] are series, the latter being a convenient way to access the former.
It is unfortunate, but the Pandas documentation doesn't specify precisely permitted arguments for pd.DataFrame.__getitem__, for which df is syntactic sugar. The most popular uses are:
- Provide a string to give a series.
- Provide a list to give a dataframe.
- Provide a Boolean series to filter your dataframe.
edited Dec 12 '18 at 13:28
geds133
818
answered Nov 14 '18 at 15:44
jppjpp
102k2164115
add a comment |
Your call of energy[:, 'Rate1E'] is doing something different to what you expect. You're looking for a .loc call.
energy = energy.loc[energy['Rate1E'] >= 3.5]
print(energy['Rate1E'])
edited Dec 12 '18 at 14:07
geds133
818
answered Nov 14 '18 at 15:47
cvonstegcvonsteg
20616
Solution is incorrect as.loccall needed after initial square brackets.
– geds133
Nov 14 '18 at 16:03
For solution see above
– geds133
Nov 14 '18 at 16:04
I am trying to view all other columns inenergythat is based on values inunitRate1Electhat are greater or equal to 3.5.
– geds133
Nov 14 '18 at 16:16
@geds133 Yes, that is what the proposed answer does. @jpp has done a great job of summarizing why you can use both bothenergy.locorenergyinside your firstenergy.loccall. Either way it looks like your problem is solved :)
– cvonsteg
Nov 14 '18 at 16:18
add a comment |
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2 Answers
2
active
oldest
votes
2 Answers
2
active
oldest
votes
active
oldest
votes
active
oldest
votes
Your syntax is incorrect. You need:
energy = energy.loc[energy['Rate1E'] >= 3.5]
Alternatively:
energy = energy.loc[energy.loc[:, 'Rate1E'] >= 3.5]
The crucial point is energy.loc[:, 'Rate1E'] and energy['Rate1E'] are series, the latter being a convenient way to access the former.
It is unfortunate, but the Pandas documentation doesn't specify precisely permitted arguments for pd.DataFrame.__getitem__, for which df is syntactic sugar. The most popular uses are:
- Provide a string to give a series.
- Provide a list to give a dataframe.
- Provide a Boolean series to filter your dataframe.
edited Dec 12 '18 at 13:28
geds133
818
answered Nov 14 '18 at 15:44
jppjpp
102k2164115
add a comment |
Your syntax is incorrect. You need:
energy = energy.loc[energy['Rate1E'] >= 3.5]
Alternatively:
energy = energy.loc[energy.loc[:, 'Rate1E'] >= 3.5]
The crucial point is energy.loc[:, 'Rate1E'] and energy['Rate1E'] are series, the latter being a convenient way to access the former.
It is unfortunate, but the Pandas documentation doesn't specify precisely permitted arguments for pd.DataFrame.__getitem__, for which df is syntactic sugar. The most popular uses are:
- Provide a string to give a series.
- Provide a list to give a dataframe.
- Provide a Boolean series to filter your dataframe.
edited Dec 12 '18 at 13:28
geds133
818
answered Nov 14 '18 at 15:44
jppjpp
102k2164115
add a comment |
Your syntax is incorrect. You need:
energy = energy.loc[energy['Rate1E'] >= 3.5]
Alternatively:
energy = energy.loc[energy.loc[:, 'Rate1E'] >= 3.5]
The crucial point is energy.loc[:, 'Rate1E'] and energy['Rate1E'] are series, the latter being a convenient way to access the former.
It is unfortunate, but the Pandas documentation doesn't specify precisely permitted arguments for pd.DataFrame.__getitem__, for which df is syntactic sugar. The most popular uses are:
- Provide a string to give a series.
- Provide a list to give a dataframe.
- Provide a Boolean series to filter your dataframe.
edited Dec 12 '18 at 13:28
geds133
818
answered Nov 14 '18 at 15:44
jppjpp
102k2164115
Your syntax is incorrect. You need:
energy = energy.loc[energy['Rate1E'] >= 3.5]
Alternatively:
energy = energy.loc[energy.loc[:, 'Rate1E'] >= 3.5]
The crucial point is energy.loc[:, 'Rate1E'] and energy['Rate1E'] are series, the latter being a convenient way to access the former.
It is unfortunate, but the Pandas documentation doesn't specify precisely permitted arguments for pd.DataFrame.__getitem__, for which df is syntactic sugar. The most popular uses are:
- Provide a string to give a series.
- Provide a list to give a dataframe.
- Provide a Boolean series to filter your dataframe.
edited Dec 12 '18 at 13:28
geds133
818
answered Nov 14 '18 at 15:44
jppjpp
102k2164115
edited Dec 12 '18 at 13:28
geds133
818
edited Dec 12 '18 at 13:28
geds133
818
edited Dec 12 '18 at 13:28
geds133
818
818
answered Nov 14 '18 at 15:44
jppjpp
102k2164115
answered Nov 14 '18 at 15:44
jppjpp
102k2164115
answered Nov 14 '18 at 15:44
jppjpp
102k2164115
102k2164115
add a comment |
add a comment |
Your call of energy[:, 'Rate1E'] is doing something different to what you expect. You're looking for a .loc call.
energy = energy.loc[energy['Rate1E'] >= 3.5]
print(energy['Rate1E'])
edited Dec 12 '18 at 14:07
geds133
818
answered Nov 14 '18 at 15:47
cvonstegcvonsteg
20616
Solution is incorrect as.loccall needed after initial square brackets.
