Pandas plotting of pizza price comparison

pizza-price-comparison.py

# -*- coding: utf-8 -*-
import pandas as pd
import matplotlib.pyplot as plt
import itertools

# Load data
prices = pd.read_csv("PizzaPrices.csv")

# Filter out an unwanted establishment
prices = prices[(prices['establishment_name'] != "Pizza Zone")]

# Sort data
prices = prices.sort(['establishment_type', 'establishment_name', 'Price'], ascending=[1, 1, 1])

# Set marker types to cycle through
marker1 = itertools.cycle(('s', 'o', '^', 'v', '*')) 
marker2 = itertools.cycle(('s', 'o', '^', 'v', '*')) 
marker3 = itertools.cycle(('s', 'o', '^', 'v', '*')) 

# Group data according to establishment type
grouped = prices.groupby("establishment_name")

# Have a look at the colormaps here and decide which one you'd like:
num_plots = len(grouped)
colormap = plt.cm.gist_rainbow

# Loop through grouped data
# Change plot style depending on group
for key, grp in grouped:    
    if grp.establishment_type.irow(0) == "Shop":
        this_marker = marker1.next()
        this_colour = "red"
    elif grp.establishment_type.irow(0) == "Takeaway":
        this_marker = marker2.next()
        this_colour = "green"
    elif grp.establishment_type.irow(0) == "Restaurant":
        this_marker = marker3.next()
        this_colour = "blue"
    plt.plot(grp['Diameter'],grp['Price'],  label=key, linestyle = '-', marker=this_marker, color = this_colour, ms = 9, linewidth = 0.5)
 
# Plot data   
plt.legend(loc=2,bbox_to_anchor=(1, 1.03))   
plt.xlabel("Diameter (inch)") 
plt.ylabel("Price per sq. inch (GBP/sq. inch)") 
plt.xlim([5,20])
plt.grid()

# Save figure to file
save_image_as = "pizza_prices.png"
fig = plt.gcf()
fig.set_size_inches(8,6)
fig.savefig(save_image_as,dpi=600,bbox_inches='tight')
plt.show()

PizzaPrices.csv