Deep dive Visualizations with - Bokeh , Holoviews , PlotlyJS , d3.js , dc.js and maybe Seaborn

[RohitDhankar]

Deep dive Visualizations with - Bokeh , Holoviews , PlotlyJS , d3.js , dc.js and maybe Seaborn @RohitDhankar and @RohanMathur17 to collab .

Existing old code here - https://github.com/digital-cognition-co-in/DigitalCognition/blob/97d80d279d8cf0cb5f85a2264bab8e2f23e7a44c/dc_dash/dc_bokeh_plots.py#L19

@S-T-A-R-L-O-R-D ( DEVESH SOLANKI ) to collab with @RohanMathur17 for Plotly Python version and Bokeh plots / charts.

[S-T-A-R-L-O-R-D]

It's an Interactive Plot, if we hover over any field it will display more information about that field like tableau Looking forward to creating more engaging and Interactive visuals.

[RohitDhankar]

@S-T-A-R-L-O-R-D - thanks Devesh , this is awesome :)

[S-T-A-R-L-O-R-D]

from bokeh.plotting import figure, output_file, show, ColumnDataSource from bokeh.models.tools import HoverTool from bokeh.transform import factor_cmap from bokeh.palettes import Blues8 from bokeh.embed import components from bokeh.io import output_notebook,show import pandas as pd

x = [1, 2, 3, 4, 5]

y = [4, 6, 2, 4, 3]

Read CSV

df = pd.read_csv("cars.csv")

car = df['Car']

hp = df['Horsepower']

ColumnDataSource from data frame

source = ColumnDataSource(df)

output_notebook() output_file("index.html")

Add plot

p = figure( y_range=source.data['Car'].tolist(), plot_width=800, plot_height=600, title="Cars With Top Horsepower ", x_axis_label="Horsepower", tools="pan,box_select,zoom_in,zoom_out,save,reset")

Render Glyph

p.hbar(y='Car', right='Horsepower', left=0, height=0.4, fill_color=factor_cmap('Car',palette=Blues8,factors=source.data['Car'].tolist()), fill_alpha=0.5, legend='Car' ,source=source)

Adding Legend

p.legend.orientation='vertical' p.legend.location='top_right' p.legend.label_text_font_size='10px'

Adding Tooltip

hover = HoverTool() hover.tooltips = """

@Car

Price: @Price

Horsepower: @Horsepower

""" p.add_tools(hover)

show results

show(p)

print out div and script

script,div=components(p) print(div) print(script)