alexpghayes

library(ggplot2)
library(glmnet)

x <- model.matrix(mpg ~ factor(cyl) + factor(gear) + wt * factor(gear), mtcars)
y <- mtcars$mpg

x

fit <- cv.glmnet(x, y, alpha = 1) # lasso when alpha = 1, ridge when alpha = 0

alexpghayes

I have categorical data spread across multiple columns that I would like to aggregate.

    library(tidyverse)
    
    data <- data_frame(var1 = sample(LETTERS[1:2], 50, replace = TRUE), # categorical A/B
                       var2 = sample(LETTERS[1:2], 50, replace = TRUE),
                       var3 = sample(LETTERS[1:2], 50, replace = TRUE),
                       var4 = sample(LETTERS[3:4], 50, replace = TRUE), # categorical C/D
                       var5 = sample(LETTERS[3:4], 50, replace = TRUE),
                       var6 = sample(LETTERS[3:4], 50, replace = TRUE)) %>%

alexpghayes

library(tidyverse)

get_ts <- function(group_size, ttt_p_inf, ctrl_p_inf) {
  a <- rbinom(1, size = group_size, prob = ttt_p_inf) # a
  c <- rbinom(1, size= group_size, prob = ctrl_p_inf) # c
  
  b <- group_size - a
  d <- group_size - c
  
  ((a - c) / group_size) / sqrt((a * b + c * d) / group_size ^ 3)

alexpghayes

df <- tribble(
  ~ID, ~d1, ~d2, ~d3,
  1, "G", "G", "C",
  2, NA, "G", "T",
  3, "A", NA, "G",
  4, "G", "A", "A",
  5,  NA,  NA, NA,
  6, "G", "G", "G")

merge_chr <- function(df, col, ..., fun, remove = TRUE) {

alexpghayes

library(tidyverse)

data_frame(id = 1:50,
  rel1 = sample(LETTERS[1:4], 50, replace = TRUE),
  gender1 = sample(c("M", "F", "O"), 50, replace = TRUE),
  score1 = rnorm(50),
  rel2 = sample(LETTERS[1:4], 50, replace = TRUE),
  gender2 = sample(c("M", "F", "O"), 50, replace = TRUE),
  score2 = rnorm(50)) %>% 
  gather(field, value, -id) %>% 

alexpghayes

library(tidyverse)
library(rlang)

f <- function(x, c) c * x
col_names <- c("am", "gear", "carb")

exprs <- purrr::map(col_names, ~quo(!!paste0("c_", .x) := f(!!sym(.x), 3)))
mutate(mtcars, !!!exprs)

# Error in mutate_impl(.data, dots) : Column ``:=`("c_am", f(am, 3))` is of unsupported type quoted call

alexpghayes

import numpy as np

phrases = [ \
    "I don't like Guerra", \
    "Roberto is excellent. I like Roberto.", \
    "Dobelman is a great teacher! How could you not like Dobelman!", \
    "I don't like Devika. She's not a very good teacher.", \
    "Noon is too early to go to class.", \
    "I like Ms. Poon :)", \
    "!"]

alexpghayes

library(reticulate)
library(tidyverse)

X <- rbind(
  c(1, 2),
  c(3, 4)
)

y <- cbind(
  c(3, 5)

alexpghayes

library(tidyverse)

beans <- c("Caturra", "Grusti", "Double roasted")
coffees <- c("Garuda", "Blend 101", "Blend 201", "Exxxtra special blend")
location <- c("Rwanda", "Columbia", "Peru")
people <- c("Dan Wallach", "Chris Jermaine", "Scott Rikner", "Luay")

has_bean <- tibble(
  coffee = sample(coffees, 10, replace = TRUE),
  bean_name = sample(beans, 10, replace = TRUE)

alexpghayes

# open a SQL terminal. note that my netid is aph3
runas /user:adrice\aph3 /netonly "sqlcmd -S classdb.ad.rice.edu"

# in the SQL terminal, make sure things work
CREATE DATABASE apgha1db
USE apgha1db;
GO

# populate the database we just created. note that C:\Users\alex\Desktop\comp330\a1\ is the path to where I kept my A1 files