%config InlineBackend.figure_format = 'retina'
%matplotlib inline

import numpy as np
import scipy as sp
import matplotlib.pyplot as plt
import pandas as pd

import seaborn as sns
sns.set_style("white")

"""
Explanation: San Diego Burrito Analytics: The best burritos (under construction)
Scott Cole
21 May 2016
This notebook will determine the best and worst burritos across the different dimensions, such as:
1. What taco shop has the highest rated burritos?
2. What taco shop has the best California burrito?
3. What taco shop has the most optimal meat-to-filling ratio?
Default imports
End of explanation
"""


filename="burrito_current.csv"
df = pd.read_csv(filename)
N = df.shape[0]

"""
Explanation: Load data
End of explanation
"""


m_best = ['Volume','Cost','Tortilla','Temp','Meat','Fillings','Meat:filling',
               'Uniformity','Salsa','Synergy','Wrap','overall','Google','Yelp']

for m in m_best:
    print m
    print 'High,', df.Location[df[m].idxmax()], df[m][df[m].idxmax()]
    print 'Low,', df.Location[df[m].idxmin()], df[m][df[m].idxmin()]

"""
Explanation: Find the best location for each dimension
End of explanation
"""


