python pandas: assigning a json data to a data frame entry returns error “Incompatible indexer with...
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As a newbie to python I'm struggling with an error "Incompatible indexer with Series".
I'm reading a entry from a postgreSQL database:
df_postgresDB = pd.read_sql_query('SELECT * FROM public.json_view',con=<...>)
exampleKey = 'FPB-83160'
jsonCol = 'efforts'
AreasDict = df_postgresDB.loc[exampleKey, jsonCol]
print('AreasDict=', AreasDict)
print('type(AreasDict)=', type(AreasDict))
...output:
AreasDict= {'4G NeVe': 0, '4G FT ET': 400, '4G C-Plane': 800, 'MANO BTSSM': 0}
type(AreasDict)= <class 'dict'>
The column in the postgreSQL data base shows type 'jsonb':
This 'AreasDict' is used in the function of another project I want to call and re-use for my project. But in my project, I need to build up the data from another source. So I create a data frame and try to assign that 'AreasDict' ()...
column_names = ['issue_key', jsonCol]
df = pd.DataFrame(index=range(1,2), columns=column_names)
df.iloc[0, 0] = exampleKey
df.iloc[0, 1] = AreasDict
... and with the last code line I get that error
ValueError: Incompatible indexer with Series
What do I do wrong?
json pandas jsonb
asked Nov 20 at 8:49
Joe Phi
8510
|
show 11 more comments
up vote
0
down vote
favorite
As a newbie to python I'm struggling with an error "Incompatible indexer with Series".
I'm reading a entry from a postgreSQL database:
df_postgresDB = pd.read_sql_query('SELECT * FROM public.json_view',con=<...>)
exampleKey = 'FPB-83160'
jsonCol = 'efforts'
AreasDict = df_postgresDB.loc[exampleKey, jsonCol]
print('AreasDict=', AreasDict)
print('type(AreasDict)=', type(AreasDict))
...output:
AreasDict= {'4G NeVe': 0, '4G FT ET': 400, '4G C-Plane': 800, 'MANO BTSSM': 0}
type(AreasDict)= <class 'dict'>
The column in the postgreSQL data base shows type 'jsonb':
This 'AreasDict' is used in the function of another project I want to call and re-use for my project. But in my project, I need to build up the data from another source. So I create a data frame and try to assign that 'AreasDict' ()...
column_names = ['issue_key', jsonCol]
df = pd.DataFrame(index=range(1,2), columns=column_names)
df.iloc[0, 0] = exampleKey
df.iloc[0, 1] = AreasDict
... and with the last code line I get that error
ValueError: Incompatible indexer with Series
What do I do wrong?
json pandas jsonb
asked Nov 20 at 8:49
Joe Phi
8510
1
Problem is in pandas is not recomended store dicts in DataFrame column, but one possible solution is usedf.iloc[0, 1] = [AreasDict]
– jezrael
Nov 20 at 9:04
Yes, that turns it into class 'list' !! I'll try that in my project that calls the function using it and let you know.
– Joe Phi
Nov 20 at 9:09
So it working for you nice? It is what you need?
– jezrael
Nov 20 at 9:10
1
I still have to try that principle in my 'real' project that calls the shared function and see if that function eats it.Will let you know.
– Joe Phi
Nov 20 at 9:11
1
the workaround? this one:if isinstance(AreasDict, str) : then AreasDict = ast.literal_eval(AreasDict
– Joe Phi
Nov 20 at 13:51
|
show 11 more comments
up vote
0
down vote
favorite
up vote
0
down vote
favorite
As a newbie to python I'm struggling with an error "Incompatible indexer with Series".
I'm reading a entry from a postgreSQL database:
df_postgresDB = pd.read_sql_query('SELECT * FROM public.json_view',con=<...>)
exampleKey = 'FPB-83160'
jsonCol = 'efforts'
AreasDict = df_postgresDB.loc[exampleKey, jsonCol]
print('AreasDict=', AreasDict)
print('type(AreasDict)=', type(AreasDict))
...output:
AreasDict= {'4G NeVe': 0, '4G FT ET': 400, '4G C-Plane': 800, 'MANO BTSSM': 0}
type(AreasDict)= <class 'dict'>
The column in the postgreSQL data base shows type 'jsonb':
This 'AreasDict' is used in the function of another project I want to call and re-use for my project. But in my project, I need to build up the data from another source. So I create a data frame and try to assign that 'AreasDict' ()...
column_names = ['issue_key', jsonCol]
df = pd.DataFrame(index=range(1,2), columns=column_names)
df.iloc[0, 0] = exampleKey
df.iloc[0, 1] = AreasDict
... and with the last code line I get that error
ValueError: Incompatible indexer with Series
What do I do wrong?
json pandas jsonb
asked Nov 20 at 8:49
Joe Phi
8510
As a newbie to python I'm struggling with an error "Incompatible indexer with Series".
