Dataframe from JSON formatted as text?

up vote
0
down vote

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Is it possible to create a dataframe from JSON formatted as text, not as Python object?

With Python object, I could for example do:

from pandas.io.json import json_normalize
import requests

response = requests.get(url, params).json()
df = json_normalize(response)

but I want to achieve the same with response = requests.get(url,params).text (flattening is not required though).

asked Nov 9 at 17:16

barciewicz

426310

Can you put few lines of the data?
– pygo
Nov 9 at 17:21

@pygo why the list comprehension?
– roganjosh
Nov 9 at 17:24

@pygo I won't be reading JSON from file, I want to put requests.get(url,params).text response into a dataframe.
– barciewicz
Nov 9 at 17:26

@barciewicz, yes got it thats y i said i misread tehe question sorry :-)
– pygo
Nov 9 at 17:28

Is the .text guaranteed to be valid JSON string?
– Idlehands
Nov 9 at 18:37

add a comment |

up vote
0
down vote

favorite

Is it possible to create a dataframe from JSON formatted as text, not as Python object?

With Python object, I could for example do:

from pandas.io.json import json_normalize
import requests

response = requests.get(url, params).json()
df = json_normalize(response)

but I want to achieve the same with response = requests.get(url,params).text (flattening is not required though).

asked Nov 9 at 17:16

barciewicz

426310

Can you put few lines of the data?
– pygo
Nov 9 at 17:21

@pygo why the list comprehension?
– roganjosh
Nov 9 at 17:24

@pygo I won't be reading JSON from file, I want to put requests.get(url,params).text response into a dataframe.
– barciewicz
Nov 9 at 17:26

@barciewicz, yes got it thats y i said i misread tehe question sorry :-)
– pygo
Nov 9 at 17:28

Is the .text guaranteed to be valid JSON string?
– Idlehands
Nov 9 at 18:37

add a comment |

up vote
0
down vote

favorite

Is it possible to create a dataframe from JSON formatted as text, not as Python object?

With Python object, I could for example do:

from pandas.io.json import json_normalize
import requests

response = requests.get(url, params).json()
df = json_normalize(response)

but I want to achieve the same with response = requests.get(url,params).text (flattening is not required though).

asked Nov 9 at 17:16

barciewicz

426310

Is it possible to create a dataframe from JSON formatted as text, not as Python object?

With Python object, I could for example do:

from pandas.io.json import json_normalize
import requests

response = requests.get(url, params).json()
df = json_normalize(response)

but I want to achieve the same with response = requests.get(url,params).text (flattening is not required though).

python json pandas dataframe

asked Nov 9 at 17:16

barciewicz

426310

asked Nov 9 at 17:16

barciewicz

426310

asked Nov 9 at 17:16

barciewicz

426310

asked Nov 9 at 17:16

barciewicz

426310

asked Nov 9 at 17:16

barciewicz

426310

Can you put few lines of the data?
– pygo
Nov 9 at 17:21

@pygo why the list comprehension?
– roganjosh
Nov 9 at 17:24

@pygo I won't be reading JSON from file, I want to put requests.get(url,params).text response into a dataframe.
– barciewicz
Nov 9 at 17:26

@barciewicz, yes got it thats y i said i misread tehe question sorry :-)
– pygo
Nov 9 at 17:28

Is the .text guaranteed to be valid JSON string?
– Idlehands
Nov 9 at 18:37

add a comment |

Can you put few lines of the data?
– pygo
Nov 9 at 17:21

@pygo why the list comprehension?
– roganjosh
Nov 9 at 17:24

@pygo I won't be reading JSON from file, I want to put requests.get(url,params).text response into a dataframe.
– barciewicz
Nov 9 at 17:26

@barciewicz, yes got it thats y i said i misread tehe question sorry :-)
– pygo
Nov 9 at 17:28

Is the .text guaranteed to be valid JSON string?
– Idlehands
Nov 9 at 18:37

Can you put few lines of the data?
– pygo
Nov 9 at 17:21

@pygo why the list comprehension?
– roganjosh
Nov 9 at 17:24

@pygo I won't be reading JSON from file, I want to put requests.get(url,params).text response into a dataframe.
– barciewicz
Nov 9 at 17:26

@barciewicz, yes got it thats y i said i misread tehe question sorry :-)
– pygo
Nov 9 at 17:28

Is the .text guaranteed to be valid JSON string?
– Idlehands
Nov 9 at 18:37

add a comment |

2 Answers
2

active

oldest

votes

up vote
0
down vote

I usually create dataframe from json using "read_json"

import pandas as pd
import requests

data = requests.get(url, params).content
df = pd.read_json(data)
df.head()

answered Nov 9 at 17:30

lfkopp

692

Thanks, sadly this gives me ValueError: arrays must all be same length at read_json line, I guess because my JSON is nested. Do you know how to work around it?
– barciewicz
Nov 9 at 18:01

replace read_json line by: from pandas.io.json import json_normalize, loads df = json_normalize(loads(data))
– lfkopp
Nov 10 at 1:09

add a comment |

up vote
0
down vote

If your response = requests.get(url,params).text is guaranteed to give you a valid JSON string, then all you need to do is as follows:

from pandas.io.json import json_normalize, loads
import requests

response = requests.get(url, params).text
df = json_normalize(loads(response))

