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# enable CORS policy
# https://gist.github.com/maxparm/3105526
<IfModule mod_rewrite.c>
  Header add Access-Control-Allow-Origin "*"
  Header add Access-Control-Allow-Methods: "GET,POST,OPTIONS,DELETE,PUT"
  Header add Access-Control-Allow-Headers: "Content-Type"

  RewriteEngine on
  RewriteBase /
</IfModule>

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name	keywords
Felicitas	Development, Corruption, Housing, Transportation, Religion
Lucile	Inequality, Migration, Race and Gender, Community/Neighborhood
Corentin	Inequality, Religion, Migration, Poverty, Gender
Charlotte	Energy, Environment, Smart Cities, Conflict, Gender
Alice	Environment, Gender, Migration, Urban Studies
Miranda	Politics, Gender, Human Rights
Margaux	Inequality, Urban Studies, Migration, Human Rights
Marina	Critical Theory, Social Inequality, Race and Gender
Cosima	Race and Gender and Sexuality, Spatial Inequality, Migration 

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A translation of the code in this blog post.

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#' Read Points out of a KML file.
#' 
#' @param x A KML file exported from Google Maps.
#' @param layer The name of the layer to extract from: defaults to \code{"d1"}.
#' @param verbose Whether to report invalid coordinates and/or altitudes below
#' sea level; defaults to \code{TRUE}. See \link{kml_coordinate}.
#' @return A \link[tibble:tibble]{tibble} containing the \code{name}, 
#' \code{description}, \code{styleUrl} and Point coordinates (\code{longitude}, 
#' \code{latitude} and \code{altitude}) of each Placemark element contained in 
#' the KML file. Placemark elements with no Point coordinates, such as Polygon

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R to python useful data wrangling snippets

The dplyr package in R makes data wrangling significantly easier. 
The beauty of dplyr is that, by design, the options available are limited. 
Specifically, a set of key verbs form the core of the package. 
Using these verbs you can solve a wide range of data problems effectively in a shorter timeframe. 
Whilse transitioning to Python I have greatly missed the ease with which I can think through and solve problems using dplyr in R. 
The purpose of this document is to demonstrate how to execute the key dplyr verbs when manipulating data using Python (with the pandas package). 

dplyr is organised around six key verbs

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library(dplyr)
library(readr)
library(rvest)

h = html("https://meta.wikimedia.org/wiki/Freedom_of_Panorama_in_Europe_in_2015/Contact_your_MEP")

l = html_nodes(h, xpath = "//a[contains(@href, 'Contact_your_MEP/')]") %>%
  html_attr("href") %>%
  unique

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name	keywords
Felicitas	Development, Corruption, Housing, Transportation, Religion
Lucile	Inequality, Migration, Race and Gender, Community/Neighborhood
Corentin	Inequality, Religion, Migration, Poverty, Gender
Charlotte	Energy, Environment, Smart Cities, Conflict, Gender
Alice	Environment, Gender, Migration, Urban Studies
Miranda	Politics, Gender, Human Rights
Margaux	Inequality, Urban Studies, Migration, Human Rights
Marina	Critical Theory, Social Inequality, Race and Gender
Cosima	Race and Gender and Sexuality, Spatial Inequality, Migration 

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#' Get a PubMed search index
#' @param query a PubMed search string
#' @return the XML declaration of the search
#' @example
#' # Which articles discuss the WHO FCTC?
#' pubmed_ask("FCTC OR 'Framework Convention on Tobacco Control'")
pubmed_ask <- function(query) {
  
  # change spaces to + and single-quotes to URL-friendly %22 in query
  query = gsub("'", "%22", gsub(" ", "+", query))

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# ==============================================================================
# SESSION_INFO
#
# A script to deal with package dependencies that will
#
#  - detach all packages except base ones
#  - install its own package dependencies
#  - look for session_info.txt and parse it for packages
#  - ensure the packages are installed and up to date
#

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# removes characters from multiple data frame columns
# example removes * , % characters

dw <- data.frame(gsub("\\*|,|%", "", as.matrix(dw)), stringsAsFactors = FALSE)