JSON array keyerror in Python - arrays

Question

I'm fairly new to Python programming and am attempting to extract data from a JSON array. Below code results in an error for
js[jstring][jkeys]['5. volume'])
Any help would be much appreciated.
import urllib.request, urllib.parse, urllib.error
import json
def DailyData(symb):
url = https://www.alphavantage.co/queryfunction=TIME_SERIES_DAILY&symbol=MSFT&apikey=demo
stockdata = urllib.request.urlopen(url)
data = stockdata.read().decode()
try:
js = json.loads(data)
except:
js = None
jstring = 'Time Series (Daily)'
for entry in js:
i = js[jstring].keys()
for jkeys in i:
return (jkeys,
js[jstring][jkeys]['1. open'],
js[jstring][jkeys]['2. high'],
js[jstring][jkeys]['3. low'],
js[jstring][jkeys]['4. close'],
js[jstring][jkeys]['5. volume'])
print('volume',DailyData(symbol)[5])

Answer 1

Looks like the reason for the error is because the returned data from the URL is a bit more hierarchical than you may realize. To see that, print out js (I recommend using a jupyter notebook):
import urllib.request, urllib.parse, urllib.error
import ssl
import json
import sqlite3
url = "https://www.alphavantage.co/query?function=TIME_SERIES_DAILY&symbol=MSFT&apikey=demo"
stockdata = urllib.request.urlopen(url)
data = stockdata.read().decode()
js = json.loads(data)
js
You can see that js (now a python dict) has a "Meta Data" key before the actual time series begins. You need to start operating on the dict at that key.
Having said that, to get the data into a table like structure (for plotting, time series analysis, etc), you can use pandas package to read the dict key directly into a dataframe. The pandas DataFrame constructor accepts a dict as input. In this case, the data was transposed, so the T at the end rotates it (try with and without the T and you will see it.
import pandas as pd
df=pd.DataFrame(js['Time Series (Daily)']).T
df
Added edit... You could get the data into a dataframe with a single line of code:
import requests
import pandas as pd
url = "https://www.alphavantage.co/query?function=TIME_SERIES_DAILY&symbol=MSFT&apikey=demo"
data = pd.DataFrame(requests.get(url).json()['Time Series (Daily)']).T
DataFrame: The contructor from Pandas to make data into a table like structure
requests.get(): method from the requests library to fetch data..
.json(): directly converts from JSON to a dict
['Time Series (Daily)']: pulls out the key from the dict that is the time series
.T: transposes the rows and columns.
Good luck!
Following code worked for me
import urllib.request, urllib.parse, urllib.error
import json
def DailyData(symb):
# Your code was missing the ? after query
url = "https://www.alphavantage.co/query?function=TIME_SERIES_DAILY&symbol={}&apikey=demo".format(symb)
stockdata = urllib.request.urlopen(url)
data = stockdata.read().decode()
js = json.loads(data)
jstring = 'Time Series (Daily)'
for entry in js:
i = js[jstring].keys()
for jkeys in i:
return (jkeys,
js[jstring][jkeys]['1. open'],
js[jstring][jkeys]['2. high'],
js[jstring][jkeys]['3. low'],
js[jstring][jkeys]['4. close'],
js[jstring][jkeys]['5. volume'])
# query multiple times, just to print one item?
print('open',DailyData('MSFT')[1])
print('high',DailyData('MSFT')[2])
print('low',DailyData('MSFT')[3])
print('close',DailyData('MSFT')[4])
print('volume',DailyData('MSFT')[5])
Output:
open 99.8850
high 101.4300
low 99.6700
close 101.1600
volume 19234627
Without seeing the error, it's hard to know what exact problem you were having.