tomschenkjr

# This is a conceptual study to leverage the tidyverse syntax and lazy
# evaluation concepts (influenced by sparklyr) to approach API wrapper packages.
#
# Problem statement: API wrappers often require users to download *all* data
# to manipulate and filter the information. Some packages support custom
# queries but often complicate syntax by adding many parameters within the
# function that may be hard for data scientists to formulate.
#
# Potential solution: API queries can be separated into three principal parts.
# First, to query the API metadata to understand column names and data types.

tomschenkjr

library(devtools)
install_github("Chicago/RSocrata" ref = "issue124") # RSocrata 1.7.2-7 or above 
library(RSocrata)

#' Exports CSVs from Socrata data portals
#' 
#' Input the URL of a data portal (e.g., "data.cityofchicago.org") and
#' will download all CSV files (no other files supported) and saved in
#' a single directory named after the root URL (e.g., "data.cityofchicago.org/").
#' Downloaded files are compressed to GZip format and timestamped so the download

tomschenkjr

Public Function BASE64SHA1(ByVal sTextToHash As String)

    Dim asc As Object
    Dim enc As Object
    Dim TextToHash() As Byte
    Dim SharedSecretKey() As Byte
    Dim bytes() As Byte
    Const cutoff As Integer = 5

    Set asc = CreateObject("System.Text.UTF8Encoding")

tomschenkjr

# A note on how to geocode using R, since I always forget

library(tigris) # also loads 'sp'
library(RSocrata)

# Obtain data
d <- read.socrata("https://data.cityofchicago.org/Education/Connect-Chicago-Locations/bmus-hp7e")
ccgeo <- tracts(state = '17', county = c('031'), cb = T) ## cb=T means smaller file

# Data organization

tomschenkjr

# Notes from Julia Workshop: From Installed to Productive
# 2014-11-15
# http://www.meetup.com/JuliaChicago/events/216950712/


println("hello world") # => hello world

x = 5

## IF statements

tomschenkjr

[
  {
    "op": "core/text-transform",
    "description": "Text transform on cells in column Phone Number using expression grel:value.replace(\" -\",\"\")",
    "engineConfig": {
      "facets": [],
      "mode": "row-based"
    },
    "columnName": "Phone Number",
    "expression": "grel:value.replace(\" -\",\"\")",

tomschenkjr

City of Chicago
Individual Contributor License Agreement ("Agreement") 
======================================================

Thank you for your interest in [Project Name] by the City of Chicago (the "City"), 
a municipal corporation and home rule unit of local government existing under the 
Constitution of the State of Illinois. In order to clarify the intellectual property 
license granted with Contributions from any person or entity, the City must have a 
Contributor License Agreement ("CLA") on file that has been signed by each Contributor, 
indicating agreement to the license terms below. This license is for your protection 

tomschenkjr

CoefficientPlot <- function(models, alpha = 0.05, modelnames = ""){
  # models must be a list()

  Multiplier <- qnorm(1 - alpha / 2)
  CoefficientTables <- lapply(models, function(x){summary(x)$coef})
  TableRows <- unlist(lapply(CoefficientTables, nrow))

  if(modelnames[1] == ""){
    ModelNameLabels <- rep(paste("Model", 1:length(TableRows)), TableRows)
    } else {

tomschenkjr

# Install reshape package. You will be asked to pick a server.
install.packages("reshape")

# We're going to also use ggplot2, so let's install that as well:
install.packages(c("reshape","ggplot2")) # In R, c() concatenates inputs as a vector

# You will always need to load the libraries after installing the package.
library(reshape)
library(ggplot2)

tomschenkjr

# Let's customize our plot outputs. First, load the library.

library(ggplot2)

# Plot something simple

p <- ggplot(mtcars, aes(x=cyl, y=mpg)) + geom_point(aes(color=qsec, size=wt))

# Change axis
p + scale_y_continuous(limits=c(0,40))