✏️Guide

We’re going to wrangle and analyze data input from a bird-watching group.

Let’s just read a CSV. It looks like this:

species,person,date,notes
Blue Jay,Kerri Johnson,2021-05-14,perched in a tree

We’d like to declare what this should look like.

import typeddfs as tdf

Sightings = (
    tdf.typed("Sightings")
    .require("species", "person", "date")
    .reserve("notes")
    .strict()
    .build()
)

Let’s try reading a malformed CSV that is missing the “date” column.

Sightings.read_csv("missing_col.csv")

This will raise a typeddfs.errors.MissingColumnError.

Much more to come…

Serialization

Typing rules

Construction and customization

New functions

Natural sorting.

✏️Guide

Serialization

Typing rules

Construction and customization

New functions

Matrix types

Imperative declaration

Data types and freezing

Checksums and caching

Advanced serialization

Generating CLI-style help

Utilities