– geds133
Nov 14 '18 at 16:03
For solution see above
– geds133
Nov 14 '18 at 16:04
I am trying to view all other columns inenergythat is based on values inunitRate1Electhat are greater or equal to 3.5.
– geds133
Nov 14 '18 at 16:16
@geds133 Yes, that is what the proposed answer does. @jpp has done a great job of summarizing why you can use both bothenergy.locorenergyinside your firstenergy.loccall. Either way it looks like your problem is solved :)
– cvonsteg
Nov 14 '18 at 16:18
add a comment |
Your call of energy[:, 'Rate1E'] is doing something different to what you expect. You're looking for a .loc call.
energy = energy.loc[energy['Rate1E'] >= 3.5]
print(energy['Rate1E'])
edited Dec 12 '18 at 14:07
geds133
818
answered Nov 14 '18 at 15:47
cvonstegcvonsteg
20616
Solution is incorrect as.loccall needed after initial square brackets.
– geds133
Nov 14 '18 at 16:03
For solution see above
– geds133
Nov 14 '18 at 16:04
I am trying to view all other columns inenergythat is based on values inunitRate1Electhat are greater or equal to 3.5.
– geds133
Nov 14 '18 at 16:16
@geds133 Yes, that is what the proposed answer does. @jpp has done a great job of summarizing why you can use both bothenergy.locorenergyinside your firstenergy.loccall. Either way it looks like your problem is solved :)
– cvonsteg
Nov 14 '18 at 16:18
add a comment |
Your call of energy[:, 'Rate1E'] is doing something different to what you expect. You're looking for a .loc call.
energy = energy.loc[energy['Rate1E'] >= 3.5]
print(energy['Rate1E'])
edited Dec 12 '18 at 14:07
geds133
818
answered Nov 14 '18 at 15:47
cvonstegcvonsteg
20616
Your call of energy[:, 'Rate1E'] is doing something different to what you expect. You're looking for a .loc call.
energy = energy.loc[energy['Rate1E'] >= 3.5]
print(energy['Rate1E'])
edited Dec 12 '18 at 14:07
geds133
818
answered Nov 14 '18 at 15:47
cvonstegcvonsteg
20616
edited Dec 12 '18 at 14:07
geds133
818
edited Dec 12 '18 at 14:07
geds133
818
edited Dec 12 '18 at 14:07
geds133
818
818
answered Nov 14 '18 at 15:47
cvonstegcvonsteg
20616
answered Nov 14 '18 at 15:47
cvonstegcvonsteg
20616
answered Nov 14 '18 at 15:47
cvonstegcvonsteg
20616
20616
Solution is incorrect as.loccall needed after initial square brackets.
– geds133
Nov 14 '18 at 16:03
For solution see above
– geds133
Nov 14 '18 at 16:04
I am trying to view all other columns inenergythat is based on values inunitRate1Electhat are greater or equal to 3.5.
– geds133
Nov 14 '18 at 16:16
@geds133 Yes, that is what the proposed answer does. @jpp has done a great job of summarizing why you can use both bothenergy.locorenergyinside your firstenergy.loccall. Either way it looks like your problem is solved :)
– cvonsteg
Nov 14 '18 at 16:18
add a comment |
Solution is incorrect as.loccall needed after initial square brackets.
– geds133
Nov 14 '18 at 16:03
For solution see above
– geds133
Nov 14 '18 at 16:04
I am trying to view all other columns inenergythat is based on values inunitRate1Electhat are greater or equal to 3.5.
– geds133
Nov 14 '18 at 16:16
@geds133 Yes, that is what the proposed answer does. @jpp has done a great job of summarizing why you can use both bothenergy.locorenergyinside your firstenergy.loccall. Either way it looks like your problem is solved :)
– cvonsteg
Nov 14 '18 at 16:18
Solution is incorrect as
.loc call needed after initial square brackets.– geds133
Nov 14 '18 at 16:03
Solution is incorrect as
.loc call needed after initial square brackets.– geds133
Nov 14 '18 at 16:03
For solution see above
– geds133
Nov 14 '18 at 16:04
For solution see above
– geds133
Nov 14 '18 at 16:04
I am trying to view all other columns in
energy that is based on values in unitRate1Elec that are greater or equal to 3.5.– geds133
Nov 14 '18 at 16:16
I am trying to view all other columns in
energy that is based on values in unitRate1Elec that are greater or equal to 3.5.– geds133
Nov 14 '18 at 16:16
@geds133 Yes, that is what the proposed answer does. @jpp has done a great job of summarizing why you can use both both
energy.loc or energy inside your first energy.loc call. Either way it looks like your problem is solved :)– cvonsteg
Nov 14 '18 at 16:18
@geds133 Yes, that is what the proposed answer does. @jpp has done a great job of summarizing why you can use both both
energy.loc or energy inside your first energy.loc call. Either way it looks like your problem is solved :)– cvonsteg
Nov 14 '18 at 16:18
add a comment |
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In general,
df[x, y, z]treatsx, y, zas a tuple that represents a label when the column index is aMultiIndex. In this case it's trying to use:, i.e.,slice(None)as a label.– BallpointBen
Nov 14 '18 at 15:49