Extract data from a pandas series if the values are in a dictionary-like format
I try the solution in Extracting dictionary values from a pandas dataframe But it didn't work.
I have a pandas.core.series.Series with the following general format:
0 {'hashtags': , 'symbols': , 'user_mentions...
1 {'hashtags': , 'symbols': , 'user_mentions...
2 {'hashtags': , 'symbols': , 'user_mentions...
3 {'hashtags': , 'symbols': , 'user_mentions...
...
the specific format of each one is similar to the following:
{'hashtags': ,
'symbols': ,
'user_mentions': [{'screen_name': 'jose_m',
'id_str': '132',
'name': 'Jose',
'indices': [0, 10],
'id': 103},
{'screen_name': 'paul',
'id_str': '243403',
'name': 'Jorge',
'indices': [50, 64],
'id': 2423}],
'urls': }
I get that by placing the index zero to the variable entities[0] (Index may change).
I need to extract extract all the screen_name and name inside user_mentions. Thanks :)
python pandas
asked Nov 23 '18 at 1:48
Ricardo PrietoRicardo Prieto
154
add a comment |
I try the solution in Extracting dictionary values from a pandas dataframe But it didn't work.
I have a pandas.core.series.Series with the following general format:
0 {'hashtags': , 'symbols': , 'user_mentions...
1 {'hashtags': , 'symbols': , 'user_mentions...
2 {'hashtags': , 'symbols': , 'user_mentions...
3 {'hashtags': , 'symbols': , 'user_mentions...
...
the specific format of each one is similar to the following:
{'hashtags': ,
'symbols': ,
'user_mentions': [{'screen_name': 'jose_m',
'id_str': '132',
'name': 'Jose',
'indices': [0, 10],
'id': 103},
{'screen_name': 'paul',
'id_str': '243403',
'name': 'Jorge',
'indices': [50, 64],
'id': 2423}],
'urls': }
I get that by placing the index zero to the variable entities[0] (Index may change).
I need to extract extract all the screen_name and name inside user_mentions. Thanks :)
python pandas
asked Nov 23 '18 at 1:48
Ricardo PrietoRicardo Prieto
154
add a comment |
I try the solution in Extracting dictionary values from a pandas dataframe But it didn't work.
I have a pandas.core.series.Series with the following general format:
0 {'hashtags': , 'symbols': , 'user_mentions...
1 {'hashtags': , 'symbols': , 'user_mentions...
2 {'hashtags': , 'symbols': , 'user_mentions...
3 {'hashtags': , 'symbols': , 'user_mentions...
...
the specific format of each one is similar to the following:
{'hashtags': ,
'symbols': ,
'user_mentions': [{'screen_name': 'jose_m',
'id_str': '132',
'name': 'Jose',
'indices': [0, 10],
'id': 103},
{'screen_name': 'paul',
'id_str': '243403',
'name': 'Jorge',
'indices': [50, 64],
'id': 2423}],
'urls': }
I get that by placing the index zero to the variable entities[0] (Index may change).
I need to extract extract all the screen_name and name inside user_mentions. Thanks :)
python pandas
asked Nov 23 '18 at 1:48
Ricardo PrietoRicardo Prieto
154
I try the solution in Extracting dictionary values from a pandas dataframe But it didn't work.
I have a pandas.core.series.Series with the following general format:
0 {'hashtags': , 'symbols': , 'user_mentions...
1 {'hashtags': , 'symbols': , 'user_mentions...
2 {'hashtags': , 'symbols': , 'user_mentions...
3 {'hashtags': , 'symbols': , 'user_mentions...
...
the specific format of each one is similar to the following:
{'hashtags': ,
'symbols': ,
'user_mentions': [{'screen_name': 'jose_m',
'id_str': '132',
'name': 'Jose',
'indices': [0, 10],
'id': 103},
{'screen_name': 'paul',
'id_str': '243403',
'name': 'Jorge',
'indices': [50, 64],
'id': 2423}],
'urls': }
I get that by placing the index zero to the variable entities[0] (Index may change).
