#Creating a line plot

#Importing the required packages

from bokeh.io import output_file, show

from bokeh.plotting import figure

#Creating our data arrays used for plotting the line plot

x = [5,6,7,8,9,10]

y = [1,2,3,4,5,6]

#Calling the figure() function to create the figure of the plot

plot = figure()

#Creating a line plot using the line() function

plot.line(x,y)

#Creating markers on our line plot at the location of the intersection between x and y

plot.cross(x,y, size = 15)

#Output the plot 

output_file('line_plot.html')

show(plot)



#Creating bar plots


#Importing the required packages

from bokeh.plotting import figure, show, output_file

#Points on the x axis

x = [8,9,10]

#Points on the y axis

y = [1,2,3]

#Creating the figure of the plot

plot = figure()

#Code to create the barplot

plot.vbar(x,top = y, color = "blue", width= 0.5)

#Output the plot

output_file('barplot.html')

show(plot)


#Creating patch plots


#Importing the required packages

from bokeh.io import output_file, show

from bokeh.plotting import figure

#Creating the regions to map

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

y_region = [[2,5,6], [3,6,7], [2,4,7,8]]

#Creating the figure

plot = figure()

#Building the patch plot

plot.patches(x_region, y_region, fill_color = ['yellow', 'black', 'green'], line_color = 'white')

#Output the plot

output_file('patch_plot.html')

show(plot)


#Creating scatter plots



#Importing the required packages

from bokeh.io import output_file, show

from bokeh.plotting import figure

#Creating the figure

plot = figure()

#Creating the x and y points

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

y = [5,7,2,2,4]

#Plotting the points with a cirle marker

plot.circle(x,y, size = 30)

#Output the plot

output_file('scatter.html')

show(plot)




#Different types of markers

- cross()
- x()
- diamond()
- diamond_cross()
- circle_x()
- circle_cross()
- triangle()
- inverted_triangle()
- square()
- square_x()
- square_cross()
- asterisk()


#Adding labels to the plot

plot.figure(x_axis_label = "Label name of x axis", y_axis_label = "Label name of y axis")



#Customizing transperancy of the plot

plot.circle(x, y, alpha = 0.5)
