#!/usr/bin/env python
# coding: utf-8

# # Analyzing Data

# ## Prison Helicopter Escapes

# We begin by importing some helper functions

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from helper import *


# ## Get the Data

# Now, let's get the data from the [List of helicopter prison escapes](https://en.wikipedia.org/wiki/List_of_helicopter_prison_escapes) Wikipedia article.

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url = 'https://en.wikipedia.org/wiki/List_of_helicopter_prison_escapes'
data = data_from_url(url)


# Let's print the first three rows

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for d in data[:3]:
    print(d)


# ### Fetching only year and saving back to the data

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index = 0
for row in data:
    
    row[0] = fetch_year(row[0])
    data[index] = row[:-1]
    print(row)
    index+=1
   


# ### 

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min_year = min(data, key=lambda x: x[0])[0]
max_year = max(data, key=lambda x: x[0])[0]
print(min_year)
print(max_year)


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years = []
attempts_per_year = []
each_year = []
for year in range(min_year, max_year+1):
    years.append(year)

for year in years:
    times = data.count(year)
    each_year.append(year)
    each_year.append(times)
    attempts_per_year.append(each_year)
    each_year = []

for row in data:
    for year_attempt in attempts_per_year:
        if row[0]==year_attempt[0]:
            year_attempt[1]+=1
print (attempts_per_year)


# ### In which year did the most attempts at breaking out of prison with a helicopter occur?

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get_ipython().run_line_magic('matplotlib', 'inline')
barplot(attempts_per_year)


# ### In which country did the most attempts at breaking out of prison with a helicopter occur?

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countries_frequency = df["Country"].value_counts()
print_pretty_table(countries_frequency)


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