I have some not-quite-columnar data like this:

"hello", "2024 JAN", "2024 FEB"
"a", 0, 1

If it were truly columnar, it would look like:

"hello", "year", "month", "value"
"a", 2024, "JAN", 0
"a", 2024, "FEB", 1

Suppose the data is in the form of a numpy array, like this:

import numpy as np

data = np.array([["hello", "2024 JAN", "2024 FEB"], ["a", "0", "1"]], dtype="<U")
data

array([['hello', '2024 JAN', '2024 FEB'],
       ['a', '0', '1']], dtype='<U8')

Imagine also that I created a table:

import duckdb as ddb

conn = ddb.connect("hello.db")
conn.execute("CREATE TABLE columnar (hello VARCHAR, year UINTEGER, month VARCHAR, value UINTEGER);")

How could I go about efficiently inserting data into the DuckDB table columnar?

The naive/easy way would be to transform the data into a columnar format in-memory, in Python, before inserting it into the DuckDB table. This will be slow though, if I have a lot of data…