GeorgeOduor

from selenium import webdriver
from selenium.webdriver.common.keys import Keys
from selenium.webdriver.common.by import By
from selenium.webdriver.chrome.options import Options
from selenium.webdriver.chrome.service import Service
from bs4 import BeautifulSoup as bs
from datetime import datetime
import pygsheets
import pandas as pd
from time import sleep

GeorgeOduor

rm(list = ls())
library(pdftools)
library(magick)
library(mbanalytics)
library(R6)
statement = "E:/Reports/improptu/Oct/KaribuStatement.pdf"
# pdf_file <- pdf_convert(statement,pages = 1,dpi = 100)


file = pdf_text(pdf = statement)

GeorgeOduor

rm(list = ls())
library(tidyverse)
library(R6)

# datastes ------
set.seed(1)
population1 = tibble(x = rnorm(20.00, 20, 5),
                     y = rnorm(20.00, 15, 5),)
population2 = tibble(x = rpois(3231, 50),
                     y = rnorm(3231, 45),)

GeorgeOduor

---
title: "Basic Statistics"
author: "George"
date: "8/2/2021"
output: html_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```

GeorgeOduor

# This script simulates a simple core banking system in R.Its an illustration of Object oriented programming in R
CBS <- R6Class(classname = "CBS",public = list(
  accs = tibble("Full Name" = NA,"IDNo" = NA,'AccountNo' = NA,'AccountBalance' = NA,'LoanBalance' = NA),
  bank_name = NA,
  initialize = function(accs = NULL,bank_name) {
    self$bank_name = bank_name
    cat(paste(' --------- \n This is ',self$bank_name,'. \n --------- \n'))
  },
  create_account = function(FirstName=NULL,SecondName=NULL,IDNo=NULL) {
    FirstName = readline(prompt = "Enter FirstName: ")

GeorgeOduor

# want to keep retryng until a condition is met then run your script?here you go......

library(futile.logger)
library(utils)

eod_check <- function(){
  eod_file = readxl::read_excel('D:/test.xlsx')
  return(eod_file$Status)
}
retry_until <- function(expr, maxErrors=5, sleep=0) {

GeorgeOduor

# i used these linses of code to scrap african gendernames from the internet for one of my projects, it may not help you
library(rvest)
library(mbanalytics)
url = "https://www.momjunction.com/baby-names/african/page/%s/"
Allnames = 1:20%>% 
  map_df(~sprintf(url,.) %>% 
           read_html() %>% html_table(fill = T) %>% as.data.frame()  %>% 
           select(NAMES,GENDER) %>%  filter(!grepl("googletag.cmd.",NAMES),GENDER != "Unisex") %>% 
           mutate(GENDER = ifelse(GENDER == "Boy","M","F"),  NAMES = tolower(NAMES))) %>% 
  rename_all(tolower)