Adding column to sqlite database and distribute rows based on primary key - sql

Question

I have some data elements containing a timestamp and information about Item X sales related to this timestamp.
e.g.
timestamp | items X sold
------------------------
1 | 10
4 | 40
7 | 20
I store this data in an SQLite table. Now I want to add to this table. Especially if I get data about another item Y.
The item Y data might or might not have different timestamps but I want to insert this data into the existing table so that it looks like this:
timestamp | items X sold | items Y sold
------------------------------------------
1 | 10 | 5
2 | NULL | 10
4 | 40 | NULL
5 | NULL | 3
7 | 20 | NULL
Later on additional sales data (columns) must be added with the same scheme.
Is there an easy way to accomplish this with SQLite?
In the end I want to fetch data by timestamp and get an overview which items were sold at this time. Most examples consider the usecase to add a complete row (one record) or a complete column if it perfectly matches to the other columns.
Or is sqlite the wrong tool at all? And I should rather use csv or excel?
(Using pythons sqlite3 package to create and manipulate the DB)
Thanks!

Answer 1

Dynamically adding columns is not a good design. You could add them using
ALTER TABLE your_table ADD COLUMN the_column_name TEXT
the column, for existing rows would be populated with nulls, although you could specify a DEFAULT value and the existing rows would then be populated with that value.
e.g. the following demonstrates the above :-
DROP TABLE IF EXISTS soldv1;
CREATE TABLE IF NOT EXISTS soldv1 (timestamp INTEGER PRIAMRY KEY, items_sold_x INTEGER);
INSERT INTO soldv1 VALUES(1,10),(4,40),(7,20);
SELECT * FROM soldv1 ORDER BY timestamp;
ALTER TABLE soldv1 ADD COLUMN items_sold_y INTEGER;
UPDATE soldv1 SET items_sold_y = 5 WHERE timestamp = 1;
INSERT INTO soldv1 VALUES(2,null,10),(5,null,3);
SELECT * FROM soldv1 ORDER BY timestamp;
resulting in the first query returning :-
and the second query returning :-
However, as stated, the above is not considered a good design as the schema is dynamic.
You could alternately manage an equivalent of the above with the addition of either a new column (to also be part of the primary key) or by prefixing/suffixing the timestamp with a type.
Consider, as an example, the following :-
DROP TABLE IF EXISTS soldv2;
CREATE TABLE IF NOT EXISTS soldv2 (type TEXT, timestamp INTEGER, items_sold INTEGER, PRIMARY KEY(timestamp,type));
INSERT INTO soldv2 VALUES('x',1,10),('x',4,40),('x',7,20);
INSERT INTO soldv2 VALUES('y',1,5),('y',2,10),('y',5,3);
INSERT INTO soldv2 VALUES('z',1,15),('z',2,5),('z',9,25);
SELECT * FROM soldv2 ORDER BY timestamp;
This has replicated, data-wise, your original data and additionally added another type (column items_sold_z) without having to change the table's schema (nor having the additional complication of needing to update rather than insert as per when applying timestamp 1 items_sold_y 5).
The result from the query being :-
Or is sqlite the wrong tool at all? And I should rather use csv or excel?
SQLite is a valid tool. What you then do with the data can probably be done as easy as in excel (perhaps simpler) and probably much simpler than trying to process the data in csv format.
For example, say you wanted the total items sold per timestamp and how many types were sold then :-
SELECT timestamp, count(items_sold) AS number_of_item_types_sold, sum(items_sold) AS total_sold FROM soldv2 GROUP by timestamp ORDER BY timestamp;
would result in :-