In [98]:

    

import pandas as pd
import numpy as np

itu_mobile = pd.DataFrame.from_csv('mobile_cell_2.csv')
itu_mobile = itu_mobile[['2000','2001','2002','2003','2004','2005','2006','2007',
                         '2008','2009','2010','2011','2012','2013','2014']]


    

In [99]:

    

pop_df = pd.DataFrame.from_csv('sp.pop.totl_Indicator_en_csv_v2.csv')


    

In [100]:

    

ldc = ["Angola",
"Madagascar",
"Benin",
"Malawi",
"Burkina Faso",
"Mali",
"Burundi",
"Mauritania",
"Mozambique",
"Chad",
"Niger",
"Comoros",
"Rwanda",
"Congo (Dem. Rep.)",
"S. Tome & Principe",
"Djibouti",
"Senegal",
"Equatorial Guinea",
"Sierra Leone",
"Eritrea",
"Somalia",
"Ethiopia",
"South Sudan",
"Gambia",
"Sudan",
"Guinea",
"Togo",
"Guinea-Bissau",
"Uganda",
"Lesotho",
"Tanzania",
"Liberia",
"Zambia",
"Afghanistan",
"Nepal",
"Bangladesh",
"Solomon Islands",
"Bhutan",
"Timor-Leste",
"Cambodia",
"Tuvalu",
"Kiribati",
"Vanuatu",
"Lao P.D.R.",
"Yemen",
"Myanmar",
"Haiti"]


    

In [101]:

    

ldc_pop = ["Angola",
"Madagascar",
"Benin",
"Malawi",
"Burkina Faso",
"Mali",
"Burundi",
"Mauritania",
"Mozambique",
"Chad",
"Niger",
"Comoros",
"Rwanda",
"Congo, Dem. Rep.",
"Sao Tome and Principe",
"Djibouti",
"Senegal",
"Equatorial Guinea",
"Sierra Leone",
"Eritrea",
"Somalia",
"Ethiopia",
"South Sudan",
"Gambia, The",
"Sudan",
"Guinea",
"Togo",
"Guinea-Bissau",
"Uganda",
"Lesotho",
"Tanzania",
"Liberia",
"Zambia",
"Afghanistan",
"Nepal",
"Bangladesh",
"Solomon Islands",
"Bhutan",
"Timor-Leste",
"Cambodia",
"Tuvalu",
"Kiribati",
"Vanuatu",
"Lao PDR",
"Yemen, Rep.",
"Myanmar",
"Haiti"]


    

In [102]:

    

ldc_pop_df = pop_df[pop_df.index.isin(ldc_pop)]


    

In [103]:

    

def ldc_pop_by_year(year):
    return ldc_pop_df[year].sum()


    

In [104]:

    

ldc_pop_by_year("2000")


    

    
Out[104]:





660660039.0

In [105]:

    

m_stack = itu_mobile.stack()


    

In [106]:

    

for k,v in m_stack.iteritems():
    m_stack[k] = int(v.replace(',',''))


    

In [107]:

    

def ldc_total_phone_by_year(year):
    val = 0
    for c in ldc:
        try:
#             print c
            val += m_stack[c][year]
        except:
            print c
    return val

def prevalence_year(year):
    return ldc_total_phone_by_year(year)/ldc_pop_by_year(year)


    

In [162]:

    

prevalence_year("2006")


    

    




Sierra Leone
South Sudan
Guinea






    
Out[162]:





0.088955138004260872

In [114]:

    

pop_stack = pop_df.stack()


    

In [163]:

    

m_stack["Haiti"]["2006"]/pop_stack["Haiti"]["2006"]


    

    
Out[163]:





0.12753097169354435

In [145]:

    

for p in itu_mobile.index:
    if "Cote" in p:
        print p


    

    




Cote d'Ivoire

In [ ]: