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Moore's Law

This week's data is from Wikipedia - by way of the Data Is Beautiful Subreddit.

Additional info and graphics can be found at Our World in Data.

Moore's Law: Transistors per microprocessor

  • The observation that the number of transistors in a dense integrated circuit doubles approximately every two years.

Get the data!

cpu <- readr::read_csv("https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2019/2019-09-03/cpu.csv")

gpu <- readr::read_csv("https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2019/2019-09-03/gpu.csv")

ram <- readr::read_csv("https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2019/2019-09-03/ram.csv")

Data Dictionary

cpu.csv

variable class description
processor character Processor name
transistor_count double Number of transitors
date_of_introduction double year introduced
designer character Designer
process double Size of manufacturing process (in nanometers)
area double Area of chip in square millimeters

gpu.csv

variable class description
processor character Processor name
transistor_count double Transistor count
date_of_introduction double year introduced
designer_s character designer
manufacturer_s character manufacturer
process double size of manufacturing process (nanometers)
area double area of chip in square millimeters
ref character reference

ram.csv

variable class description
chip_name character Chip name
capacity_bits character capacity bits - essentially how many units of information it can work on, units in next column
bit_units character Units for bit capacity (bits < kb < Mb < Gb)
ram_type character Ram type
transistor_count double Transistor count
date_of_introduction double Year introduced
manufacturer_s character Manufactured
process double Size of manufacturing process (nanometers)
area double Area of chip in square millimeters
ref character reference

Cleaning Script

library(tidyverse)
library(rvest)

url <- "https://en.wikipedia.org/wiki/Transistor_count"

tables <- url %>% 
  read_html() %>% 
  html_table(fill = TRUE)

df1 <- tables %>% chuck(1) %>% 
  janitor::clean_names() %>% 
  as_tibble()

df1_clean <- df1 %>% 
  mutate(
    # transistor_count = gsub("\\[[^\\]]*\\]", "", transistor_count, perl=TRUE),
    transistor_count = str_remove(transistor_count, "\\[[^\\]]*\\]"),
    transistor_count = str_remove(transistor_count, "[:punct:]+"),
    transistor_count = str_remove(transistor_count, "\\[[^\\]]*\\]"),
    transistor_count = str_remove(transistor_count, "[:punct:]+"),
    transistor_count = str_remove(transistor_count, "[:punct:]+"),
    transistor_count = str_extract(transistor_count, "[:digit:]+"),
    date_of_introduction = str_sub(date_of_introduction, 1, 4),
    process = str_remove(process, ","),
    process = str_extract(process, "[:digit:]+"),
    area = str_extract(area, "[:digit:]+")
    ) %>% 
  mutate_at(.vars = vars(transistor_count:date_of_introduction, process:area), as.double)


df1_clean %>%
  mutate() 
df2 <- tables %>% chuck(2) %>% 
  janitor::clean_names() %>% 
  as_tibble()

df2_clean <- df2 %>% 
  mutate(
    # transistor_count = gsub("\\[[^\\]]*\\]", "", transistor_count, perl=TRUE),
    transistor_count = str_remove(transistor_count, "\\[[^\\]]*\\]"),
    transistor_count = str_remove(transistor_count, "[:punct:]+"),
    transistor_count = str_remove(transistor_count, "\\[[^\\]]*\\]"),
    transistor_count = str_remove(transistor_count, "[:punct:]+"),
    transistor_count = str_remove(transistor_count, "[:punct:]+"),
    transistor_count = str_extract(transistor_count, "[:digit:]+"),
    process = str_remove(process, ","),
    process = str_extract(process, "[:digit:]+"),
    area = str_extract(area, "[:digit:]+")
  ) %>% 
  mutate_at(.vars = vars(transistor_count:date_of_introduction, process:area), as.double)

df3 <- tables %>% chuck(4) %>% 
  janitor::clean_names() %>% 
  as_tibble()

df3

df3_clean <- df3 %>% 
  mutate(
    # transistor_count = gsub("\\[[^\\]]*\\]", "", transistor_count, perl=TRUE),
    transistor_count = str_remove(transistor_count, "\\[[^\\]]*\\]"),
    transistor_count = str_remove(transistor_count, "[:punct:]+"),
    transistor_count = str_remove(transistor_count, "\\[[^\\]]*\\]"),
    transistor_count = str_remove(transistor_count, "[:punct:]+"),
    transistor_count = str_remove(transistor_count, "[:punct:]+"),
    transistor_count = str_extract(transistor_count, "[:digit:]+"),
    date_of_introduction = if_else(
      str_length(date_of_introduction) >= 5,
      str_sub(date_of_introduction, -4),
      str_sub(date_of_introduction, 1, 4)),
    process = str_remove(process, ","),
    process = str_extract(process, "[:digit:]+"),
    area = str_extract(area, "[:digit:]+"),
    bit_units = case_when(
      str_detect(capacity_bits, "bit") ~ "Bits",
      str_detect(capacity_bits, "kb") ~ "kb",
      str_detect(capacity_bits, "Mb") ~ "Mb",
      str_detect(capacity_bits, "Gb") ~ "Gb",
      TRUE ~ ""
                 )
  ) %>% 
  mutate_at(.vars = vars(transistor_count:date_of_introduction, process:area), as.double) %>% 
  select(chip_name, capacity_bits, bit_units, everything()) %>% 
  mutate(capacity_bits = str_extract(capacity_bits, "[:digit:]+"))

df3_clean

write_csv(df1_clean, here::here("2019", "2019-09-03", "cpu.csv"))
write_csv(df2_clean, here::here("2019", "2019-09-03", "gpu.csv"))
write_csv(df3_clean, here::here("2019", "2019-09-03", "ram.csv"))