sadatnfs

    require(ncdf4)  
    require(ncdf4.helpers)
    require(data.table)
    
    ## Get the name of the value vars in the nc file
    get_nc_value_name <- function(nc_file) {
      
      ## Get names
      nc_obj <- nc_open(nc_file)
      name<-names(nc_obj$var)

halhen

# data from http://ec.europa.eu/eurostat/web/gisco/geodata/reference-data/population-distribution-demography/geostat
# Originally seen at http://spatial.ly/2014/08/population-lines/

# So, this blew up on both Reddit and Twitter. Two bugs fixed (southern Spain was a mess,
# and some countries where missing -- measure twice, submit once, damnit), and two silly superflous lines removed after
# @hadleywickham pointed that out. Also, switched from geom_segment to geom_line.

# The result of the code below can be seen at http://imgur.com/ob8c8ph

library(tidyverse)

simecek

conormm

R to python 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:

tomhopper

#' When plotting multiple data series that share a common x axis but different y axes,
#' we can just plot each graph separately. This suffers from the drawback that the shared axis will typically
#' not align across graphs due to different plot margins.
#' One easy solution is to reshape2::melt() the data and use ggplot2's facet_grid() mapping. However, there is
#' no way to label individual y axes.
#' facet_grid() and facet_wrap() were designed to plot small multiples, where both x- and y-axis ranges are
#' shared acros all plots in the facetting. While the facet_ calls allow us to use different scales with
#' the \code{scales = "free"} argument, they should not be used this way.
#' A more robust approach is to the grid package grid.draw(), rbind() and ggplotGrob() to create a grid of 
#' individual plots where the plot axes are properly aligned within the grid.

ramnathv

example.md: example.Rmd
	./knit

example.ipynb: example.md
	notedown example.md | sed 's/%%r/%%R/' > example.ipynb

stared

Software for scientists

Some things takes much less time and stress once you know the right tool. Below, there is a community edited list of software for scientists.

Text editors

in General purpose text/code editors. It may be better to have a good editor for everything, than different ones for different languages, scripts, notes.