jrosen48

from facebook_scraper import get_posts
import pandas as pd
import time
import json

# param
n_pages_to_iterate = 100 # number of pages to scrape within one FB page

# reading data with page names
district_data = pd.read_csv("2020-2021-critical-race-posts-schools-districts.csv")

jrosen48

from facebook_scraper import *
import pandas as pd

set_user_agent("Mozilla/5.0 (compatible; Googlebot/2.1; +http://www.google.com/bot.html)")

page = pd.DataFrame()

for post in get_posts('245937932251091/posts/2129192957258903', pages=10 ,options={"comments": True}, credentials = ("jrosenb8@utk.edu","025021")):
    page = page.append(post, ignore_index = True)

jrosen48

library(tidyverse)
library(googlesheets4)

# this is an example Google Sheet
d <- read_sheet("https://docs.google.com/spreadsheets/d/1kz2LlLgXkN_HaBEAiFETl59b09u9AwMIgrwQx6DCv8A/edit#gid=0", col_names = FALSE)

prep_otter_transcript <- function(d, length_less_than_100_min) {

  d <- d %>% rename(x1 = 1)

jrosen48

# apply for access to Twitter's academic program: https://developer.twitter.com/en/solutions/academic-research

library(academictwitteR)
library(rtweet)
library(tidytags) # must be installed first with: remotes::install_github("ropensci/tidytags")

bearer_token <- "xxx" # Insert bearer token from developer.twitter.com from the your academic account

trial <- get_all_tweets("#BAmazonUnion OR #UnionizeAmazon", "2020-01-01T00:00:00Z", "2021-05-01T00:00:00Z", bearer_token, data_path = NULL)

jrosen48

library(tidyverse)
library(tidytuesdayR)
library(janitor)

tt_output <- tt_load_gh(last_tuesday())
list_of_d <- tt_download(tt_output)

d <- list_of_d$animal_complaints

d %>%

jrosen48

library(tidyverse)
library(readxl)
d <- read_excel("Downloads/Public-Dataset-Age.xlsx")
d %>% 
    mutate(month = lubridate::month(DATE, label = TRUE)) %>% 
    group_by(month, AGE_RANGE) %>% 
    summarize(total_cases = sum(NEW_ARCASES)) %>% 
    filter(AGE_RANGE != "Pending") %>% 
    mutate(total_cases_prop = total_cases / sum(total_cases)) %>% 
    ggplot(aes(y = total_cases_prop, x = AGE_RANGE, fill = as.factor(month))) +

jrosen48

The Generality Widget

The goal of this document

The goal of this document is to describe how and why we created The Generality Widget and how we made it, focusing on:

• What data we used
• How we coded the data
• How we prepared the data
• How we analyzed the data

jrosen48

library(shiny)

ui <- fluidPage(

    titlePanel("How Many Reviewers?"),

    sidebarLayout(
        sidebarPanel(
            numericInput("n_papers", "Number of Anticipated Papers", 100),
            numericInput("n_reviews", "Number of Reviews Per Paper", 3),

jrosen48

library(shiny)
library(tidyverse)

d <- read_csv("https://raw.githubusercontent.com/nytimes/covid-19-data/master/us-counties.csv")

states <- d %>% 
    pull(state) %>% 
    unique() %>% 
    sort()

jrosen48

#
# This is a Shiny web application. You can run the application by clicking
# the 'Run App' button above.
#
# Find out more about building applications with Shiny here:
#
#    http://shiny.rstudio.com/
#

library(shiny)