CODEWITHSUNDEEP
pythonpandasdataframe
Connor
Connor

Reputation: 423

Add unpacked json data to an existing dataframe

I have an initial df that looks like:

id title urls
1 title1 www.url1.com
2 title2 www.url2.com

I would like to use apply or some loop that can take each row and after an api call unpack a json blob into new column data for each row...

for r in df:
    json_blob = make_api_call(r.urls)
    # take json blob and put into df?
    pd.read_json(json_blob)
    # add to row r back in the original df?

Such that given the api data ->

{
  "validThrough": "2022-10-16",
  "description": "this and that",
  "Location": {
    "geo": {
      "longitude": "-73.962547",
      "latitude": "40.687089",
      "@type": "GeoCoordinates"
    }
}

df after everything ->

title urls validThrough description Location.geo.longitude Location.geo.latitude Location.geo.@type
0 title1 www.url1.com 2022-10-16 this is a description -73.962547 40.687089 GeoCoordinates
n ...

Upvotes: 0

Views: 152

Answers (1)

Connor
Connor

Reputation: 423

Solved this with

def get_api_data(url):
   json_data = make_req(url)
   # returns a series that apply can use
   return pd.json_normalize(job_info).squeeze()

df1 = df.apply(lambda x: get_api_data(x['url']), axis=1)
df = pd.concat([df, df1], axis=1)

Upvotes: 1

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