how to enable secondary y axis in plotly & get better visuals

kbsudhir Published at Dev

kbsudhir

I am creating OHLC graphs using plotly with and add line chart to the same plot to showcase Moving averages & RSI which can be enabled or disabled by clicking on legend.

I am using tutorial provided in the below link Below code creates the required charts

#https://chart-studio.plotly.com/~jackp/17421/plotly-candlestick-chart-in-python/#/

import time


Mstart = time.process_time()

import plotly.graph_objects as go
from plotly.subplots import make_subplots
import plotly.io as pio


from plotly.offline import iplot
# Calling Numpy package to manipulate numbers
import numpy as np

# Calling Pandas to create dataframe 
import pandas as pd

#importing ta-lib to calculate Technical indicators
import talib as ta

import datetime
from datetime import date as dt


# ----------------------- Loading data from csv file --------------------------------

VipData = pd.read_csv(r"C:\xxxxxxxx\data.csv")



#  ---------------------------   Generating Technical indicator features --------------------------
VipData['RSI7']= ta.RSI(VipData['Close'].values, timeperiod=7)

def bbp(price):
    #print(price)
    up, mid, low = ta.BBANDS(price, timeperiod=20, nbdevup=2, nbdevdn=2, matype=0)
    bbp = (VipData['Close'] - low) / (up - low)
    return up, mid, low, bbp

VipData['BB_up'],VipData['BB_mid'],VipData['BB_low'],VipData['BBP']=bbp(VipData.Close)
VipData['AD']=ta.AD(VipData.High, VipData.Low, VipData.Close, VipData.Volume)
VipData['OBV'] = ta.OBV(VipData.Close, VipData.Volume)
VipData['EMA12']=ta.EMA(VipData.Close, timeperiod=12)
VipData['EMA26']=ta.EMA(VipData.Close, timeperiod=26)
VipData['MA10'] = ta.MA(VipData.Close, timeperiod=10, matype=0)
VipData['MA50'] = ta.MA(VipData.Close, timeperiod=50, matype=0)
VipData['MP'] = ta.MIDPOINT(VipData.Close, timeperiod=14)
VipData['SMA10']= ta.SMA(VipData.Close, timeperiod=10)
VipData['SMA42']= ta.SMA(VipData.Close, timeperiod=42)
VipData['ADX'] = ta.ADX(VipData.High, VipData.Low, VipData.Close, timeperiod=14)
VipData['CCI'] = ta.CCI(VipData.High, VipData.Low, VipData.Close, timeperiod=14)

def macd(close):
    macd, macdsignal, macdhist = ta.MACD(close, fastperiod=12, slowperiod=26, signalperiod=9)
    return macd, macdsignal, macdhist

VipData['MACD'],VipData['MACDSig'],VipData['MACDHist'] = macd(VipData.Close)
VipData['MDI'] = ta.MINUS_DI(VipData.High, VipData.Low, VipData.Close, timeperiod=14)
VipData['PDM'] = ta.PLUS_DM(VipData.High, VipData.Low, timeperiod=14)
VipData['ATR'] = ta.ATR(VipData.High, VipData.Low, VipData.Close, timeperiod=14)

#--------------------------- Creating Chart ------------------------------------------------------
Cstart = time.process_time()
fig = make_subplots(specs=[[{"secondary_y": True}]])

INCREASING_COLOR = '#90ee90'
DECREASING_COLOR = '#ff0000'

#Create the layout object
annotations = []
annotations.append(go.layout.Annotation(x= VipData['Datetime'].iloc[VipData['Close'].idxmin()],
                                        y=VipData['Close'].iloc[VipData['Close'].idxmin()],
                                        showarrow=True,
                                        arrowhead=1,
                                        arrowcolor="purple",
                                        arrowsize=2,
                                        arrowwidth=2,
                                        text="Low"))

annotations.append(go.layout.Annotation(x= VipData['Datetime'].iloc[VipData['Close'].idxmax()],
                                        y=VipData['Close'].iloc[VipData['Close'].idxmax()],
                                        showarrow=True,
                                        arrowhead=1,
                                        arrowcolor="purple",
                                        arrowsize=2,
                                        arrowwidth=2,
                                        text="High"))

layout = dict(
        title="VIP Chart",
        xaxis=go.layout.XAxis(title=go.layout.xaxis.Title( text="Time (IST)"), rangeslider=dict (visible = True)),
        yaxis=go.layout.YAxis(title=go.layout.yaxis.Title( text="Price - Indian Rupees"),domain = [0, 0.2]),
        yaxis2 = go.layout.YAxis(domain = [0.2, 0.8],title=go.layout.yaxis.Title( text="Indicator Values")),
        legend = dict(orientation = 'h', y=0.9, x=0.3, yanchor='bottom'),
        margin = dict( t=29, b=20, r=20, l=20 ),
        width=800,
        height=600,
        annotations=annotations
)

#Creating OHLC Chart
data = [ dict(
    type = 'ohlc',
    open = VipData.Open,
    high = VipData.High,
    low = VipData.Low,
    close = VipData.Close,
    x = VipData.Datetime,
    yaxis = 'y2',
    name = 'OHLC',
    increasing = dict( line = dict( color = INCREASING_COLOR ) ),
    decreasing = dict( line = dict( color = DECREASING_COLOR ) ),
) ]

layout=dict()

fig = dict( data=data, layout=layout )

#Adding moving average
fig['data'].append( dict( x=list(VipData.Datetime), y=list(VipData.MA10), type='scatter', mode='lines', 
                         line = dict( width = 1 ),
                         marker = dict( color = '#E377C2' ),
                         yaxis = 'y2', name='Moving Average' ) )

