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# Quick wrapper for the awesome commandlinefu.com API
# http://www.commandlinefu.com/site/api
using Requests
using JSON

BASE_URL = "http://www.commandlinefu.com/commands/"

function bestfu()
    q = BASE_URL * "browse/sort-by-votes/json"
    return JSON.parse(IOBuffer(Requests.get(q).data))

sboysel

# Prepare SpatialPolygonsDataFrame for plotting with ggplot2
# Follows https://github.com/hadley/ggplot2/wiki/plotting-polygon-shapefiles
# Assumes you are in Hadleyverse and already have dplyr loaded.

prepare_spdf <- function(spdf) {
  require(dplyr)
  reguire(ggplot2)
  spdf@data$id <- rownames(spdf@data)
  spdf.points <- ggplot2::fortify(spdf, region = "id")
  if (sum(is.na(spdf.points$hole))) {

sboysel

# Load the MNIST digit recognition dataset into R
# http://yann.lecun.com/exdb/mnist/
# assume you have all 4 files and gunzip'd them
# creates train$n, train$x, train$y  and test$n, test$x, test$y
# e.g. train$x is a 60000 x 784 matrix, each row is one digit (28x28)
# call:  show_digit(train$x[5,])   to see a digit.
# brendan o'connor - gist.github.com/39760 - anyall.org

load_mnist <- function(path = "mnist") {
  # Usage:

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#' Prints a LaTeX table with numeric columns aligned on their decimal points.
#' 
#' This function wraps the \code{\link{xtable}} and \code{\link{print.xtable}}
#' functions in the \code{xtable} package so that numeric columns are aligned
#' on their decimal place.
#' 
#' See \url{http://jason.bryer.org/posts/2013-01-04/xtable_with_aligned_decimals.html}
#' for more information.
#' 
#' @author Jason Bryer <jason@@bryer.org>

sboysel

R Spatial Analysis Notes

Spatial Analysis in R

Key Packages

• sp - defines the set of base classes for spatial data in R. Most useful for creating, converting, merging, transforming (e.g. projection), and plotting (see spplot) Spatial* objects.
• rgdal - wrapper

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#' Grouped summary statistics
#'
#' Wraps \code{\link{aggregate}} to generate common summary statistics over
#' subsets.
#'
#' @param data A data.frame to be summarized.
#' @param by Grouping variables specified by a formula as used in 
#'  \code{\link{aggregate}}.
#' @param stats A character vector of statistical functions.  Default is c("n",
#'  "mean", "sd", "min", "max").  More functions can be added by modifying the 

sboysel

# TODO: (1) What if I want to keep the remote zipfile after downloading? [x]
#       (2) Other common formats: - GeoJSON                              [x]
#                                 - KML                                  [ ]
library(rgdal)

# Functions to check filenames
is_remote <- function(x) grepl("(ht|f)tp(s)?://", x)
is_zip <- function(x) grepl("\\.zip$", basename(x))
is_shp <- function(x) grepl("\\.shp$", basename(x))
is_json <- function(x) grepl("\\.(geo)?json$", basename(x))

sboysel

library(ggplot2)
library(maptools)
library(mapproj)
library(ggthemes)
library(sp)
library(raster)
library(rgeos)
library(RColorBrewer)

# Get administrative boundaries as SpatialPolygonsDataFrame

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Notes on Econometrics in R

This note summarizes several tools for traditional econometric analysis using R. The CRAN Task View - Econometrics provides a very comprehensive overview of available econometrics packages in R. Rather the duplicate this resource, I will highlight several functions and tools that accommodate 95% of my econometric analyses.

Packages and functions

Linear Regression

• stats::lm - the standard OLS routine included in the base R package stats. The call summary(lm(y ~ x1 + x2, data = mydata)) produces output most similar to reg y x1 x2 in Stata.
• lfe - Linear Fixed Effects models. In addition to efficiently handling high-dimension fixed effects, the workhorse function felm also supports instrumental variables and clustered standard errors. As it improves lm by incorp

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license: gpl-3.0
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