Black Lives Matter. Please consider donating to Black Girls Code today.
https://www.blackgirlscode.com/

OHLC Charts in Python

How to make interactive OHLC charts in Python with Plotly. Six examples of OHLC charts with Pandas, time series, and yahoo finance data.


New to Plotly?

Plotly is a free and open-source graphing library for Python. We recommend you read our Getting Started guide for the latest installation or upgrade instructions, then move on to our Plotly Fundamentals tutorials or dive straight in to some Basic Charts tutorials.

The OHLC chart (for open, high, low and close) is a style of financial chart describing open, high, low and close values for a given x coordinate (most likely time). The tip of the lines represent the low and high values and the horizontal segments represent the open and close values. Sample points where the close value is higher (lower) then the open value are called increasing (decreasing). By default, increasing items are drawn in green whereas decreasing are drawn in red.

See also Candlestick Charts and other financial charts.

Simple OHLC Chart with Pandas

In [1]:
import plotly.graph_objects as go
import pandas as pd

df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/finance-charts-apple.csv')

fig = go.Figure(data=go.Ohlc(x=df['Date'],
                    open=df['AAPL.Open'],
                    high=df['AAPL.High'],
                    low=df['AAPL.Low'],
                    close=df['AAPL.Close']))
fig.show()

OHLC Chart without Rangeslider

In [2]:
import plotly.graph_objects as go

import pandas as pd


df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/finance-charts-apple.csv')

fig = go.Figure(data=go.Ohlc(x=df['Date'],
                open=df['AAPL.Open'],
                high=df['AAPL.High'],
                low=df['AAPL.Low'],
                close=df['AAPL.Close']))
fig.update(layout_xaxis_rangeslider_visible=False)
fig.show()

Adding Customized Text and Annotations

In [3]:
import plotly.graph_objects as go
import pandas as pd

df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/finance-charts-apple.csv')

fig = go.Figure(data=go.Ohlc(x=df['Date'],
                open=df['AAPL.Open'],
                high=df['AAPL.High'],
                low=df['AAPL.Low'],
                close=df['AAPL.Close']))

fig.update_layout(
    title='The Great Recession',
    yaxis_title='AAPL Stock',
    shapes = [dict(
        x0='2016-12-09', x1='2016-12-09', y0=0, y1=1, xref='x', yref='paper',
        line_width=2)],
    annotations=[dict(
        x='2016-12-09', y=0.05, xref='x', yref='paper',
        showarrow=False, xanchor='left', text='Increase Period Begins')]
)

fig.show()

Custom OHLC Colors

In [4]:
import plotly.graph_objects as go
import pandas as pd

df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/finance-charts-apple.csv')

fig = go.Figure(data=[go.Ohlc(
    x=df['Date'],
    open=df['AAPL.Open'], high=df['AAPL.High'],
    low=df['AAPL.Low'], close=df['AAPL.Close'],
    increasing_line_color= 'cyan', decreasing_line_color= 'gray'
)])
fig.show()

Simple OHLC with datetime Objects

In [5]:
import plotly.graph_objects as go

from datetime import datetime

open_data = [33.0, 33.3, 33.5, 33.0, 34.1]
high_data = [33.1, 33.3, 33.6, 33.2, 34.8]
low_data = [32.7, 32.7, 32.8, 32.6, 32.8]
close_data = [33.0, 32.9, 33.3, 33.1, 33.1]
dates = [datetime(year=2013, month=10, day=10),
         datetime(year=2013, month=11, day=10),
         datetime(year=2013, month=12, day=10),
         datetime(year=2014, month=1, day=10),
         datetime(year=2014, month=2, day=10)]

fig = go.Figure(data=[go.Ohlc(x=dates,
                          open=open_data, high=high_data,
                          low=low_data, close=close_data)])
fig.show()

Custom Hovertext

In [6]:
import plotly.graph_objects as go

import pandas as pd
from datetime import datetime

hovertext=[]
for i in range(len(df['AAPL.Open'])):
    hovertext.append('Open: '+str(df['AAPL.Open'][i])+'<br>Close: '+str(df['AAPL.Close'][i]))

df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/finance-charts-apple.csv')

fig = go.Figure(data=go.Ohlc(x=df['Date'],
                open=df['AAPL.Open'],
                high=df['AAPL.High'],
                low=df['AAPL.Low'],
                close=df['AAPL.Close'],
                text=hovertext,
                hoverinfo='text'))
fig.show()

Reference

For more information on candlestick attributes, see: https://plotly.com/python/reference/#ohlc

What About Dash?

Dash is an open-source framework for building analytical applications, with no Javascript required, and it is tightly integrated with the Plotly graphing library.

Learn about how to install Dash at https://dash.plot.ly/installation.

Everywhere in this page that you see fig.show(), you can display the same figure in a Dash application by passing it to the figure argument of the Graph component from the built-in dash_core_components package like this:

import plotly.graph_objects as go # or plotly.express as px
fig = go.Figure() # or any Plotly Express function e.g. px.bar(...)
# fig.add_trace( ... )
# fig.update_layout( ... )

import dash
import dash_core_components as dcc
import dash_html_components as html

app = dash.Dash()
app.layout = html.Div([
    dcc.Graph(figure=fig)
])

app.run_server(debug=True, use_reloader=False)  # Turn off reloader if inside Jupyter