alekrutkowski

# just a stub to change the title of the gist

alekrutkowski

# Convert Excel column letter codes to numbers
# Very similar to openxlsx::convertFromExcelRef() (see https://rdrr.io/cran/openxlsx/man/convertFromExcelRef.html).
# The inverse function to openxlsx::int2col() (see https://rdrr.io/cran/openxlsx/man/int2col.html).
#
# excelColsToInt(c('a','F','x','aa','az','aaa','a','Az','aZ','AZ'))
# #=>  int [1:10]   1   6   24  27   52   703   1   52   52   52
#
# x <- c('a','F','x','aa','az','aaa','a','Az','aZ','AZ')
# n <- excelColsToInt(x)
# x2 <- openxlsx::int2col(n)

alekrutkowski

# Parse Oracle metadata SQL file obtained via "Quick DDL > Save to File..."
# (see https://stackoverflow.com/a/14262027)
# in Oracle SQL Developer (tested with version 19.2.1.247.2212)
# into R code which builds a list of data.tables with 0 length columns
# which can be later visualised via autoschema::schema -- see
# the example:

# r_code <- parseQDDL('exported.sql')  ## the top-level function defined below
# library(autoschema)  ## it can be obtained from https://github.com/alekrutkowski/autoschema
# schema(eval(parse(text=r_code)))  ## see the graph or...

alekrutkowski

library(magrittr)
library(data.table)

summaries <- function(dt, col_names, fun_names, additional_code, by, sep='__')
  eval(parse(
    text=
      expand.grid(var=col_names, fun=fun_names) %>% 
      {paste0('`',.$fun,sep,.$var,'`=`',.$fun,'`(',.$var,')')} %>%
      c(additional_code) %>% 
      paste(collapse=',') %>% 

alekrutkowski

import eurostat
import pandas as pd

def importData(EurostatDatasetCode, flags=False):
    """
    Import a dataset from Eurostat as a flat/melted table (pandas dataframe)

    Parameter
    ----------
    EurostatDatasetCode : str

alekrutkowski

# ##  Example:            ⮦ time=3 missing
# library(magrittr)
# data.table(time = c(1,2, 4,5,6,
#                     1,2),
#            my_x = c(11:15,
#                     11,12),
#            my_y = c(101,103,105,NA,109,
#                     111,121),
#            group = c(rep.int('a',5),
#                      rep.int('b',2))) %>%

alekrutkowski

library(magrittr)

monthToQuarter <- function(charvec, safe=TRUE) {
  # monthToQuarter(c('2022M01','2022M02','2022M03','2022M04',
  #                 NA_character_,'2022M12'))
  # #  "2022Q1"  "2022Q1"  "2022Q1"  "2022Q2"  NA  "2022Q4"
  if (safe)
    stopifnot(all(grepl('^[1-2][0-9]{3}M[0-1][0-9]',
                        charvec) | is.na(charvec)))
  yr <-

alekrutkowski

library(magrittr)
library(data.table)

download.file('https://ec.europa.eu/economy_finance/db_indicators/ameco/documents/ameco0.zip',
              'ameco0.zip')
time_stamp <-
  'https://ec.europa.eu/info/business-economy-euro/indicators-statistics/economic-databases/macro-economic-database-ameco/download-annual-data-set-macro-economic-database-ameco_en' %>% 
  rvest::read_html() %>% 
  rvest::html_elements(xpath='//*[@id="block-ewcms-theme-main-page-content"]/article/div/div/div/div[2]/div/div/p[1]/text()[2]') %>%
  rvest::html_text() %>%

alekrutkowski

options(width=200)
if (interactive()) {
  message('================================================================================')
  ab <- function(sym_as_str, fun)
    makeActiveBinding(sym_as_str, fun, .GlobalEnv)
  
  library(magrittr)
  message('- Imported package `magrittr`')
  
  library(data.table)

alekrutkowski

main = do
  putStrLn $ show $ add (MyInt 1) (MyInt 3)
    -- MyInt 4
  putStrLn $ show $ add (MyInt 13) (MyString "B")
    -- MyString "13B"
  putStrLn $ show $ add (MyString "B") (MyInt 13)
    -- MyString "B13"
  putStrLn $ show $ add (MyString "a") (MyString "b")
    -- MyString "ab"
  putStrLn $ show $ add' $ IntInt 1 3