CODEWITHSUNDEEP
python-3.xapipandasdata-science
bbartling
bbartling

Reputation: 3494

Python TypeError: unhashable type: 'dict'

I am attempting to use an API request to gather weather data and ultimately save the data to a CSV file with pandas.to_csv. The API request is working, but I get this error when I am trying to convert the API response from a dictionary to pandas. Any tips for what I am doing wrong is greatly appreciated:

TypeError: unhashable type: 'dict'

The last line in the code is what is messed up and the shell is returning an error:

from urllib.request import urlopen
import json
import pandas as pd

api_key = ""
date = "20170601"
zip_code = "53711"

response = urlopen("http://api.wunderground.com/api/%s/history_%s/q/%s.json"     % (api_key, date, zip_code))

json_data = response.read().decode('utf-8', 'replace')

data = json.loads(json_data)

for observation in data['history']['observations']:
     print("Date/Time:    " + observation['date']['pretty'])
     print("Temperature:  " + observation['tempi'])
     print("Humidity:     " + observation['hum'])

df = pd.DataFrame([data], columns=data.keys())

The screen shot is what the data looks like in the shell output: enter image description here

Upvotes: 2

Views: 1878

Answers (1)

jezrael
jezrael

Reputation: 862511

You can use json_normalize with filtering columns, also is possible convert date column to_datetime:

from pandas.io.json import json_normalize

df = json_normalize(data['history']['observations'])

df = df[['date.pretty','tempi','hum']]
df['date.pretty'] = pd.to_datetime(df['date.pretty'])
print (df.head())
          date.pretty tempi hum
0 2017-06-01 00:15:00  49.8  83
1 2017-06-01 00:35:00  50.0  82
2 2017-06-01 00:55:00  49.1  85
3 2017-06-01 01:15:00  49.3  83
4 2017-06-01 01:35:00  48.2  85

Upvotes: 1

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