#Add RSI chart
fig['data'].append( dict( x=VipData.Datetime, y=VipData.RSI7,                         
                         marker=dict( color='#000' ),
                         type='scatter', yaxis='y', secondary_y=True, name='RSI' ) )

#Add volume bollinger bands
fig['data'].append( dict( x=VipData.Datetime, y=VipData.BB_up, type='scatter', yaxis='y2', 
                         line = dict( width = 1 ),
                         marker=dict(color='#b41c1c'), hoverinfo='none', 
                         legendgroup='Bollinger Bands', name='Bollinger Bands'))

fig['data'].append( dict( x=VipData.Datetime, y=VipData.BB_low, type='scatter', yaxis='y2',
                         line = dict( width = 1 ),
                         marker=dict(color='#b41c1c'), hoverinfo='none',
                         legendgroup='Bollinger Bands', showlegend=False ))

CRstart = time.process_time()

pio.renderers.default = "browser"

iplot( fig, filename = 'candlestick-test-3', validate = False )
#iplot( fig, validate = False )

Cend = time.process_time()

CRtime = Cend - CRstart
CTime = Cend-Cstart

print(f'Chart rendered in {CRtime} secs')
print(f'Chart created in {CTime} secs')

The charts are getting created but I am getting two problems:

Both Y axis values are coming on the same side, left of the plot how show secondary y axis on the right. Adding image for your reference.
Since this is a intraday data with 1min intervals hence will be dense so when I zoom into the same the candlesticks becomes extremely small. how to increase the size of the same. I understand the OHLC are very near to each other but still, i want to have higher sized candlesticks for better visibility. How can I go about doing the same. Image for your reference

Thanks for your time & efforts for helping me.

Regards Sudhir

r-beginners

It's an interesting question, so I've added a second y-axis setting and a moving average, referring to the official plotly reference. Limiting the period with the slider also expands the candlestick; I didn't see a setting to make the box larger on the plotly candlestick.

import plotly.graph_objects as go
import numpy as np
import pandas as pd
import pandas_datareader.data as web
import datetime
from plotly.subplots import make_subplots


start = datetime.datetime(2018, 1, 1)
end = datetime.datetime(2019, 1, 1)
df = web.DataReader("MSFT", 'yahoo', start, end)
df.reset_index(inplace=True)
# moving average
exp12 = df['Close'].ewm(span=12, adjust=False).mean()
exp26 = df['Close'].ewm(span=26, adjust=False).mean()
macd = exp12 - exp26
signal = macd.ewm(span=9, adjust=False).mean()

# Create figure with secondary y-axis
fig = make_subplots(specs=[[{"secondary_y": True}]])

fig.add_trace(go.Candlestick(x=df['Date'], open=df['Open'], high=df['High'], low=df['Low'], close=df['Close'],
                             yaxis='y1', name='Cnadlestick'))

fig.add_trace(go.Scatter(x=df['Date'], y=exp12, name='Moving Avg 12',
                        line=dict(color='royalblue',width=2)))

fig.add_trace(go.Scatter(x=df['Date'], y=exp26, name='Moving Avg 26',
                        line=dict(color='firebrick',width=2)))

fig.add_trace(go.Bar(x=df['Date'], y=df['Volume'], yaxis='y2', name='Volume'))

# Add figure title
fig.update_layout(
    width=1100,
    height=600,
    title_text="Microsoft Stock",
    yaxis_tickformat='M'
)

fig.update_layout(legend=dict(
    orientation="h",
    yanchor="bottom",
    y=1.02,
    xanchor="right",
    x=1
))

# Set x-axis title
fig.update_xaxes(title_text="Date")

# Set y-axes titles
fig.update_yaxes(title_text="<b>primary</b> Close", secondary_y=False)
fig.update_yaxes(title_text="<b>secondary</b> Volume", range=[0, 300000000], secondary_y=True)

fig.show()

Collected from the Internet

Please contact [email protected] to delete if infringement.

edited at2021-05-30

Comments

0 comments

how to enable secondary y axis in plotly & get better visuals

how to enable secondary y axis in plotly & get better visuals

pump.io port in URL

Failed to listen on localhost:8000 (reason: Cannot assign requested address)

How to import an asset in swift using Bundle.main.path() in a react-native native module

Inner Loop design for webscrapping

Can't pre-populate phone number and message body in SMS link on iPhones when SMS app is not running in the background

ggplotly no applicable method for 'plotly_build' applied to an object of class "NULL" if statements

mysql.connector.errors.InterfaceError: 2003: Can't connect to MySQL server on '127.0.0.1:3306' (111 Connection refused)

Removed zsh, but forgot to change shell back to bash, and now Ubuntu crashes (wsl)

Ambiguous use of 'init' with CFStringTransform and Swift 3

Resetting Value of <input type="time"> in Firefox

Execute ./script.sh with a crontab

Converting a class method to a property with a backing field

Spring Boot JPA PostgreSQL Web App - Internal Authentication Error

How to update azerothcore-wotlk docker container

How to set tab order for array of cluster,where cluster elements have different data types in LabVIEW?

Grails with Oracle thick OCI driver authenticate to Oracle with wrong user

How to pass data to the ng2-bs3-modal?

Making Array From Page Elements in jQuery

Retrieve Element Tag Value XML Using Bash

Laravel's ORM sync with timestamps doesn't update timestamps

Do animations stop css changes after animation completion?