geotheory

require(tidyverse)

mm_ratio = function(x) mean(x) / median(x)

x = map(10^seq(2,6,length.out = 200), ~ list(unif = runif(.x), exp = rexp(.x), log = rlnorm(.x)))

d = x %>% map_df(~ tibble(n = length(.x$unif), 
                          unif = mm_ratio(.x$unif), 
                          exp = mm_ratio(.x$exp), 
                          log = mm_ratio(.x$log)))

geotheory

require(robotstxt)
#> Loading required package: robotstxt

rt = robotstxt::get_robotstxt('bbc.com')

paths_allowed('https://bbc.com/notexists', rt_robotstxt_http_getter = rt)
#> bbc.com
#> 
#> [1] TRUE

geotheory

#acad1a
#a55151
#be551e
#b0bb1e
#ca551e
#debb1e
#0de55a
#aba5ed
#acac1a
#accede

geotheory

library(bit64)
require(tidyverse)

twepoch <- as.integer64('1288834974657')
base <- as.integer64(2)
datacenter_id_bits <- 5
worker_id_bits <- 5
sequence_id_bits <- 12
max_datacenter_id <- 1 * base^datacenter_id_bits
max_worker_id <- 1 * base^worker_id_bits

geotheory

require(R6)
# depends: {purrr}, {tibble}, {tidy} for graph conversion

Step = R6Class("Step", list(
  id = NA,
  stage = NA,
  state = NA,
  parent = NA,
  children = list(),
  open = TRUE,

geotheory

c1 = as.matrix(readr::read_csv("comp,x1,x2,y1,y2
1,0,1,2,2
2,0,1,1,1
3,0,1,2,1
4,0,1,1,2
5,0,1,2,2
5,0,1,1,2
6,1,1,1,2
7,1,1,1,2

geotheory

"user_id","status_id","created_at","screen_name","text","source","display_text_width","reply_to_status_id","reply_to_user_id","reply_to_screen_name","is_quote","is_retweet","favorite_count","retweet_count","quote_count","reply_count","hashtags","symbols","urls_url","urls_t.co","urls_expanded_url","media_url","media_t.co","media_expanded_url","media_type","ext_media_url","ext_media_t.co","ext_media_expanded_url","ext_media_type","mentions_user_id","mentions_screen_name","lang","quoted_status_id","quoted_text","quoted_created_at","quoted_source","quoted_favorite_count","quoted_retweet_count","quoted_user_id","quoted_screen_name","quoted_name","quoted_followers_count","quoted_friends_count","quoted_statuses_count","quoted_location","quoted_description","quoted_verified","retweet_status_id","retweet_text","retweet_created_at","retweet_source","retweet_favorite_count","retweet_retweet_count","retweet_user_id","retweet_screen_name","retweet_name","retweet_followers_count","retweet_friends_count","retweet_statuses_c

geotheory

library(purrr)
library(rrapply)

# Split a data frame into a nested list using a different column for each level.
# This uses rrapply::rrapply() to avoid having to do any nested loops (map, lapply,
# for loop, whatever).

# Nested lists can be useful for avoiding searching through your data: the data
# has already been indexed in the list. This can be pretty handy for saving time 
# if you need to do lots of filtering stuff. 

geotheory

require(tidyverse)
#> Loading required package: tidyverse
require(DBI)
#> Loading required package: DBI
require(RPostgres)
#> Loading required package: RPostgres

con = dbConnect(RPostgres::Postgres(), dbname = "xxx")

# toy dataset with numeric and datetime fields

geotheory

require(tidyverse)
require(DBI)
require(RPostgres)

con = dbConnect(RPostgres::Postgres(), dbname = "xxx")
dbWriteTable(con, "diamonds", diamonds, row.names=FALSE, append=FALSE)

sql_method = dbGetQuery(con, "
with price_stats as (
  select min(price) as min,