I'm reading a entry from a postgreSQL database:
df_postgresDB = pd.read_sql_query('SELECT * FROM public.json_view',con=<...>)
exampleKey = 'FPB-83160'
jsonCol = 'efforts'
AreasDict = df_postgresDB.loc[exampleKey, jsonCol]
print('AreasDict=', AreasDict)
print('type(AreasDict)=', type(AreasDict))
...output:
AreasDict= {'4G NeVe': 0, '4G FT ET': 400, '4G C-Plane': 800, 'MANO BTSSM': 0}
type(AreasDict)= <class 'dict'>
The column in the postgreSQL data base shows type 'jsonb':
This 'AreasDict' is used in the function of another project I want to call and re-use for my project. But in my project, I need to build up the data from another source. So I create a data frame and try to assign that 'AreasDict' ()...
column_names = ['issue_key', jsonCol]
df = pd.DataFrame(index=range(1,2), columns=column_names)
df.iloc[0, 0] = exampleKey
df.iloc[0, 1] = AreasDict
... and with the last code line I get that error
ValueError: Incompatible indexer with Series
What do I do wrong?
json pandas jsonb
json pandas jsonb
asked Nov 20 at 8:49
Joe Phi
8510
asked Nov 20 at 8:49
Joe Phi
8510
edited Nov 20 at 9:00
asked Nov 20 at 8:49
Joe Phi
8510
asked Nov 20 at 8:49
Joe Phi
8510
asked Nov 20 at 8:49
Joe Phi
8510
8510
1
Problem is in pandas is not recomended store dicts in DataFrame column, but one possible solution is usedf.iloc[0, 1] = [AreasDict]
– jezrael
Nov 20 at 9:04
Yes, that turns it into class 'list' !! I'll try that in my project that calls the function using it and let you know.
– Joe Phi
Nov 20 at 9:09
So it working for you nice? It is what you need?
– jezrael
Nov 20 at 9:10
1
I still have to try that principle in my 'real' project that calls the shared function and see if that function eats it.Will let you know.
– Joe Phi
Nov 20 at 9:11
1
the workaround? this one:if isinstance(AreasDict, str) : then AreasDict = ast.literal_eval(AreasDict
– Joe Phi
Nov 20 at 13:51
|
show 11 more comments
1
Problem is in pandas is not recomended store dicts in DataFrame column, but one possible solution is usedf.iloc[0, 1] = [AreasDict]
– jezrael
Nov 20 at 9:04
Yes, that turns it into class 'list' !! I'll try that in my project that calls the function using it and let you know.
– Joe Phi
Nov 20 at 9:09
So it working for you nice? It is what you need?
– jezrael
Nov 20 at 9:10
1
I still have to try that principle in my 'real' project that calls the shared function and see if that function eats it.Will let you know.
– Joe Phi
Nov 20 at 9:11
1
the workaround? this one:if isinstance(AreasDict, str) : then AreasDict = ast.literal_eval(AreasDict
– Joe Phi
Nov 20 at 13:51
1
1
Problem is in pandas is not recomended store dicts in DataFrame column, but one possible solution is use
df.iloc[0, 1] = [AreasDict]– jezrael
Nov 20 at 9:04
Problem is in pandas is not recomended store dicts in DataFrame column, but one possible solution is use
df.iloc[0, 1] = [AreasDict]– jezrael
Nov 20 at 9:04
Yes, that turns it into class 'list' !! I'll try that in my project that calls the function using it and let you know.
– Joe Phi
Nov 20 at 9:09
Yes, that turns it into class 'list' !! I'll try that in my project that calls the function using it and let you know.
– Joe Phi
Nov 20 at 9:09
So it working for you nice? It is what you need?
– jezrael
Nov 20 at 9:10
So it working for you nice? It is what you need?
– jezrael
Nov 20 at 9:10
1
1
I still have to try that principle in my 'real' project that calls the shared function and see if that function eats it.Will let you know.
– Joe Phi
Nov 20 at 9:11
I still have to try that principle in my 'real' project that calls the shared function and see if that function eats it.Will let you know.
– Joe Phi
Nov 20 at 9:11
1
1
the workaround? this one:
if isinstance(AreasDict, str) : then AreasDict = ast.literal_eval(AreasDict– Joe Phi
Nov 20 at 13:51
the workaround? this one:
if isinstance(AreasDict, str) : then AreasDict = ast.literal_eval(AreasDict– Joe Phi
Nov 20 at 13:51
|
show 11 more comments
1 Answer
1
active
oldest
votes
up vote
1
down vote
accepted
In pandas non scalar values are poorly supported - many function should failed.
