How can I convert a pandas series that contains an array of json dictionaries into a dataframe?
I have a series composed of the following:
[
[{u'edu_location': u'correctly_parsed', u'edu_dates': u'correctly_parsed', u'edu_title': u'missing', u'edu_item': 1, u'edu_school': u'correctly_parsed'}, {u'edu_location': u'not_on_source', u'edu_dates': u'not_on_source', u'edu_title': u'missing', u'edu_item': 2, u'edu_school': u'correctly_parsed'}], :SHOULD BE ITS OWN ROW:
[{u'edu_location': u'correctly_parsed', u'edu_dates': u'correctly_parsed', u'edu_title': u'missing', u'edu_item': 1, u'edu_school': u'correctly_parsed'}] :SHOULD BE ITS OWN ROW:
]
Whats the best way of turning this pandas series into its own df and dynamically renaming the columns with the correspond u'edu_item' value so that they are displayed on one row rather than multiple rows?
pandas
asked Nov 19 at 22:35
Drew Pham
12
add a comment |
I have a series composed of the following:
[
[{u'edu_location': u'correctly_parsed', u'edu_dates': u'correctly_parsed', u'edu_title': u'missing', u'edu_item': 1, u'edu_school': u'correctly_parsed'}, {u'edu_location': u'not_on_source', u'edu_dates': u'not_on_source', u'edu_title': u'missing', u'edu_item': 2, u'edu_school': u'correctly_parsed'}], :SHOULD BE ITS OWN ROW:
[{u'edu_location': u'correctly_parsed', u'edu_dates': u'correctly_parsed', u'edu_title': u'missing', u'edu_item': 1, u'edu_school': u'correctly_parsed'}] :SHOULD BE ITS OWN ROW:
]
Whats the best way of turning this pandas series into its own df and dynamically renaming the columns with the correspond u'edu_item' value so that they are displayed on one row rather than multiple rows?
pandas
asked Nov 19 at 22:35
Drew Pham
12
add a comment |
I have a series composed of the following:
[
[{u'edu_location': u'correctly_parsed', u'edu_dates': u'correctly_parsed', u'edu_title': u'missing', u'edu_item': 1, u'edu_school': u'correctly_parsed'}, {u'edu_location': u'not_on_source', u'edu_dates': u'not_on_source', u'edu_title': u'missing', u'edu_item': 2, u'edu_school': u'correctly_parsed'}], :SHOULD BE ITS OWN ROW:
[{u'edu_location': u'correctly_parsed', u'edu_dates': u'correctly_parsed', u'edu_title': u'missing', u'edu_item': 1, u'edu_school': u'correctly_parsed'}] :SHOULD BE ITS OWN ROW:
]
Whats the best way of turning this pandas series into its own df and dynamically renaming the columns with the correspond u'edu_item' value so that they are displayed on one row rather than multiple rows?
pandas
asked Nov 19 at 22:35
Drew Pham
12
I have a series composed of the following:
[
[{u'edu_location': u'correctly_parsed', u'edu_dates': u'correctly_parsed', u'edu_title': u'missing', u'edu_item': 1, u'edu_school': u'correctly_parsed'}, {u'edu_location': u'not_on_source', u'edu_dates': u'not_on_source', u'edu_title': u'missing', u'edu_item': 2, u'edu_school': u'correctly_parsed'}], :SHOULD BE ITS OWN ROW:
[{u'edu_location': u'correctly_parsed', u'edu_dates': u'correctly_parsed', u'edu_title': u'missing', u'edu_item': 1, u'edu_school': u'correctly_parsed'}] :SHOULD BE ITS OWN ROW:
]
Whats the best way of turning this pandas series into its own df and dynamically renaming the columns with the correspond u'edu_item' value so that they are displayed on one row rather than multiple rows?
pandas
pandas
asked Nov 19 at 22:35
Drew Pham
12
asked Nov 19 at 22:35
Drew Pham
12
edited Nov 19 at 23:03
asked Nov 19 at 22:35
Drew Pham
12
asked Nov 19 at 22:35
Drew Pham
12
asked Nov 19 at 22:35
Drew Pham
12
12
add a comment |
add a comment |
1 Answer
1
active
oldest
votes
If your dataframe looks like this:
>>> df
column
0 [{'work_location': 'correctly_parsed', 'work_c...
