full_live_graph.py

# Raw Package
import numpy as np
import pandas as pd

#Data Source
import yfinance as yf

#Data viz
import plotly.graph_objs as go

data = yf.download(tickers='SPY', period='1d', interval='1m')
#Interval required 1 minute
data['Middle Band'] = data['Close'].rolling(window=21).mean()
data['Upper Band'] = data['Middle Band'] + 1.96*data['Close'].rolling(window=21).std()
data['Lower Band'] = data['Middle Band'] - 1.96*data['Close'].rolling(window=21).std()

#declare figure
fig = go.Figure()

fig.add_trace(go.Scatter(x=data.index, y= data['Middle Band'],line=dict(color='blue', width=.7), name = 'Middle Band'))
fig.add_trace(go.Scatter(x=data.index, y= data['Upper Band'],line=dict(color='red', width=1.5), name = 'Upper Band (Sell)'))
fig.add_trace(go.Scatter(x=data.index, y= data['Lower Band'],line=dict(color='green', width=1.5), name = 'Lower Band (Buy)'))


#Candlestick
fig.add_trace(go.Candlestick(x=data.index,
                open=data['Open'],
                high=data['High'],
                low=data['Low'],
                close=data['Close'], name = 'market data'))

# Add titles
fig.update_layout(
    title='SPY live share price evolution',
    yaxis_title='Stock Price (USD per Shares)')

# X-Axes
fig.update_xaxes(
    rangeslider_visible=True,
    rangeselector=dict(
        buttons=list([
            dict(count=15, label="15m", step="minute", stepmode="backward"),
            dict(count=45, label="45m", step="minute", stepmode="backward"),
            dict(count=1, label="HTD", step="hour", stepmode="todate"),
            dict(count=3, label="3h", step="hour", stepmode="backward"),
            dict(step="all")
        ])
    )
)

#Show
fig.show()