Bokeh can be easily used in conjunction with NumPy, Pandas, and other Python packages. It can be used to produce interactive plots, dashboards, and so on.
Dependencies of Bokeh −
Numpy Pillow Jinja2 Packaging Pyyaml Six Tornado Python−dateutil
Installation of Bokeh on Windows command prompt
pip3 install bokeh
Installation of Bokeh on Anaconda prompt
conda install bokeh
Following is an example −
from math import pi import pandas as pd from bokeh.plotting import figure, output_file, show from bokeh.sampledata.stocks import MSFT my_df = pd.DataFrame(MSFT)[:35] my_df["date"] = pd.to_datetime(my_df["date"]) inc = my_df.close > my_df.open dec = my_df.open > my_df.close w = 12*60*60*1000 TOOLS = "pan,wheel_zoom,box_zoom,reset,save" p = figure(x_axis_type="datetime", tools=TOOLS, plot_width=1000, title = "Candlestick using MSFT data") p.xaxis.major_label_orientation = pi/4 p.grid.grid_line_alpha=0.3 p.segment(my_df.date, my_df.high, my_df.date, my_df.low, color="black") p.vbar(my_df.date[inc], w, my_df.open[inc], my_df.close[inc], fill_color="#D5E1DD", line_color="black") p.vbar(my_df.date[dec], w, my_df.open[dec], my_df.close[dec], fill_color="#F2583E", line_color="black") output_file("candlestick.html", title="candlestick plot") show(p)
Note − To run this code, the pre−requisites are to install Bokeh, and execute the below command to download the sample datasets.
The required packages are imported, and aliased.
The MSFT data is an inbuilt dataset present in Bokeh library.
It is stored as a dataframe.
The figure function is called along with plot width and height.
The ‘output_file’ function is called to mention the name of the html file that will be generated.
The ‘TOOLS’ attribute is defined.
The ‘vbar’ function present in Bokeh is called, along with data.
The ‘show’ function is used to display the plot.