Polygon minute-bar data

Table of contents

• Retrieve minute bar data from the Polygon REST API
• Put response into a pd.DataFrame
• Visualize Data

Retrieve minute bar data from the Polygon REST API

Retrieve minute bar data for AAPL on 2020-05-04

import requests
import json
import time
import pandas as pd
import pytz
from datetime import datetime

# retrieve alpaca keys
%run alpaca_keys.py

ticker = 'AAPL'
multiplier = '1'
date_start = '2020-05-04'
date_end = '2020-05-04'
timespan = 'minute'

request_string = (
    f'https://api.polygon.io/v2/aggs/ticker/{ticker}'
    f'/range/{multiplier}/{timespan}/{date_start}/{date_end}'
    f'?apiKey={KEY_ID}'
)

r = requests.get(request_string)

Put response into a pandas DataFrame

Insert into dataframe with a pd.Timestamp index (in the EST timezone)

df = pd.DataFrame(r.json()['results'])

est = pytz.timezone('US/Eastern')
utc = pytz.utc
# convert index time UTC to EST
df.index = [datetime.utcfromtimestamp(ts / 1000.).replace(tzinfo=utc).astimezone(est) for ts in df['t']]
df.index.name = 'Date'
df.head()

	v	vw	o	c	h	l	t	n
Date
2020-05-04 04:00:00-04:00	4972.0	72.0518	72.0625	72.0625	72.0625	72.0625	1588579200000	10
2020-05-04 04:01:00-04:00	3400.0	71.8663	71.8750	71.8700	71.8750	71.8425	1588579260000	12
2020-05-04 04:02:00-04:00	2144.0	71.8106	71.7875	71.7875	71.7875	71.7875	1588579320000	18
2020-05-04 04:03:00-04:00	1836.0	71.9074	71.9850	71.9850	71.9850	71.9850	1588579380000	8
2020-05-04 04:05:00-04:00	1476.0	71.9960	72.0000	72.0000	72.0000	72.0000	1588579500000	5

Visualize data

Plot minute bars during the last two hours of trading hours

import matplotlib.pyplot as plt
import mplfinance as mpf
%matplotlib inline

df.columns = ['Volume', 'Volume Weighted', 'Open', 'Close', 'High', 'Low', 'Time', 'Num Trades']
mpf.plot(
    df['2020-05-04 14:00:00-04:00':'2020-05-04 16:00:00-04:00'], 
    type='candle',
    volume=True
)