WooheonHong

find_ratio <- function(.df, ...) {
  group_var <- enquos(...)
  result <- 
    .df %>% 
    group_by(!!!group_var) %>% 
    summarise(n = n(), avg_n = n / nrow(.))  
  
  return(result)
}

WooheonHong

class Timer:
    def __init__(self):
        self.start = time.time()

    def restart(self):
        self.start = time.time()

    def get_time_hhmmss(self):
        end = time.time()
        m, s = divmod(end - self.start, 60)

WooheonHong

import random
import time

import numpy as np
import pandas as pd

import torch
import torch.nn as nn
import torch.nn.functional as f

WooheonHong

df_periodicity <- filter(df, id %in% sample(unique), month == 12, day == 29)
df_event <- 
  df %>% 
  filter(month == 12, day == 29) %>%
  semi_join(df_periodicity, by = "id") %>% 
  mutate(
    var1 = if_else(var1 == 0, NA, var1) # Except Events that do not occur 
    var2 = if_else(var2 == 0, NA, var2) 
  )

WooheonHong

plot_na <- function(df, start_date, end_date) {
  start_date <- paste(start_date, "00:00:00")
  end_date <- paste(end_date, "00:00:00")
  
  g <- 
    df %>% 
    filter(id %in% sample(unique(id), 20)) %>% 
    ggplot(aes(dt, 0)) +
    geom_point() +
    sacle_x_datetime(limits = ymd_hms(c(start_date, end_date))) +