Countries by Natural Disaster Risk

Retrieve data on natural disaster risk from Wikipedia's List of countries by natural disaster risk, do some cleanup and save it on a format appropriate for rendering a map with d3.geomap.

In [1]:
import requests
import io
import re

import pandas as pd
import geonamescache

from geonamescache import mappings

gc = geonamescache.GeonamesCache()
cnames = gc.get_countries_by_names()

url = ''

re_num = re.compile(r'^[\d,.]+$')

def fix_num(x):
    if (isinstance(x, str) and, x)):
        x = x.replace(',', '')
        if '.' in x:
            x = float(x)
            x = int(x)
    return x

Download the data as CSV, read it into a Pandas DataFrame and convert numbers to floats and integers.

In [2]:
csv = requests.get(url).text
df = pd.read_csv(io.StringIO(csv))
df = df.applymap(fix_num)
Country Rank Disaster risk
0 Qatar 1 0.10%
1 Malta 2 0.61%
2 Barbados 3 1.16%
3 Saudi Arabia 4 1.32%
4 Grenada 5 1.44%

5 rows × 3 columns

Map country names to iso3 codes.

In [3]:
def get_iso3(name):
    if name in mappings.country_names:
        name = mappings.country_names[name]
    return cnames[name]['iso3']

df['iso3'] = df['Country'].apply(get_iso3)

Delete unused columns and save the data as a CSV file.

In [4]:
df['Disaster Risk in Percent'] = df['Disaster risk'].apply(lambda x: float(x.replace('%', '')))
del df['Rank'], df['Disaster risk']
df.to_csv('../static/data/csv/natural-disaster-risk.csv', encoding='utf-8', index=False)

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Ramiro Gómez

About this post

This post was written by Ramiro Gómez (@yaph) and published on July 28, 2014.

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