walkerke

library(mapgl)
library(tidycensus)
library(tigris)
options(tigris_use_cache = TRUE)

manhattan_income <- get_acs(
  geography = "tract",
  variables = "B19013_001",
  state = "NY",
  county = "New York",

walkerke

library(tidycensus)
library(tigris)
library(tidyverse)
library(sf)
library(ggiraph)
library(patchwork)
options(tigris_use_cache = TRUE)
set.seed(123456)

# Get a list of counties within the Austin CBSA using tigris

Andrei-WongE

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	[${1:text}]{.aside}
	
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	:::{.${1:type}}
		${2:body}
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veekaybee

Anti-hype LLM reading list

Goals: Add links that are reasonable and good explanations of how stuff works. No hype and no vendor content if possible. Practical first-hand accounts of models in prod eagerly sought.

Foundational Concepts

Pre-Transformer Models

tim-salabim

library(mapview)
library(leafem)
library(leaflet)
library(sf)
library(geojsonsf)

franc_ext <- unname(as.vector(st_bbox(franconia)))
francgj = geojsonsf::sf_geojson(franconia)

leaflet() |>

AlbertRapp

library(tidyverse)
big_tech_companies <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2023/2023-02-07/big_tech_companies.csv')
big_tech_companies
# # A tibble: 14 × 2
#    stock_symbol company                                  
#    <chr>        <chr>                                    
#  1 AAPL         Apple Inc.                               
#  2 ADBE         Adobe Inc.                               
#  3 AMZN         Amazon.com, Inc.                         
#  4 CRM          Salesforce, Inc.                         

AlbertRapp

library(tidyverse)
library(gt)

filtered_penguins <- palmerpenguins::penguins |> 
    filter(!is.na(sex))

penguin_weights <- palmerpenguins::penguins |> 
  filter(!is.na(sex)) |> 
  group_by(species) |> 
  summarise(

midudev

Requisitos

Necesitas tener instalado Python 3.9 e instalar la dependencia de Whisper y PyTube:

pip install git+https://github.com/openai/whisper.git
pip install pytube

También necesitas tener instalado ffmpeg. Según tu sistema operativo se instala de esta forma:

RamiKrispin

#!/bin/bash

# Launching RStuido server on a docker with different settings

# Basic run command to launce rocker container with RStudio Server
docker run -d -p 8787:8787 \
            -e USER=rstudio -e PASSWORD=rstudio \
            rocker/rstudio:4.2

# Disabling the authentication 

meghall06

# to create the plots in this Twitter thread: https://twitter.com/MeghanMHall/status/1560411406935138305

library(tidyverse)
library(ggrepel)
library(scales)

df1 <- txhousing %>%
  filter(city %in% c("Houston","Austin")) %>%
  group_by(year, city) %>%
  summarize(avg = mean(median, na.rm = TRUE)) %>%