!date
Mon Mar 10 16:08:52 PDT 2014
import numpy as np, pandas as pd
%matplotlib inline
import matplotlib.pyplot as plt, seaborn
df = pd.read_csv('http://ghdx.healthmetricsandevaluation.org/sites/default/files/record-attached-files/IHME_IRAQ_MORTALITY_STUDY_2001_2011_HH_DEATHS.CSV')
df.head()
cluster | hh | gov | sex | mod | yod | cod | death_cert | war_death | war_cod | respo | distance | year_hh_formed | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
0 | 1 | 6 | 18 | F | 7 | 2007 | cardiovascular | death cert not available | N | NaN | NaN | NaN | 1980 |
1 | 1 | 10 | 18 | M | 3 | 2002 | injury (not war) >=18 | able to see death cert | N | NaN | NaN | NaN | 1989 |
2 | 1 | 10 | 18 | M | 4 | 2006 | injury (not war) >=18 | able to see death cert | N | NaN | NaN | NaN | 1989 |
3 | 1 | 15 | 18 | F | 10 | 2003 | injury (war) <18 | able to see death cert | Y | gunshot | coalition forces | Yes <1 KM | 1976 |
4 | 1 | 16 | 18 | F | 5 | 2009 | injury (not war) <18 | able to see death cert | N | NaN | NaN | NaN | 1983 |
5 rows × 13 columns
s = df.death_cert.value_counts() / float(len(df.index))
s *= 100
s.order().plot(kind='barh', fontsize=24)
plt.xticks(fontsize=18)
plt.xlabel('Percent of Deaths in HH Survey', fontsize=24)
plt.axis(xmax=100);