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This repository has been archived by the owner on Aug 29, 2020. It is now read-only.
** 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.
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")
Deep dive Visualizations with - Bokeh , Holoviews , PlotlyJS , d3.js , dc.js and maybe Seaborn
@RohitDhankar and @RohanMathur17 to collab .
Existing old code here -
DigitalCognition/dc_dash/dc_bokeh_plots.py
Line 19 in 97d80d2
@S-T-A-R-L-O-R-D ( DEVESH SOLANKI ) to collab with @RohanMathur17 for Plotly Python version and Bokeh plots / charts.
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