Data Visualization using Bokeh.ipynb

Kernel: Python 3 (ipykernel)

You can create interactive plots with Bokeh and also dashboards and data applications.

from bokeh.plotting import figure, show
from bokeh.io import output_notebook
import pandas as pd
import numpy as np

• The figure function allows us to create a basic plot object, where we can define things like height, grids, and tools.

data = pd.read_csv("Airline.csv")
data.head(2)

p = figure(width=800, height=400)

# add a circle renderer with a size, color, and alpha
p.circle(data.sum_departures_performed, data.Passengers, size=20, color="navy", alpha=0.2)

# show the results
show(p)

# add a title with providing the title parameter
p = figure(width=800, height=400, title="Average Fuel Price")

# compute the histogram of the price variable 
hist, edges = np.histogram(data.avg_Fuel_Price, density=True, bins=50)

# call the quad method on our figure object p
p.quad(top=hist, bottom=0, left=edges[:-1], right=edges[1:], line_color="white")

show(p)

if we wanted to specify the position of the title, and we wanted a title for each axis? Well, Bokeh also offers a simple solution to this problem

from bokeh.palettes import Spectral7
from bokeh.models import Title

# prepare the Aircratft  value counts
colors = sorted(list(data.Aircraft.unique()))
counts = [i for i in data.Aircraft.value_counts().sort_index()]

p = figure(x_range=Aircraft, width=800, height=400)

p.vbar(x=Arcraft ,op=counts, width=0.9, color=Spectral7)

p.y_range.start = 0

p.add_layout(Title(text="Aircraft", align="center"), "below")
p.add_layout(Title(text="Unnique", align="center"), "left")

show(p)