trinker

if (!require("pacman")) install.packages("pacman"); library(pacman)
p_load(tidyverse, numform, viridis, ggrepel, lexicon)
p_load_current_gh('trinker/plotflow')

set.seed(13)
dat <- data_frame(
    revenue = rnorm(5000, 50000, 5000),
    date = sample(seq(as.Date('1999/01/01'), as.Date('1999/12/31'), by="day"), 5000, TRUE),
    site = sample(paste("Site", 1:5), 5000, TRUE),
    sales_person = sample(f_title(sample(lexicon::common_names, 15)), 5e3, TRUE)

trinker

In this post I have a few goals:

1. Become (re-)familiar with available geoms
2. Become (re-)familiar with aesthetic mappings in geoms (stroke who knew?)
3. Answer these questions:
<ul>
	<li>How often do various geoms appear and how often do they have required aesthetics?</li>
	<li>How often do various aesthetics appear and how often are they required?</li>
	<li>What geoms are most similar based on mappings?</li>
</ul>

trinker

# test data
before <- "A."
after <- ".Z"
x <- c("A.xyz.Z", "ABxyzYZ")

pattern <- sprintf('(?<=\\Q%s\\E).*?(?=\\Q%s\\E)', before, after)
which gives:

> gregexpr(pattern, x, perl = TRUE) > 0
[1]  TRUE FALSE

trinker

# based on https://stats.stackexchange.com/q/85560/7482
if (!require("pacman")) install.packages("pacman")
pacman::p_load(dplyr, ggplot2)

boot_dat <- lapply(1:1000, function(i){
    inds <- sample.int(nrow(mtcars), replace = TRUE)
    lm(mpg ~ hp, data = mtcars[inds, c('mpg', 'hp')])
}) %>%
    lapply(function(x) setNames(as.data.frame(t(c(x$coeff))), c('intercept', 'slope'))) %>%
    bind_rows() %>%

trinker

Main stuff below

trinker

###############################
## Plotting Likert Type Data ##
###############################
##------------------------------------------------------------------------
## Note: Plotting horizontal stacked bar plots in ggplot2 with Likert type
## data is a non-trivial task.  Stacking is not well defined for mixed
## negative/positive values on a bar.  This requires splitting the data
## set into two different parts (positive/negative), plotting each side
## separately, and filling the colors manually.  This script adds complexity
## for neutral scales.

trinker

###############################
## Plotting Likert Type Data ##
###############################
##------------------------------------------------------------------------
## Note: Plotting horizontal stacked bar plots in ggplot2 with Likert type
## data is a non-trivial task.  Stacking is not well defined for mixed
## negative/positive values on a bar.  This requires splitting the data
## set into two different parts (positive/negative), plotting each side
## separately, and filling the colors manually.
##------------------------------------------------------------------------

trinker

## From: https://stackoverflow.com/q/48479535/1000343

## First part is just to make an external text file like the OP provided.

x <- c("Month march ", "MARK ", "good in mathematic ", "JOE", "he need  help in language ", 
"SUZANA ", "he is  good  in mathematic", "MARY ", "she has  ti work hard  this month ", 
"", "", "Month April  ", "MARK ", "good in language ", "JOE", 
"he need  help in mathematics ", "SUZANA ", "he is  good  in history ", 
"MARY ", "she need  help ")

trinker

if (!require("pacman")) install.packages("pacman")
pacman::p_load(dplyr, data.table, stringi, R.utils)
## browseURL('http://storage.googleapis.com/books/ngrams/books/datasetsv2.html')

if (!dir.exists('google_ngram')) dir.create('google_ngram')
#letter <- 'b'

get_google_ngram_data <- function(letter, ...){
    
    loc <- sprintf('http://storage.googleapis.com/books/ngrams/books/googlebooks-eng-all-1gram-20120701-%s.gz', letter) %>%

trinker

make_link <- function(x = NULL){

    if (is.null(x)) x <- clipr::read_clip()

    out <- sprintf('["%s"](#%s)',
        x,
        gsub('[?/]', '', gsub(' ', '-', tolower(x)))
    )
    clipr::write_clip(out)
    cat(out)