When I run the following code, it runs, however, the middle portion of data from row 5 to row 720 is missing. Where row 5 should appear, the row is filled with dots. See the following code and output:
import pandas as pd
import requests
from pandas.io.json import json_normalize
from config import client_id
stock = "GOOG"
endpoint = r'https://api.tdameritrade.com/v1/marketdata/{}/pricehistory'.format(stock)
payload = {'apikey':client_id,
'periodType': 'day',
'frequencyType': 'minute',
'frequency' :'1',
'period':'2',
'needExtendedHoursData':'true'}
content = requests.get(url = endpoint, params = payload)
data = content.json()
df = pd.json_normalize(data['candles'])
print(df)
#print (data) // If I run this line, it displays all the historical data unformatted.
Output:
open high low close volume datetime
0 2103.0000 2103.0000 2103.00 2103.00 119 1613045160000
1 2106.0000 2106.0000 2106.00 2106.00 118 1613051640000
2 2096.3300 2102.0000 2096.33 2098.04 1400 1613053680000
3 2099.2100 2099.2100 2099.16 2099.16 200 1613053740000
4 2099.1200 2102.0300 2085.62 2090.31 32575 1613053800000
.. ... ... ... ... ... ...
721 2104.6500 2104.6500 2104.00 2104.00 200 1613167200000
722 2104.9900 2104.9900 2104.99 2104.99 300 1613167500000
723 2104.9900 2104.9900 2104.99 2104.99 195 1613167560000
724 2105.9999 2105.9999 2104.99 2104.99 2200 1613167740000
725 2104.1100 2104.1100 2104.11 2104.11 2810 1613167920000
[726 rows x 6 columns]
Could someone point me in the right direction to resolve this issue?
The above code was obtained from How to extract json from nested column to dataframe.
