Extract column namd and data from json

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ShambhuRai-4099 asked May 4, '22 ShambhuRai-4099 answered May 5, '22

Extract column namd and data from json

Hi Expert,

I getting data in unstructured format via exporting json from azure form. How to extract it using column name and data

 {"status":"succeeded","createdDateTime":"2022-05-02T08:55:55Z","lastUpdatedDateTime":"2022-05-02T08:56:05Z","analyzeResult":{"version":"2.1.0","readResults":[{"page":1,"angle":0,"width":11.6806,"height":8.2639,"unit":"inch","lines":[{"boundingBox":[0.2079,0.8619,1.673,0.8517,1.6781,1.1357,0.2079,1.1458],"text":"intertek","appearance":{"style":{"name":"other","confidence":0.878}},"words":[{"boundingBox":[0.2079,0.872,1.5665,0.8568,1.5716,1.1407,0.2079,1.1458],"text":"intertek","confidence":0.985}]},{"boundingBox":[4.6587,1.0541,9.3281,1.0541,9.3281,1.16,4.6587,1.16],"text":" QUALITY REPORT  IN SEPTEMBER 2020","appearance":{"style":{"name":"other","confidence":1}},"words":[{"text":"QUALITY","confidence":1},{"boundingBox":[6.3762,1.0541,6.8301,1.0541,6.8301,1.1456,6.3762,1.1456],"text":"REPORT","confidence":1},{"boundingBox":[6.8726,1.0541,7.0978,1.0541,7.0978,1.1456,6.8726,1.1456],"text":"FOR","confidence":1},{"boundingBox":[7.1344,1.0541,7.6076,1.0541,7.6076,1.1456,7.1344,1.1456],"text":"VESSELS","confidence":1},{"boundingBox":[7.6534,1.0541,8.1233,1.0541,8.1233,1.1456,7.6534,1.1456],"text":"LOADED","confidence":1},{"boundingBox":[8.1696,1.0553,8.2799,1.0553,8.2799,1.1444,8.1696,1.1444],"text":"IN","confidence":1},{"boundingBox":[8.3246,1.0541,9.012,1.0541,9.012,1.1456,8.3246,1.1456],"text":"SEPTEMBER","confidence":1},{"boundingBox":[9.0524,1.0541,9.3281,1.0541,9.3281,1.1456,9.0524,1.1456],"text":"2020","confidence":1}]},{"boundingBox":}],"errors":[]}}

could you please help with Pycode to extract column name and from it

azure-form-recognizer

· 1

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GiftA-MSFT · May 04 at 06:03 PM

Hi, thanks for reaching out. This blog tutorial may be useful for your scenario and includes sample code. You can also try using JSONPath python library, here's an example. Please check them out.

0 ·

Answer 1 · 2022-05-05T18:52:03.58Z

ShambhuRai-4099 answered May 5, '22

have used the above option and getting below output

{
"status": "success",
"pages": [
{
"number": 1,
"height": 841,
"width": 595,
"clusterId": 0,
"keyValuePairs": [
{
"key": [
{
"text": "XXXXX",
"boundingBox": [
415.3,
778.6,
564.5,
778.6,
564.5,
765.4,
415.3,
765.4
]
}
],
"value": []
},
{
"key": [
{
"text": "Abendmarkt 2",
"boundingBox": [
81.0,
681.3,
137.5,
681.3,
137.5,
672.6,
81.0,
672.6
]
}
],
"value": [
{
"text": "XXXX",
"boundingBox": [
80.7,
670.6,
151.1,
670.6,
151.1,
661.1,
80.7,
661.1
],
"confidence": 1.0
}
]
},
{
"key": [
{
"text": "Datum:",
"boundingBox": [
361.1,
635.0,
393.4,
635.0,
393.4,
625.5,
361.1,
625.5
]
}
],
"value": [
{
"text": "27.06.2019",
"boundingBox": [
489.5,
635.2,
539.0,
635.2,
539.0,
625.5,
489.5,
625.5
],
"confidence": 1.0
}
]
},

          ],
         "tables": []
     }
 ],
 "errors": []

}

How to parse data from this to get proper table structure

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