how to retrieve data from pandas

Question

I am trying to retrieve the most recent data from the below results.

The code I am running is:

import datetime
from Historic_Crypto import HistoricalData

# Time Setup
now_bsc = datetime.datetime.now()
now = (now_bsc.strftime("%Y-%m-%d-%H-%M"))

start_bsc = (datetime.datetime.now() - datetime.timedelta(minutes=10))
start = (start_bsc.strftime("%Y-%m-%d-%H-%M"))
"""print(start)
print(now)"""

# Pull OHLC Crypto
new = HistoricalData('BTC-USD', 60, start, now).retrieve_data()

print(new)

This is the result

Checking input parameters are in the correct format...
Formatting Dates...
Checking if ticker supplied is available on the CoinBase Pro API...
Connected to the CoinBase Pro API...
Ticker 'BTC-USD' found at the CoinBase Pro API, continuing to extraction...
Data Extracted from API...
                          low      high      open     close     volume
time                                                                  
2021-05-12 21:18:00  54577.75  54641.08  54637.08  54582.91  14.041055
2021-05-12 21:19:00  54572.71  54610.19  54582.91  54599.86   3.327732
2021-05-12 21:20:00  54599.86  54691.49  54599.86  54678.31  17.552511
2021-05-12 21:21:00  54677.93  54725.75  54677.93  54711.22   5.963198
2021-05-12 21:22:00  54703.62  54756.39  54710.24  54753.88  11.564766
2021-05-12 21:23:00  54750.42  54800.47  54753.88  54768.64  13.601058
2021-05-12 21:24:00  54707.11  54768.64  54768.64  54738.99  11.131357
2021-05-12 21:25:00  54499.99  54739.49  54738.89  54669.53  37.366287
2021-05-12 21:26:00  54665.96  54748.10  54665.97  54743.89   7.932319
2021-05-12 21:27:00  54719.23  54752.19  54736.09  54734.70   9.654189
2021-05-12 21:28:00  54719.97  54749.00  54725.91  54748.99   6.386556

Process finished with exit code 0

How do I retrieve the data "low" and "high" for 2021-05-12 21:28:000?

Answer 1

The answer to this ended up being retrieving the items through index location as the columns were not identified. this is done by using .iloc instead of .loc.

low = new.iloc[10, 0]
high = new.iloc[10, 1]

Answer 2

This API returns pandas Dataframe object.

You can use pandas datafram filter options here.

For example:

data = new.loc[(new['time'] == '2021-05-12 21:28:000')]
low = data['low']
high = data['high']

Answer 3

In order to access the time index, you should reset the index:

new.reset_index(drop=False, inplace=True)
low = new[new['time'] <= '2022-04-18 20:11:00']["low"].min()
high = new[new['time'] <= '2022-04-18 20:11:00']["high"].max()

After which, the time column can be used to slice. The above shows how to do this, after which we take the minimum low value prior to the date string, and the maximum high value prior to the date string.