learnathon-2023

README

learnathon-2023

Convert Proper Names TSV

This is just a quick verification that the TSV parses OK.

$ cd convertToCsv/
$ go run convertToCsv.go -i ../properNames.tsv -o properNames.csv
$ 

Looks good.

Extract Places

This will extract the place data. Two output files are produced.

If places.csv is the given output, then it will also create places_significance.csv.

Note: there is a many to one relation between the places and the "significance" (and the associated references of each significance) data.

Run and import into database:

$ cd extractPlaces/
$ go run extractPlaces.go -i ../properNames.tsv -o places.csv
$ ls
extractPlaces.go  places.csv places_significance.csv
$ sqlite3 ../properNames.db
SQLite version 3.34.1 2021-01-20 14:10:07
Enter ".help" for usage hints.
sqlite> .mode csv
sqlite> .import places.csv places
sqlite> select count(*) from places;
1017
sqlite> .import places_significance.csv significance
sqlite> .schema
CREATE TABLE IF NOT EXISTS "places"(
  "UniqueName" TEXT,
  "OpenBible" TEXT,
  "Founder" TEXT,
  "People Group" TEXT,
  "GoogleMap URL" TEXT,
  "Palopenmaps URL" TEXT
);
CREATE TABLE IF NOT EXISTS "significance"(
  "UniqueName" TEXT,
  "Significance" TEXT,
  "Strongs" TEXT,
  "ESV Name" TEXT,push
  "References" TEXT
);
sqlite> select count(*) from significance ;
2414
sqlite> 

Extract Persons

Similar to above. Run the script in the extractPersons folder to create the tables: sh run.sh

Sample Queries

select EsvName, GoogleMapURL 
from places a 
inner join places_significance b 
on a.UniqueName = b.UniqueName
where a.uniquename = 'Arabia@2Sa.23.35'
;

select *
from places 
where uniquename like 'Arabia%'
limit 10;

-- Arabia@2Sa.23.35=H6152B

select * 
from places_significance 
where uniquename like 'Arabia%'
limit 10;