fubits1

def measure_semantic_shift_by_neighborhood(model1,model2,word,k=25,verbose=False):
	"""
	Basic implementation of William Hamilton (@williamleif) et al's measure of semantic change
	proposed in their paper "Cultural Shift or Linguistic Drift?" (https://arxiv.org/abs/1606.02821),
	which they call the "local neighborhood measure." They find this measure better suited to understand
	the semantic change of nouns owing to "cultural shift," or changes in meaning "local" to that word,
	rather than global changes in language ("linguistic drift") use that are better suited to a
	Procrustes-alignment method (also described in the same paper.)
	
	Arguments are:

fubits1

Dummy

fubits1

{"status":"success","data":{"resultType":"matrix","result":[{"metric":{},"values":[[1528041600,"102.43391526291488"],[1528045200,"65.27196652719665"],[1528048800,"124.51882845188284"],[1528052400,"364.87669611378044"],[1528056000,"183.96696534350002"],[1528059600,"961.6033647520676"],[1528063200,"1879.493872956394"],[1528066800,"2909.280958465486"],[1528070400,"2762.5223109500967"],[1528074000,"2759.345753378236"],[1528077600,"2921.181614271897"],[1528081200,"4400.141282278818"],[1528084800,"3470.964912153553"],[1528088400,"2854.2055329831237"],[1528092000,"3478.3747877579676"],[1528095600,"4375.370035672176"],[1528099200,"5467.983879136413"],[1528102800,"3437.2946121956893"],[1528106400,"1306.4284762774053"],[1528110000,"7507.044709329386"],[1528113600,"2355.919232170903"],[1528117200,"893.1636953489782"],[1528120800,"846.2098475015198"],[1528124400,"4232.320772507555"],[1528128000,"7506.763612642862"],[1528131600,"8659.400483909612"],[1528135200,"6146.439094062068"],[1528138800,"5709.934255702872"],[1528142

fubits1

library("roomba")
json_jsonlite <- jsonlite::fromJSON("data.json",
                                    simplifyVector = FALSE,
                                    simplifyDataFrame = FALSE,
                                    simplifyMatrix = FALSE)
json_roomba <- roomba(json_jsonlite$data, cols = "values")
library(tidyverse)
json_roomba %>% str_split(",")

#jsonlite atomic level

fubits1

# gridSVG::grid.garnish can be used to add SVG attributes to elements of a plot!
# we don't even need to do it one at a time: with the option `group = FALSE`, we
# can give it a vector of values for an attribute and garnish an entire geom at
# once. the only rub is that sometimes ggplot2 shuffles your data around when
# plotting it. we need to check how the data was reordered, and arrange our
# original data to match, before we send it to grid.garnish.

library(tidyverse)
library(magrittr)
library(grid)

fubits1

---
title: "R Notebook"
output: html_document
---

```{r echo=FALSE, warning=FALSE, message=FALSE}
library(tidyverse)
library(leaflet)
library(mapview)
library(sf)

fubits1

library(tidyverse)

annotation <-"HP"

# identify max char length of y-label
ymax_chr <- nchar(as.integer(max(mtcars$hp)))

ggplot(mtcars, aes(x = mpg, y = hp)) +
  geom_point(color = "black", alpha = 0.5) +
  scale_y_continuous(

fubits1

#!/bin/bash
## libraries: sed, exiftool
# sudo apt-get install sed libimage-exiftool-perl
## if output folder is needed
# [ -d output-folder ] || mkdir output-folder # checks if output folder exists, and create if not
i=0 # to track iteration cycle for lookup by row in text file with sed
## for each JPG
for filename in source-folder/*.jpg; do
    ((i++))
    ## lookup row i in text file

fubits1

Keybase proof

I hereby claim:

• I am fubits1 on github.
• I am fubits (https://keybase.io/fubits) on keybase.
• I have a public key ASCBPqZQmVjZKFDJNPD92EEVEXLzZow-57iZx-4msM15dgo

To claim this, I am signing this object:

fubits1

create type public.continents as enum (
    'Africa',
    'Antarctica',
    'Asia',
    'Europe',
    'Oceania',
    'North America',
    'South America'
);
create table public.countries (