README.md

In csps-efpc/TokenLink: Joins two dataframes using tokens or like words

TokenLink

2022-05-05

TokenLink

link two dataset using tokens or words in common between them

Install

devtools::install_github("csps-efpc/TokenLink")

Example Basic Usage

Load Libraries and Data from Internet

source('R/tokenify.R')
library(tidyr)
library(dplyr)
library(readr)
library(magrittr)
library(TokenLink)

ceo_url <- 'https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2021/2021-04-27/departures.csv'
ceo_url <- 'https://tinyurl.com/2p8etjr6'
alb_url <- 'https://open.alberta.ca/dataset/a2b1fc9b-aac4-4718-8645-b0466ca5ec57/resource/3da9a7f9-bd34-48c0-841f-19c856b551ad/download/foodindustry.csv'
alb_url <- 'https://tinyurl.com/2p8ap4ad'

# Load Data From internet
dat_ceo <- readr::read_csv(ceo_url)
dat_alb <- readr::read_csv(alb_url)

CEO Resignation data from Tidy Tuesday

| coname | exec_fullname | |:-----------------------|:----------------------| | MEDQUIST INC | David A. Cohen | | ATC TECHNOLOGY CORP | Donald T. Johnson Jr. | | E TRADE FINANCIAL CORP | Karl A. Roessner |

Data from open.alberta.ca

| companyName | address | town | province | |:------------------------|:-----------------|:-----------|:---------| | Ryley Sausage 1991 Ltd. | Box 205 | Ryley | AB | | Capital Packers Inc. | 12907 - 57 St. | Edmonton | AB | | Parmalat Canada | 3410 - 24 Ave. N | Lethbridge | AB |

Show Tokenization

dat_ceo_tokes <- 
  dat_ceo |> 
  tokenize_ations(col_nms = 'coname', token_types = 'company_name') 

dat_ceo_tokes |>
  magrittr::extract2('tokens') |> 
  group_by(row_name) |>
  nest() |> ungroup() |>
  sample_n(3) |>
  unnest() |>
  knitr::kable(caption = 'Tokens')

| row_name | token | token_type | |:---------|:-------------|:-------------| | 5648 | regency | company_name | | 5648 | centers | company_name | | 5648 | corp | company_name | | 3317 | fresh | company_name | | 3317 | choice | company_name | | 3317 | incorporated | company_name | | 5244 | wec | company_name | | 5244 | energy | company_name | | 5244 | group | company_name | | 5244 | incorporated | company_name |

Tokens

Count Tokenization

nsamp <- 4

dat_ceo_tokes |> 
  magrittr::extract2('token_counts') |> 
  {\(.) bind_rows(head(., nsamp), sample_n(.,nsamp), tail(., nsamp))}() |>
  arrange(desc(n)) |>
  knitr::kable(caption = 'Token Counts') 

| token | token_type | n | |:-------------|:-------------|-----:| | incorporated | company_name | 5064 | | corp | company_name | 2436 | | company | company_name | 728 | | group | company_name | 470 | | sprint | company_name | 7 | | internap | company_name | 6 | | blount | company_name | 4 | | mn | company_name | 4 | | zions | company_name | 1 | | zoetis | company_name | 1 | | zumiez | company_name | 1 | | zynex | company_name | 1 |

Token Counts

Create a t_dat Object

t_dat <- token_links(
  dat_x = dat_ceo,
  dat_y = dat_alb,
  args_x = list(col_nms = 'coname'),
  args_y = list(col_nms = 'companyName'),
  token_types = 'company_name',
  token_index = '',
  suffix = c('ceo', 'alb')
)

t_dat |>
  extract2('tokens_all') |>
  {\(.) bind_rows(head(., nsamp), sample_n(.,nsamp), tail(., nsamp))}() |>
  knitr::kable(caption = 'All Tokens')

| token | token_type | n.ceo | n.alb | n_comparisons | u_prob | m_prob | |:-------------|:-------------|------:|------:|--------------:|----------:|----------:| | incorporated | company_name | 5064 | 102 | 516528 | 0.1081177 | 0.9900000 | | company | company_name | 728 | 37 | 26936 | 0.0056381 | 0.9920208 | | limited | company_name | 114 | 197 | 22458 | 0.0047008 | 0.9921452 | | corp | company_name | 2436 | 9 | 21924 | 0.0045890 | 0.9921616 | | trptn | company_name | 2 | 0 | 0 | 0.0000000 | 0.9990000 | | karamel | company_name | 0 | 1 | 0 | 0.0000000 | 0.9990000 | | mcdermott | company_name | 7 | 0 | 0 | 0.0000000 | 0.9990000 | | online | company_name | 3 | 0 | 0 | 0.0000000 | 0.9990000 | | yat | company_name | 0 | 1 | 0 | 0.0000000 | 0.9990000 | | yeg | company_name | 0 | 1 | 0 | 0.0000000 | 0.9990000 | | yogurt | company_name | 0 | 1 | 0 | 0.0000000 | 0.9990000 | | zinter | company_name | 0 | 1 | 0 | 0.0000000 | 0.9990000 |

