Effective Information Visualization

-effective communication of complex quantitative ideas
clarity, precision, efficiency

Visual Encoding
position x, y
Length A, B, C
Angle

Visual Encoding: Direction, Shape, Area/Volume
Color: Hue, Saturation
Combination: min, max
Limit Hues

Plotting in Python
– Many packages
– matplotlib <- very popular - ggplot <- use this, looks nicer, grammer of graphics ggplot(data, qes(xvar, yvar)) + geom_point() + geom_line() first step: create plot second step: represent data with geometric objects third step: add labels

from pandas import *
from ggplot import *

def lineplot(hr_year_csv):
	hr_year = pandas.read_csv(‘hr_year.csv’)
	print ggplot(hr_year, aes(‘yearID’, ‘HR’)) + geom_point(color=’red’) + geom_line(color=’red’) + ggtitle(‘Total HRs by Year’) + xlab(‘Year’) + ylab(‘HR’)

if __name__ == ‘__main__’:
	lineplot()