Skip to content

Instantly share code, notes, and snippets.

View devdutta's full-sized avatar

devdutta

View GitHub Profile
@devdutta
devdutta / gdpworld.html
Last active June 25, 2019 13:09
<!DOCTYPE html>
<body>
<script type="module">
// Load the Observable runtime and inspector.
import {Runtime, Inspector} from "https://cdn.jsdelivr.net/npm/@observablehq/runtime@4/dist/runtime.js";
// Your notebook, compiled as an ES module.
import notebook from "https://api.observablehq.com/@devdutta/gdp-per-capita-ppp-inflation-ajusted-1990-2017.js?v=3";
@devdutta
devdutta / country-codes.csv
Created June 25, 2019 05:30
Standard Country Codes
name alpha-2 alpha-3 country-code iso_3166-2 region sub-region intermediate-region region-code sub-region-code intermediate-region-code
Afghanistan AF AFG 004 ISO 3166-2:AF Asia Southern Asia 142 034
Åland Islands AX ALA 248 ISO 3166-2:AX Europe Northern Europe 150 154
Albania AL ALB 008 ISO 3166-2:AL Europe Southern Europe 150 039
Algeria DZ DZA 012 ISO 3166-2:DZ Africa Northern Africa 002 015
American Samoa AS ASM 016 ISO 3166-2:AS Oceania Polynesia 009 061
Andorra AD AND 020 ISO 3166-2:AD Europe Southern Europe 150 039
Angola AO AGO 024 ISO 3166-2:AO Africa Sub-Saharan Africa Middle Africa 002 202 017
Anguilla AI AIA 660 ISO 3166-2:AI Americas Latin America and the Caribbean Caribbean 019 419 029
Antarctica AQ ATA 010 ISO 3166-2:AQ
@devdutta
devdutta / GDP_perCapitaPPP.csv
Last active June 25, 2019 05:31
GDP Per Capita PPP - World Bank Data
We can make this file beautiful and searchable if this error is corrected: It looks like row 4 should actually have 33 columns, instead of 16 in line 3.
Country Name,Country Code,Indicator Name,Indicator Code,1990,1991,1992,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013,2014,2015,2016,2017,2018
Aruba,ABW,GDP per capita PPP,NY.GDP.PCAP.PP.CD,23999.11428,25748.00441,26407.61433,27303.43229,28521.48713,28510.87711,28360.17362,30064.85538,30348.01804,30588.29198,32982.32601,32011.10353,30745.46731,31310.58613,34112.04475,35176.21223,36346.7893,37840.22908,38496.92658,34674.53902,33732.84387,35490.18398,35493.09606,37409.74073,38215.63765,38249.05144,38408.58313,39492.85908,
Afghanistan,AFG,GDP per capita PPP,NY.GDP.PCAP.PP.CD,,,,,,,,,,,,,859.9325057,909.6460996,906.4487731,1001.172169,1052.673989,1196.679103,1236.580511,1474.128696,1659.112751,1649.150373,1834.098535,1906.545896,1933.021141,1924.559715,1936.792072,1976.363239,
Angola,AGO,GDP per capita PPP,NY.GDP.PCAP.PP.CD,2994.948443,3030.210421,2824.97352,2127.127244,2131.895543,2427.795665,2727.936456,2896.233888,2982.899676,3008.188118,3075.900376,317
@devdutta
devdutta / classifier_from_little_data_script_2.py
Created June 17, 2018 11:56 — forked from fchollet/classifier_from_little_data_script_2.py
Updated to the Keras 2.0 API.
'''This script goes along the blog post
"Building powerful image classification models using very little data"
from blog.keras.io.
It uses data that can be downloaded at:
https://www.kaggle.com/c/dogs-vs-cats/data
In our setup, we:
- created a data/ folder
- created train/ and validation/ subfolders inside data/
- created cats/ and dogs/ subfolders inside train/ and validation/
- put the cat pictures index 0-999 in data/train/cats