Then you can do:
>>> pd.DataFrame(df['column'][0])
work_company work_dates work_description work_experience_item
0 correctly_parsed correctly_parsed correctly_parsed 1.0
1 correctly_parsed correctly_parsed correctly_parsed 2.0
2 correctly_parsed NaN correctly_parsed NaN
work_location work_title
0 correctly_parsed correctly_parsed
1 correctly_parsed correctly_parsed
2 not_on_source NaN
answered Nov 19 at 22:39
sacul
29.9k41740
the issue is that i want all the rows to be actually 1 row for
– Drew Pham
Nov 19 at 22:45
Sorry, I don't understand. Could you post your expected output as an edit to your question?
– sacul
Nov 19 at 22:49
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
If your dataframe looks like this:
>>> df
column
0 [{'work_location': 'correctly_parsed', 'work_c...
Then you can do:
>>> pd.DataFrame(df['column'][0])
work_company work_dates work_description work_experience_item
0 correctly_parsed correctly_parsed correctly_parsed 1.0
1 correctly_parsed correctly_parsed correctly_parsed 2.0
2 correctly_parsed NaN correctly_parsed NaN
work_location work_title
0 correctly_parsed correctly_parsed
1 correctly_parsed correctly_parsed
2 not_on_source NaN
answered Nov 19 at 22:39
sacul
29.9k41740
the issue is that i want all the rows to be actually 1 row for
– Drew Pham
Nov 19 at 22:45
Sorry, I don't understand. Could you post your expected output as an edit to your question?
– sacul
Nov 19 at 22:49
add a comment |
If your dataframe looks like this:
>>> df
column
0 [{'work_location': 'correctly_parsed', 'work_c...
Then you can do:
>>> pd.DataFrame(df['column'][0])
work_company work_dates work_description work_experience_item
0 correctly_parsed correctly_parsed correctly_parsed 1.0
1 correctly_parsed correctly_parsed correctly_parsed 2.0
2 correctly_parsed NaN correctly_parsed NaN
work_location work_title
0 correctly_parsed correctly_parsed
1 correctly_parsed correctly_parsed
2 not_on_source NaN
answered Nov 19 at 22:39
sacul
29.9k41740
the issue is that i want all the rows to be actually 1 row for
– Drew Pham
Nov 19 at 22:45
Sorry, I don't understand. Could you post your expected output as an edit to your question?
– sacul
Nov 19 at 22:49
add a comment |
If your dataframe looks like this:
>>> df
column
0 [{'work_location': 'correctly_parsed', 'work_c...
Then you can do:
>>> pd.DataFrame(df['column'][0])
work_company work_dates work_description work_experience_item
0 correctly_parsed correctly_parsed correctly_parsed 1.0
1 correctly_parsed correctly_parsed correctly_parsed 2.0
2 correctly_parsed NaN correctly_parsed NaN
work_location work_title
0 correctly_parsed correctly_parsed
1 correctly_parsed correctly_parsed
2 not_on_source NaN
answered Nov 19 at 22:39
sacul
29.9k41740
If your dataframe looks like this:
>>> df
column
0 [{'work_location': 'correctly_parsed', 'work_c...
Then you can do:
>>> pd.DataFrame(df['column'][0])
work_company work_dates work_description work_experience_item
0 correctly_parsed correctly_parsed correctly_parsed 1.0
1 correctly_parsed correctly_parsed correctly_parsed 2.0
2 correctly_parsed NaN correctly_parsed NaN
work_location work_title
0 correctly_parsed correctly_parsed
1 correctly_parsed correctly_parsed
2 not_on_source NaN
answered Nov 19 at 22:39
sacul
29.9k41740
answered Nov 19 at 22:39
sacul
29.9k41740
answered Nov 19 at 22:39
sacul
29.9k41740
answered Nov 19 at 22:39
sacul
29.9k41740
29.9k41740
the issue is that i want all the rows to be actually 1 row for
– Drew Pham
Nov 19 at 22:45
Sorry, I don't understand. Could you post your expected output as an edit to your question?
– sacul
Nov 19 at 22:49
add a comment |
the issue is that i want all the rows to be actually 1 row for
– Drew Pham
Nov 19 at 22:45
Sorry, I don't understand. Could you post your expected output as an edit to your question?
– sacul
Nov 19 at 22:49
the issue is that i want all the rows to be actually 1 row for
– Drew Pham
Nov 19 at 22:45
the issue is that i want all the rows to be actually 1 row for
– Drew Pham
Nov 19 at 22:45
Sorry, I don't understand. Could you post your expected output as an edit to your question?
– sacul
Nov 19 at 22:49
Sorry, I don't understand. Could you post your expected output as an edit to your question?
– sacul
Nov 19 at 22:49
add a comment |
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