how to turn Csv data to dictionary-CodePudding

I used pandas to read the csv file and was able to create a dictionary from it but need to create the dictionary as a specific format.

flightinfo = pd.read_csv('flightdata.csv',quotechar='"',names=['starting_airport', 'destination_airport', 'airline', 'time', 'start_state','end_state'], header=None)

flightinfodict = flightinfo.to_dict(orient='records')

this gives the output

[{'starting_airport': 'Hilo International Airport', 'destination_airport': 'Boise Airport ', 'airline': 'delta', 'average_time_taken': 300, 'start_state': 'HAWAII', 'end_state': 'IDAHO'}

but the output i need is

{'Hilo International Airport' : {'destination_airport': 'Boise Airport ', 'airline': 'delta', 'average_time_taken': 300}

how can i modify the code to produce this output

thanks

CodePudding user response：

There may be a more sophisticated way of doing it, but this processing of the record-oriented dict should do the job:

def get_dict_without(d, key_to_remove):
  d.pop(key_to_remove)
  return d


new_flightinfodict = [{rec["starting_airport"]: get_dict_without(rec, "starting_airport")} for rec in flightinfodict]

CodePudding user response：

Set starting_airport as index and use to_dict(orient='index'):

flightinfodict.set_index('starting_airport').to_dict(orient='index')

Output:

{'Hilo International Airport': {'destination_airport': 'Boise Airport ',
  'airline': 'delta',
  'average_time_taken': 300,
  'start_state': 'HAWAII',
  'end_state': 'IDAHO'}}

Or:

df.set_index('starting_airport')[['destination_airport','airline','average_time_taken']].to_dict(orient='index')

since you indicate you need only these three columns in the dict.