jeffgswanson

# Activate these packages
  library(shiny)
  library(DT)
  library(shinythemes)
  library(rvest)
  library(expss)
  library(dplyr)
  library(tidyr)
  library(stringr)

jeffgswanson

# Activate these packages
library(shiny)
library(DT)
library(shinythemes)
library(rvest)
library(expss)
library(dplyr)
library(tidyr)
library(stringr)
library(sqldf)

jeffgswanson

library(dplyr)
library(tidyr)
library(rvest)
library(tabulizer)

# Manual Class A names
School <-
  c(
    'Omaha South',
    'Omaha Central',

jeffgswanson

# SCRAPE STATS
library(RCurl)
library(XML)

# Set URL (make sure to use 'getURL' for https/secure sites)
nebrasketball2017_url <- getURL("https://www.sports-reference.com/cbb/schools/nebraska/2018-schedule.html")

# Pull data from second table on the page into a data frame for analysis
nebrasketball2017 <- readHTMLTable(nebrasketball2017_url, header = T, as.data.frame = T)[[2]]

jeffgswanson

# Access Twitter API using twitterR
# Need to have a Twitter account and can access keys, secrets, tokens by creating an app at apps.twitter.com
# Include the single quotes around your access codes

tw_consumer_key <- 'your_consumer_key'
tw_consumer_secret <- 'your_consumer_secret'
tw_access_token <- 'your_access_token'
tw_access_secret <- 'your_access_secret'

setup_twitter_oauth(tw_consumer_key, tw_consumer_secret, tw_access_token, tw_access_secret)

jeffgswanson

# Install/Library these functions:
library(forecast)
library (tidyr)
library (dplyr)
library (highcharter)

# Upload CSV file to R Studio, or other GUI containing only monthly sessions and dates
aa_data <- read.csv("~/[name of file].csv", stringsAsFactors = FALSE, header = TRUE, sep = ",")

# Check data structure of uploaded data