I need to extract extract all the screen_name and name inside user_mentions. Thanks :)
python pandas
python pandas
asked Nov 23 '18 at 1:48
Ricardo PrietoRicardo Prieto
154
asked Nov 23 '18 at 1:48
Ricardo PrietoRicardo Prieto
154
asked Nov 23 '18 at 1:48
Ricardo PrietoRicardo Prieto
154
asked Nov 23 '18 at 1:48
Ricardo PrietoRicardo Prieto
154
asked Nov 23 '18 at 1:48
Ricardo PrietoRicardo Prieto
154
154
add a comment |
add a comment |
1 Answer
1
active
oldest
votes
Here is an example with apply, for each entities returns a list with a tuple for each user_mention:
def find_user_mention(user_mention):
return (user_mention['screen_name'], user_mention['name'])
df['entities'].apply(lambda x: [find_user_mention(user_mention) for user_mention in x['user_mentions']])
Example output with random data:
0 [(NunkMasKKs, 🍣 SUSHIPLANERO 🍣)]
1 [(leobilanski, Leo Bilanski)]
2 [(romerodiario, El Profe Romero)]
3 [(HugoYasky, Hugo Yasky)]
4 [(marianorecalde, Mariano Recalde)]
5 [(cyngarciaradio, Cynthia García)]
answered Nov 23 '18 at 2:36
LucasLucas
2,35211128
Great! thank you very much
– Ricardo Prieto
Nov 23 '18 at 2:50
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
Here is an example with apply, for each entities returns a list with a tuple for each user_mention:
def find_user_mention(user_mention):
return (user_mention['screen_name'], user_mention['name'])
df['entities'].apply(lambda x: [find_user_mention(user_mention) for user_mention in x['user_mentions']])
Example output with random data:
0 [(NunkMasKKs, 🍣 SUSHIPLANERO 🍣)]
1 [(leobilanski, Leo Bilanski)]
2 [(romerodiario, El Profe Romero)]
3 [(HugoYasky, Hugo Yasky)]
4 [(marianorecalde, Mariano Recalde)]
5 [(cyngarciaradio, Cynthia García)]
answered Nov 23 '18 at 2:36
LucasLucas
2,35211128
Great! thank you very much
– Ricardo Prieto
Nov 23 '18 at 2:50
add a comment |
Here is an example with apply, for each entities returns a list with a tuple for each user_mention:
def find_user_mention(user_mention):
return (user_mention['screen_name'], user_mention['name'])
df['entities'].apply(lambda x: [find_user_mention(user_mention) for user_mention in x['user_mentions']])
Example output with random data:
0 [(NunkMasKKs, 🍣 SUSHIPLANERO 🍣)]
1 [(leobilanski, Leo Bilanski)]
2 [(romerodiario, El Profe Romero)]
3 [(HugoYasky, Hugo Yasky)]
4 [(marianorecalde, Mariano Recalde)]
5 [(cyngarciaradio, Cynthia García)]
answered Nov 23 '18 at 2:36
LucasLucas
2,35211128
Great! thank you very much
– Ricardo Prieto
Nov 23 '18 at 2:50
add a comment |
Here is an example with apply, for each entities returns a list with a tuple for each user_mention:
def find_user_mention(user_mention):
return (user_mention['screen_name'], user_mention['name'])
df['entities'].apply(lambda x: [find_user_mention(user_mention) for user_mention in x['user_mentions']])
Example output with random data:
0 [(NunkMasKKs, 🍣 SUSHIPLANERO 🍣)]
1 [(leobilanski, Leo Bilanski)]
2 [(romerodiario, El Profe Romero)]
3 [(HugoYasky, Hugo Yasky)]
4 [(marianorecalde, Mariano Recalde)]
5 [(cyngarciaradio, Cynthia García)]
answered Nov 23 '18 at 2:36
LucasLucas
2,35211128
Here is an example with apply, for each entities returns a list with a tuple for each user_mention:
def find_user_mention(user_mention):
return (user_mention['screen_name'], user_mention['name'])
df['entities'].apply(lambda x: [find_user_mention(user_mention) for user_mention in x['user_mentions']])
Example output with random data:
0 [(NunkMasKKs, 🍣 SUSHIPLANERO 🍣)]
1 [(leobilanski, Leo Bilanski)]
2 [(romerodiario, El Profe Romero)]
3 [(HugoYasky, Hugo Yasky)]
4 [(marianorecalde, Mariano Recalde)]
5 [(cyngarciaradio, Cynthia García)]
answered Nov 23 '18 at 2:36
LucasLucas
2,35211128
answered Nov 23 '18 at 2:36
LucasLucas
2,35211128
answered Nov 23 '18 at 2:36
LucasLucas
2,35211128
answered Nov 23 '18 at 2:36
LucasLucas
2,35211128
2,35211128
Great! thank you very much
– Ricardo Prieto
Nov 23 '18 at 2:50
add a comment |
Great! thank you very much
– Ricardo Prieto
Nov 23 '18 at 2:50
Great! thank you very much
– Ricardo Prieto
Nov 23 '18 at 2:50
Great! thank you very much
– Ricardo Prieto
Nov 23 '18 at 2:50
add a comment |
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