How to make interactive OHLC charts in Python with Plotly. Six examples of OHLC charts with Pandas, time series, and yahoo finance data.
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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=dict(text='The Great Recession'), yaxis=dict(title=dict(text='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()
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()
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()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( ... ) from dash import Dash, dcc, html app = Dash() app.layout = html.Div([ dcc.Graph(figure=fig) ]) app.run(debug=True, use_reloader=False) # Turn off reloader if inside Jupyter
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