Here we make use of json's loads to convert the JSON string to a Python object before passing back to json_normalize.

answered Nov 9 at 18:39

Idlehands

3,2901316

add a comment |

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2 Answers
2

active

oldest

votes

2 Answers
2

active

oldest

votes

up vote
0
down vote

I usually create dataframe from json using "read_json"

import pandas as pd
import requests

data = requests.get(url, params).content
df = pd.read_json(data)
df.head()

answered Nov 9 at 17:30

lfkopp

692

Thanks, sadly this gives me ValueError: arrays must all be same length at read_json line, I guess because my JSON is nested. Do you know how to work around it?
– barciewicz
Nov 9 at 18:01

replace read_json line by: from pandas.io.json import json_normalize, loads df = json_normalize(loads(data))
– lfkopp
Nov 10 at 1:09

add a comment |

up vote
0
down vote

I usually create dataframe from json using "read_json"

import pandas as pd
import requests

data = requests.get(url, params).content
df = pd.read_json(data)
df.head()

answered Nov 9 at 17:30

lfkopp

692

Thanks, sadly this gives me ValueError: arrays must all be same length at read_json line, I guess because my JSON is nested. Do you know how to work around it?
– barciewicz
Nov 9 at 18:01

replace read_json line by: from pandas.io.json import json_normalize, loads df = json_normalize(loads(data))
– lfkopp
Nov 10 at 1:09

add a comment |

up vote
0
down vote

I usually create dataframe from json using "read_json"

import pandas as pd
import requests

data = requests.get(url, params).content
df = pd.read_json(data)
df.head()

answered Nov 9 at 17:30

lfkopp

692

I usually create dataframe from json using "read_json"

import pandas as pd
import requests

data = requests.get(url, params).content
df = pd.read_json(data)
df.head()

answered Nov 9 at 17:30

lfkopp

692

answered Nov 9 at 17:30

lfkopp

692

answered Nov 9 at 17:30

lfkopp

692

answered Nov 9 at 17:30

lfkopp

692

Thanks, sadly this gives me ValueError: arrays must all be same length at read_json line, I guess because my JSON is nested. Do you know how to work around it?
– barciewicz
Nov 9 at 18:01

replace read_json line by: from pandas.io.json import json_normalize, loads df = json_normalize(loads(data))
– lfkopp
Nov 10 at 1:09

add a comment |

Thanks, sadly this gives me ValueError: arrays must all be same length at read_json line, I guess because my JSON is nested. Do you know how to work around it?
– barciewicz
Nov 9 at 18:01

replace read_json line by: from pandas.io.json import json_normalize, loads df = json_normalize(loads(data))
– lfkopp
Nov 10 at 1:09

Thanks, sadly this gives me ValueError: arrays must all be same length at read_json line, I guess because my JSON is nested. Do you know how to work around it?
– barciewicz
Nov 9 at 18:01

replace read_json line by: from pandas.io.json import json_normalize, loads df = json_normalize(loads(data))
– lfkopp
Nov 10 at 1:09

add a comment |

up vote
0
down vote

If your response = requests.get(url,params).text is guaranteed to give you a valid JSON string, then all you need to do is as follows:

from pandas.io.json import json_normalize, loads
import requests

response = requests.get(url, params).text
df = json_normalize(loads(response))

Here we make use of json's loads to convert the JSON string to a Python object before passing back to json_normalize.

answered Nov 9 at 18:39

Idlehands

3,2901316

add a comment |

up vote
0
down vote

If your response = requests.get(url,params).text is guaranteed to give you a valid JSON string, then all you need to do is as follows:

from pandas.io.json import json_normalize, loads
import requests

response = requests.get(url, params).text
df = json_normalize(loads(response))

Here we make use of json's loads to convert the JSON string to a Python object before passing back to json_normalize.

answered Nov 9 at 18:39

Idlehands

3,2901316

add a comment |

up vote
0
down vote

If your response = requests.get(url,params).text is guaranteed to give you a valid JSON string, then all you need to do is as follows:

from pandas.io.json import json_normalize, loads
import requests

response = requests.get(url, params).text
df = json_normalize(loads(response))

Here we make use of json's loads to convert the JSON string to a Python object before passing back to json_normalize.

answered Nov 9 at 18:39

Idlehands

3,2901316

If your response = requests.get(url,params).text is guaranteed to give you a valid JSON string, then all you need to do is as follows:

from pandas.io.json import json_normalize, loads
import requests

response = requests.get(url, params).text
df = json_normalize(loads(response))

Here we make use of json's loads to convert the JSON string to a Python object before passing back to json_normalize.

answered Nov 9 at 18:39

Idlehands

3,2901316

answered Nov 9 at 18:39

Idlehands

3,2901316

answered Nov 9 at 18:39

Idlehands

3,2901316

answered Nov 9 at 18:39

Idlehands

3,2901316

add a comment |

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