All Tokens

Find Posteriors

t_dat <- 
  t_dat |> 
  find_posterior()

t_dat$all_evidence |> 
  {\(.) bind_rows(head(., nsamp), sample_n(.,nsamp), tail(., nsamp))}() |>
  arrange(desc(posterior)) |>
  knitr::kable()

| row_name.ceo | row_name.alb | tokens_in_favour | tokens_against | priori | posterior | |:-------------|:-------------|-----------------:|---------------:|--------:|----------:| | 3115 | 40 | 3 | 1 | 3.9e-06 | 1.0000000 | | 59 | 40 | 3 | 1 | 3.9e-06 | 1.0000000 | | 5962 | 40 | 3 | 1 | 3.9e-06 | 1.0000000 | | 7464 | 40 | 3 | 1 | 3.9e-06 | 1.0000000 | | 171 | 133 | 3 | 1 | 3.9e-06 | 0.9999739 | | 172 | 133 | 3 | 1 | 3.9e-06 | 0.9999739 | | 171 | 134 | 2 | 3 | 3.9e-06 | 0.0136264 | | 6032 | 241 | 3 | 4 | 3.9e-06 | 0.0103901 | | 3041 | 241 | 3 | 4 | 3.9e-06 | 0.0103901 | | 4404 | 241 | 3 | 4 | 3.9e-06 | 0.0103901 | | 6032 | 241 | 3 | 4 | 3.9e-06 | 0.0103901 | | 6247 | 241 | 3 | 4 | 3.9e-06 | 0.0103901 |

Vissual Compare Of Results

t_dat |>  joined_results(include_row_numbers = TRUE, link_col_nms = c('posterior', 'tokens_in_favour', 'tokens_against')) |>
  {\(.) bind_rows(head(., nsamp), sample_n(.,nsamp), tail(., nsamp))}() |>
  arrange(desc(posterior)) |>
  knitr::kable()

| row_name.ceo | row_name.alb | posterior | tokens_in_favour | tokens_against | coname.ceo | companyName.alb | |:-------------|:-------------|----------:|-----------------:|---------------:|:--------------------------|:-------------------------------| | 3115 | 40 | 1.0000000 | 3 | 1 | ARCHER-DANIELS-MIDLAND CO | Archer Daniels Midland | | 59 | 40 | 1.0000000 | 3 | 1 | ARCHER-DANIELS-MIDLAND CO | Archer Daniels Midland | | 5962 | 40 | 1.0000000 | 3 | 1 | ARCHER-DANIELS-MIDLAND CO | Archer Daniels Midland | | 7464 | 40 | 1.0000000 | 3 | 1 | ARCHER-DANIELS-MIDLAND CO | Archer Daniels Midland | | 5962 | 40 | 1.0000000 | 3 | 1 | ARCHER-DANIELS-MIDLAND CO | Archer Daniels Midland | | 3167 | 133 | 0.9999739 | 3 | 1 | COCA-COLA CO | Coca-Cola Bottling Company | | 171 | 134 | 0.0136264 | 2 | 3 | COCA-COLA CO | Coca-Cola Bottling Ltd. | | 3041 | 241 | 0.0103901 | 3 | 4 | STEWART ENTERPRISES -CL A | J & A Stewart Enterprises Ltd. | | 3041 | 241 | 0.0103901 | 3 | 4 | STEWART ENTERPRISES -CL A | J & A Stewart Enterprises Ltd. | | 4404 | 241 | 0.0103901 | 3 | 4 | STEWART ENTERPRISES -CL A | J & A Stewart Enterprises Ltd. | | 6032 | 241 | 0.0103901 | 3 | 4 | STEWART ENTERPRISES -CL A | J & A Stewart Enterprises Ltd. | | 6247 | 241 | 0.0103901 | 3 | 4 | STEWART ENTERPRISES -CL A | J & A Stewart Enterprises Ltd. |

csps-efpc/TokenLink documentation built on Feb. 10, 2023, 3:30 a.m.