This interactive chart shows "survival curves" for females in different countries.
Calcualted from life tables, these survival curves show the expected number of survivors from birth to 85 at 5-year intervals from a hypothetical cohort of 100,000.
Tariq Khokhar tkb
tkb
/ list-of-wb-catalog-sources.json
Created
July 17, 2013 18:41
Results of: http://api.worldbank.org/sources?format=json
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| [ | |
| { | |
| "page": "1", | |
| "pages": "1", | |
| "per_page": "50", | |
| "total": "28" | |
| }, | |
| [ | |
| { | |
| "id": "11", |
tkb
/ wbdata-plot-example.py
Last active
December 20, 2015 00:19
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| import wbdata | |
| import pandas | |
| import matplotlib.pyplot as plt | |
| #set up the countries I want | |
| countries = ["CL","UY","HU"] | |
| #set up the indicator I want (just build up the dict if you want more than one) | |
| indicators = {'NY.GNP.PCAP.CD':'GNI per Capita'} | |
tkb
/ lifeexpectancy-pivoted.csv
Created
August 2, 2013 01:14
We can make this file beautiful and searchable if this error is corrected: No commas found in this CSV file in line 0.
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| Country Name 2005 2006 2007 2008 2009 | |
| Afghanistan 46.6 46.9 47.2 47.5 47.9 | |
| Albania 76.1 76.3 76.5 76.6 76.8 | |
| Algeria 71.6 71.9 72.2 72.4 72.6 |
tkb
/ lifeexpectancy.csv
Created
August 2, 2013 01:19
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| Country | Year | Life Expectancy | |
|---|---|---|---|
| Afghanistan | 2005 | 46.6 | |
| Afghanistan | 2006 | 46.9 | |
| Afghanistan | 2007 | 47.2 | |
| Afghanistan | 2008 | 47.5 | |
| Afghanistan | 2009 | 47.9 | |
| Albania | 2005 | 76.1 | |
| Albania | 2006 | 76.3 | |
| Albania | 2007 | 76.5 | |
| Albania | 2008 | 76.6 |
tkb
/ lifeexpectancy.csv
Created
August 2, 2013 01:19
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| Afghanistan | 2005 | 46.6 | |
|---|---|---|---|
| Afghanistan | 2006 | 46.9 | |
| Afghanistan | 2007 | 47.2 | |
| Afghanistan | 2008 | 47.5 | |
| Afghanistan | 2009 | 47.9 | |
| Albania | 2005 | 76.1 | |
| Albania | 2006 | 76.3 | |
| Albania | 2007 | 76.5 | |
| Albania | 2008 | 76.6 |
tkb
/ unpivot-le.py
Last active
December 20, 2015 13:09
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| import pandas as pd | |
| #read the normalized CSV file | |
| df = pandas.read_csv('lifeexpectancy.csv') | |
| #melt the normalized file, hold the country name and code variables, rename the melted columns | |
| le = pd.melt(df, id_vars=['Country Name','Country Code'], var_name="year", value_name="life_expectancy") | |
| #sort by country name for convenience | |
| le2 = le.sort(['Country Name']) |
tkb
/ unpivot-pandas-example.json
Created
August 2, 2013 14:58
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| { | |
| "metadata": { | |
| "name": "unpivoting-csv-pandas" | |
| }, | |
| "nbformat": 3, | |
| "nbformat_minor": 0, | |
| "worksheets": [ | |
| { | |
| "cells": [ | |
| { |
This interactive chart shows "survival curves" for females in different countries.
Calcualted from life tables, these survival curves show the expected number of survivors from birth to 85 at 5-year intervals from a hypothetical cohort of 100,000.
##Here's an embed of a visualization
<iframe frameborder="0" height="700px" src="http://tkb.github.io/lifeexpectancy-post/index.html" style="margin-top:-90px" width="650px"></iframe>##Here's an embed of a youtube video
<iframe width="560" height="315" src="//www.youtube.com/embed/sPlHUXHVOHY" frameborder="0" allowfullscreen></iframe>Above me you should see the contents of:
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