chemineer

#simple baduk board on python3.8x
#achievement so far
#-draw board, lines, star points (GUI by tkinter)
#-play game manually and save game record in sgf format
#
#todo lists
#-realize 'clear board' and 'exit'
#-remove 'captured stone' from the board automtically

app_name='MyBaduk'

chemineer

def solution(num):

    if num == 1 :
        return 0
    
    for i in range(500) :
        num = num / 2 if num % 2 == 0 else num*3 + 1
    
        if num == 1 :
            return i+1  # i는 0부터 시작하니까

chemineer

Collatz <- function(n) {        # 함수정의
  counter <- 0                  # 반복횟수 계산을 위한 Counter 정의
  while(n != 1){                # n이 1이 아닌 경우 계속 반복 
    if (n %% 2 == 0) {        # n이 짝수일 경우 처리 정의
      n <- n/2 
      print(n)                               
      counter <- counter + 1   
    } else {                  # n이 홀수일 경우 처리 정의
      n <- 3*n + 1
      print(n)      

chemineer

# Python program to display all the prime numbers within an interval

lower = 2
upper = 50

print("Prime numbers under", upper, "are:")

for num in range(2, upper + 1):
   # all prime numbers are greater than 1
   if num > 1:

chemineer

prime_numbers <- function(n) {
  if (n >= 2) {
    x = seq(2, n)
    prime_nums = c()
    for (i in seq(2, n)) {
      if (any(x == i)) {
        prime_nums = c(prime_nums, i)
        x = c(x[(x %% i) != 0], i)
      }
    }

chemineer

library(utils)
library(dplyr)
library(ggplot2)

data <- read.csv("https://opendata.ecdc.europa.eu/covid19/casedistribution/csv", na.strings = "", fileEncoding = "UTF-8-BOM")

COVID_KR = data %>% filter(geoId =="KR")      #한국
COVID_JP = data %>% filter(geoId =="JP")       #일본
COVID_CN = data %>% filter(geoId =="CN")     #중국
COVID_US = data %>% filter(geoId =="US")      #미국

chemineer

library(sp)
library(RColorBrewer)
gadm <- readRDS(file = "gadm36_KOR_1_sp.rds")

population <- read.csv("pop_S.csv",header=T)
population_sort <- population[order(population$Code),]
interval <- c(50,40,30,20,10,0)

population_cut <- cut(population_sort$Y2040,breaks=interval)
gadm$population <- as.factor(population_cut)