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[ARCHIVED] This starter is no longer maintained.

You can still find the starter code in older release tags: https://github.com/kedro-org/kedro-starters/tree/0.18.14/pandas-iris

The pandas-iris Kedro starter

This starter is unavailable in Kedro version 0.19.0 and beyond and the latest version of Kedro that supports it is Kedro 0.18.14. To check the version of Kedro you have installed, type kedro -V in your terminal window. To install a specific version of Kedro, e.g. 0.18.14, type pip install kedro==0.18.14.

To create a project with this starter using kedro new, type the following (assuming Kedro version 0.18.14):

kedro new --starter=pandas-iris --checkout=0.18.14

Introduction

The code in this repository demonstrates best practice when working with Kedro. It contains a Kedro starter template with some initial configuration and an example pipeline, and originates from the Kedro Iris dataset example.

An example pipeline using only native Kedro

This Kedro starter uses the simple and familiar Iris dataset. It contains the code for an example machine learning pipeline that runs a 1-nearest neighbour classifier to classify an iris.

The pipeline includes:

  • A node to split the data into training dataset and testing dataset using a configurable ratio
  • A node to run a simple 1-nearest neighbour classifier and make predictions
  • A node to report the accuracy of the predictions performed by the model