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# 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.

If you're using Dash Enterprise's Data Science Workspaces, you can copy/paste any of these cells into a Workspace Jupyter notebook.
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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.

#### Simple OHLC Chart with Pandas¶

In :
import plotly.graph_objects as go
import pandas as pd

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 :
import plotly.graph_objects as go

import pandas as pd

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 :
import plotly.graph_objects as go
import pandas as pd

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 :
import plotly.graph_objects as go
import pandas as pd

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 :
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 :
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]))

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¶

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.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)
]) 