tmasjc

library(tidyverse)
library(rlang)
set.seed(123)

df <- tibble(id = rep(c(1:2), 10),
             grade = sample(c("A", "B", "C"), 20, replace = TRUE))

df %>% 
    group_by(id) %>% 
    summarise(

tmasjc

library(tidyverse)
library(janitor)
library(EnvStats)
library(infer)
library(ggthemes)
set.seed(123)
old = theme_set(theme_minimal(base_family = "Noto Sans CJK SC") +
                    theme(legend.position = "top"))

# DID ----

tmasjc

library(feather)
library(dplyr)
library(purrr)
library(furrr)
library(uaparserjs)

raw <- feather::read_feather("raw.feather") %>% 
    `[[`('ua') %>% 
    purrr::discard(is.na) %>% 
    unique()

tmasjc

library(tidyverse)
library(ggthemes)
library(lubridate)
library(gganimate)

# ggplot theme
old <- theme_set(
    theme_minimal() +
        theme(
            text = element_text(family = 'Menlo'),

tmasjc

set.seed(1234)

vec   = c(13.1, 7.5, 4.4, 10.0, 7.8, 3.4, 3.5) / 100
rb    = EnvStats::ebeta(vec)
alpha = rb$parameters['shape1'] 
beta  = rb$parameters['shape2']

x <- rbeta(1000, shape1 = alpha, shape2 = beta)
hist(
    x,

tmasjc

cuts = 0.8 # cutoff level
maxN = 100 # number of trials
    
run_game <- function(vec, cutoff, N) {
    # browser()
    if (length(vec) > N) {
        return(vec)
    }
    pass = ifelse(mean(vec) >= cutoff, 0, 1)
    vec  = c(vec, pass)

tmasjc

## the game goes like this,
## head +1 point and tail -1 point
## we flip 3 coins and count the score
## is there a correlation between them?

library(tidyverse)
library(ggthemes)
set.seed(1234)

coins = 4

tmasjc

library(tidyverse)

# some dummy data
df <- read_csv("dummy.csv")

# loess fitting via ggplot2
df %>%
    mutate(batch = factor(batch,
                          ordered = TRUE,
                          levels = paste0("X00", 1:12))) %>%

tmasjc

Sub MergeSimilarCells()
    Application.DisplayAlerts = False
    Application.ScreenUpdating = False
    'Specify column here
    Set myRange = Range("B2:B223")

CheckAgain:
    For Each cell In myRange
        If cell.Value = cell.Offset(1, 0).Value And Not IsEmpty(cell) Then
            Range(cell, cell.Offset(1, 0)).Merge

tmasjc

library(furrr)
# for parallel computing 
future::plan(future::multiprocess)
options(future.globals.maxSize = 900*1024^2)

# remove significant jump in May 2020
max_date <- as.Date("2020-03-02")

# sequence of backtest
date_seq <- purrr::map(0:36, ~ max_date - months(1 * .x))