Solution is convert to list for list of dictionary:
jsonCol = 'j'
exampleKey = 'key'
AreasDict= {'4G NeVe': 0, '4G FT ET': 400, '4G C-Plane': 800, 'MANO BTSSM': 0}
column_names = ['issue_key', jsonCol]
df = pd.DataFrame(index=range(1,2), columns=column_names)
df.iloc[0, 0] = exampleKey
df.iloc[0, 1] = [AreasDict]
print (df)
issue_key j
1 key [{'4G NeVe': 0, '4G FT ET': 400, '4G C-Plane':...
answered Nov 20 at 9:43
jezrael
315k22256333
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
up vote
1
down vote
accepted
In pandas non scalar values are poorly supported - many function should failed.
Solution is convert to list for list of dictionary:
jsonCol = 'j'
exampleKey = 'key'
AreasDict= {'4G NeVe': 0, '4G FT ET': 400, '4G C-Plane': 800, 'MANO BTSSM': 0}
column_names = ['issue_key', jsonCol]
df = pd.DataFrame(index=range(1,2), columns=column_names)
df.iloc[0, 0] = exampleKey
df.iloc[0, 1] = [AreasDict]
print (df)
issue_key j
1 key [{'4G NeVe': 0, '4G FT ET': 400, '4G C-Plane':...
answered Nov 20 at 9:43
jezrael
315k22256333
add a comment |
up vote
1
down vote
accepted
In pandas non scalar values are poorly supported - many function should failed.
Solution is convert to list for list of dictionary:
jsonCol = 'j'
exampleKey = 'key'
AreasDict= {'4G NeVe': 0, '4G FT ET': 400, '4G C-Plane': 800, 'MANO BTSSM': 0}
column_names = ['issue_key', jsonCol]
df = pd.DataFrame(index=range(1,2), columns=column_names)
df.iloc[0, 0] = exampleKey
df.iloc[0, 1] = [AreasDict]
print (df)
issue_key j
1 key [{'4G NeVe': 0, '4G FT ET': 400, '4G C-Plane':...
answered Nov 20 at 9:43
jezrael
315k22256333
add a comment |
up vote
1
down vote
accepted
up vote
1
down vote
accepted
In pandas non scalar values are poorly supported - many function should failed.
Solution is convert to list for list of dictionary:
jsonCol = 'j'
exampleKey = 'key'
AreasDict= {'4G NeVe': 0, '4G FT ET': 400, '4G C-Plane': 800, 'MANO BTSSM': 0}
column_names = ['issue_key', jsonCol]
df = pd.DataFrame(index=range(1,2), columns=column_names)
df.iloc[0, 0] = exampleKey
df.iloc[0, 1] = [AreasDict]
print (df)
issue_key j
1 key [{'4G NeVe': 0, '4G FT ET': 400, '4G C-Plane':...
answered Nov 20 at 9:43
jezrael
315k22256333
In pandas non scalar values are poorly supported - many function should failed.
Solution is convert to list for list of dictionary:
jsonCol = 'j'
exampleKey = 'key'
AreasDict= {'4G NeVe': 0, '4G FT ET': 400, '4G C-Plane': 800, 'MANO BTSSM': 0}
column_names = ['issue_key', jsonCol]
df = pd.DataFrame(index=range(1,2), columns=column_names)
df.iloc[0, 0] = exampleKey
df.iloc[0, 1] = [AreasDict]
print (df)
issue_key j
1 key [{'4G NeVe': 0, '4G FT ET': 400, '4G C-Plane':...
answered Nov 20 at 9:43
jezrael
315k22256333
answered Nov 20 at 9:43
jezrael
315k22256333
answered Nov 20 at 9:43
jezrael
315k22256333
answered Nov 20 at 9:43
jezrael
315k22256333
315k22256333
add a comment |
add a comment |
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1
Problem is in pandas is not recomended store dicts in DataFrame column, but one possible solution is use
df.iloc[0, 1] = [AreasDict]– jezrael
Nov 20 at 9:04
Yes, that turns it into class 'list' !! I'll try that in my project that calls the function using it and let you know.
– Joe Phi
Nov 20 at 9:09
So it working for you nice? It is what you need?
– jezrael
Nov 20 at 9:10
1
I still have to try that principle in my 'real' project that calls the shared function and see if that function eats it.Will let you know.
– Joe Phi
Nov 20 at 9:11
1
the workaround? this one:
if isinstance(AreasDict, str) : then AreasDict = ast.literal_eval(AreasDict– Joe Phi
Nov 20 at 13:51