Ramya ramyaragupathy

## README.md

      
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                ramyaragupathy
                / README.md
            
            
              Created
              November 25, 2019 12:01
                — forked from jsanz/README.md
            
              
                Look up table for the Köppen-Geiger
              
          
    This CSV serves as a look up table to relate GRIDCODE field with the corresponding Köppen-Geiger classification and the color used on the paper.
I used this table to create this map

More info:

Köppen-Geiger source
Köppen-Geiger paper


## statistics.sql
** Find commmonly accessed tables and their use of indexes:

SELECT relname,seq_tup_read,idx_tup_fetch,cast(idx_tup_fetch AS numeric) / (idx_tup_fetch + seq_tup_read) AS idx_tup_pct FROM pg_stat_user_tables WHERE (idx_tup_fetch + seq_tup_read)>0 ORDER BY idx_tup_pct;

Returns output like:

       relname        | seq_tup_read | idx_tup_fetch |      idx_tup_pct
----------------------+--------------+---------------+------------------------
 schema_migrations    |          817 |             0 | 0.00000000000000000000
 user_device_photos   |          349 |             0 | 0.00000000000000000000

## continents.json

      
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                ramyaragupathy
                / continents.json
            
            
              Created
              July 30, 2019 06:55
                — forked from cmunns/continents.json
            
              
                Continental GeoJson
              
          
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## countries.json
---
layout:
---


{% capture countries_list %}
{% for country in site.where-we-work %}
{{ country.title }}::
{% for project in site.projects %}
      {% if project.Country contains country.title %}

## indian_women_in_data.md

      
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                ramyaragupathy
                / indian_women_in_data.md
            
            
              Last active
              February 23, 2018 09:58
                — forked from DevKhokhar/indian_women_in_data.md
            
              
                List of Indian women who represent the data space in India and globally
              
          
    Below is a list of Indian women who have contributed it to the data space in India and globally - be it Data Strategy, Data Engineering, Machine Learning, Artificial Intelligence, Data and Public Policy, or any other related field. Please feel free to add in the missing names. I have arranged the names alphabetically for easy searchability. Please do add the name, twitter handle (if available), linkedin profile (if available), link(s) to their public blogs/videos (if available) and the area of specialization. Also, don't forget to add in your name below to the link of contributors. This isn't an individual's effort - this will work only if more and more people contribute. Thanks!
*Note: I have started with just the Indian women here because I wanted to bring attention to some of the inspirational women at the national level. However, if you want to replicate it for any other country or even at a global level, please feel free to either add in into the same list (adding an additional column of course) or cr

  
## index.html
<!DOCTYPE html>
<html>
<head>
    <meta charset='utf-8' />
    <title></title>
    <meta name='viewport' content='initial-scale=1,maximum-scale=1,user-scalable=no' />
    <script src='https://api.tiles.mapbox.com/mapbox-gl-js/v0.17.0/mapbox-gl.js'></script>
    <link href='https://api.tiles.mapbox.com/mapbox-gl-js/v0.17.0/mapbox-gl.css' rel='stylesheet' />
    <style>
        body { margin:0; padding:0; font: 15px/20px sans-serif; }

## overpass.geojson

      
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                ramyaragupathy
                / overpass.geojson
            
            
              Created
              April 4, 2016 08:35
            
              
                data exported by overpass turbo
              
          
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## bar.js
var bar = [

 {
      "type": "Feature",
      "id": "node/446995814",
      "properties": {
        "@id": "node/446995814",
        "amenity": "bar",
        "marker-color": "#98292E ",
          "marker-size": "medium",

## atm.js
var atm = [


    {
      "type": "Feature",
      "id": "node/302493798",
      "properties":
       {
          "@id": "node/302493798",
          "amenity": "atm",
	** Find commmonly accessed tables and their use of indexes:

	SELECT relname,seq_tup_read,idx_tup_fetch,cast(idx_tup_fetch AS numeric) / (idx_tup_fetch + seq_tup_read) AS idx_tup_pct FROM pg_stat_user_tables WHERE (idx_tup_fetch + seq_tup_read)>0 ORDER BY idx_tup_pct;

	Returns output like:

	relname \| seq_tup_read \| idx_tup_fetch \| idx_tup_pct
	----------------------+--------------+---------------+------------------------
	schema_migrations \| 817 \| 0 \| 0.00000000000000000000
	user_device_photos \| 349 \| 0 \| 0.00000000000000000000
	---
	layout:
	---


	{% capture countries_list %}
	{% for country in site.where-we-work %}
	{{ country.title }}::
	{% for project in site.projects %}
	{% if project.Country contains country.title %}
	<!DOCTYPE html>
	<html>
	<head>
	<meta charset='utf-8' />
	<title></title>
	<meta name='viewport' content='initial-scale=1,maximum-scale=1,user-scalable=no' />
	<script src='https://api.tiles.mapbox.com/mapbox-gl-js/v0.17.0/mapbox-gl.js'></script>
	<link href='https://api.tiles.mapbox.com/mapbox-gl-js/v0.17.0/mapbox-gl.css' rel='stylesheet' />
	<style>
	body { margin:0; padding:0; font: 15px/20px sans-serif; }
	var bar = [

	{
	"type": "Feature",
	"id": "node/446995814",
	"properties": {
	"@id": "node/446995814",
	"amenity": "bar",
	"marker-color": "#98292E ",
	"marker-size": "medium",
	var atm = [


	{
	"type": "Feature",
	"id": "node/302493798",
	"properties":
	{
	"@id": "node/302493798",
	"amenity": "atm",