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Pandas plotting of pizza price comparison
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# -*- 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() |
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establishment_name | establishment_type | Pizza_name | Diameter | Area | Price | Price_per_sq_inch | |
---|---|---|---|---|---|---|---|
Luigi's | Takeaway | 9 | 63.61725 | 4 | 0.06288 | ||
Luigi's | Takeaway | 12 | 113.09734 | 6 | 0.05305 | ||
Luigi's | Takeaway | 15 | 176.71459 | 8 | 0.04527 | ||
Domino's | Takeaway | Personal | 7 | 38.48 | 3.99 | 0.10369 | |
Domino's | Takeaway | Small | 9.5 | 70.88 | 7.99 | 0.11273 | |
Domino's | Takeaway | Medium | 11.5 | 103.87 | 9.99 | 0.09618 | |
Domino's | Takeaway | Large | 13.5 | 143.14 | 11.99 | 0.08376 | |
Pizza Zone | Takeaway | 9 | 63.61725 | 4 | 0.06288 | ||
Pizza Zone | Takeaway | 10 | 78.53982 | 5 | 0.06366 | ||
Pizza Zone | Takeaway | 12 | 113.09734 | 6 | 0.05305 | ||
Sainsbury's | Shop | Normal | 14 | 153.93804 | 3.75 | 0.02436 | |
Sainsbury's | Shop | Basics | 12 | 113.09734 | 1.55 | 0.01371 | |
Sainsbury's | Shop | Taste The Difference | 12 | 113.09734 | 4 | 0.03537 | |
Papa John's | Takeaway | S | 10 | 78.53982 | 7.99 | 0.10173 | |
Papa John's | Takeaway | M | 12 | 113.09734 | 9.99 | 0.08833 | |
Papa John's | Takeaway | L | 14 | 153.93804 | 11.99 | 0.07789 | |
Papa John's | Takeaway | XXL | 16 | 201.06193 | 14.99 | 0.07455 | |
Amigo's | Takeaway | S | 8 | 50.26548 | 3 | 0.05968 | |
Amigo's | Takeaway | M | 10 | 78.53982 | 4.5 | 0.0573 | |
Amigo's | Takeaway | L | 12 | 113.09734 | 6 | 0.05305 | |
Amigo's | Takeaway | XL | 14 | 153.93804 | 7.5 | 0.04872 | |
Pizza Express | Restaurant | 11 | 95.03318 | 7.55 | 0.07945 | ||
Pizza Hut | Restaurant | 11 | 95.03318 | 6.95 | 0.07313 | ||
Pizza Hut | Restaurant | 14 | 153.93804 | 11.95 | 0.07763 | ||
Dino's | Takeaway | 9 | 63.61725 | 4.5 | 0.07074 | ||
Dino's | Takeaway | 12 | 113.09734 | 6 | 0.05305 | ||
Dino's | Takeaway | 16 | 201.06193 | 8 | 0.03979 |
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