Improving your data science workflows with

Overview

Make Better Defaults

Author: Kjell Wooding [email protected]

This is the git repo for Makefiles: One great trick for making your conda environments more managable. A Pydata Global 2021 talk given on October 28, 2021 by Kjell Wooding.

Getting Started

To get started, type "make".

To follow along, watch the video once it's posted.

To learn more about Easydata, the framework that generated this repo, see the Getting Started Guide.

The Tips

  1. Use git and virtual environments. Always.
  2. Good workflow trumps good tooling
  3. Good workflow means not having to remember things
  4. Use one virtual environment per git repo. Give them both the same name.
  5. Maintain virtual environments as code.
  6. Use Lockfiles: Separate "what you want" from "what you need".
  7. Auto-document your workflow
  8. Don't be afraid to "Nuke it from orbit"

The Implementation

See https://github.com/hackalog/make_better_defaults

Directory Structure

See Project Organization for details on how this project is organized on disk.


This project was built using Easydata, a python framework aimed at making your data science workflow reproducible.

Owner
Kjell Wooding
Computer Engineer. Mathematician. Current Obsession: Reproducible Data Science
Kjell Wooding
ASTR 302: Python for Astronomy (Winter '22)

ASTR 302, Winter 2022, University of Washington: Python for Astronomy Mario Jurić Location When: 2:30-3:50, Monday & Wednesday, Winter quarter 2022 Wh

UW ASTR 302: Python for Astronomy 4 Jan 12, 2022
Using Data Science with Machine Learning techniques (ETL pipeline and ML pipeline) to classify received messages after disasters.

Using Data Science with Machine Learning techniques (ETL pipeline and ML pipeline) to classify received messages after disasters.

1 Feb 11, 2022
GWpy is a collaboration-driven Python package providing tools for studying data from ground-based gravitational-wave detectors

GWpy is a collaboration-driven Python package providing tools for studying data from ground-based gravitational-wave detectors. GWpy provides a user-f

GWpy 342 Jan 07, 2023
apricot implements submodular optimization for the purpose of selecting subsets of massive data sets to train machine learning models quickly.

Please consider citing the manuscript if you use apricot in your academic work! You can find more thorough documentation here. apricot implements subm

Jacob Schreiber 457 Dec 20, 2022
Repository created with LinkedIn profile analysis project done

EN/en Repository created with LinkedIn profile analysis project done. The datase

Mayara Canaver 4 Aug 06, 2022
INFO-H515 - Big Data Scalable Analytics

INFO-H515 - Big Data Scalable Analytics Jacopo De Stefani, Giovanni Buroni, Théo Verhelst and Gianluca Bontempi - Machine Learning Group Exercise clas

Yann-Aël Le Borgne 58 Dec 11, 2022
In this tutorial, raster models of soil depth and soil water holding capacity for the United States will be sampled at random geographic coordinates within the state of Colorado.

Raster_Sampling_Demo (Resulting graph of this demo) Background Sampling values of a raster at specific geographic coordinates can be done with a numbe

2 Dec 13, 2022
General Assembly's 2015 Data Science course in Washington, DC

DAT8 Course Repository Course materials for General Assembly's Data Science course in Washington, DC (8/18/15 - 10/29/15). Instructor: Kevin Markham (

Kevin Markham 1.6k Jan 07, 2023
A data analysis using python and pandas to showcase trends in school performance.

A data analysis using python and pandas to showcase trends in school performance. A data analysis to showcase trends in school performance using Panda

Jimmy Faccioli 0 Sep 07, 2021
Detecting Underwater Objects (DUO)

Underwater object detection for robot picking has attracted a lot of interest. However, it is still an unsolved problem due to several challenges. We take steps towards making it more realistic by ad

27 Dec 12, 2022
Functional tensors for probabilistic programming

Funsor Funsor is a tensor-like library for functions and distributions. See Functional tensors for probabilistic programming for a system description.

208 Dec 29, 2022
Python Package for DataHerb: create, search, and load datasets.

The Python Package for DataHerb A DataHerb Core Service to Create and Load Datasets.

DataHerb 4 Feb 11, 2022
Very useful and necessary functions that simplify working with data

Additional-function-for-pandas Very useful and necessary functions that simplify working with data random_fill_nan(module_name, nan) - Replaces all sp

Alexander Goldian 2 Dec 02, 2021
A crude Hy handle on Pandas library

Quickstart Hyenas is a curde Hy handle written on top of Pandas API to allow for more elegant access to data-scientist's powerhouse that is Pandas. In

Peter Výboch 4 Sep 05, 2022
Multiple Pairwise Comparisons (Post Hoc) Tests in Python

scikit-posthocs is a Python package that provides post hoc tests for pairwise multiple comparisons that are usually performed in statistical data anal

Maksim Terpilowski 264 Dec 30, 2022
WAL enables programmable waveform analysis.

This repro introcudes the Waveform Analysis Language (WAL). The initial paper on WAL will appear at ASPDAC'22 and can be downloaded here: https://www.

Institute for Complex Systems (ICS), Johannes Kepler University Linz 40 Dec 13, 2022
Titanic data analysis for python

Titanic-data-analysis This Repo is an analysis on Titanic_mod.csv This csv file contains some assumed data of the Titanic ship after sinking This full

Hardik Bhanot 1 Dec 26, 2021
HyperSpy is an open source Python library for the interactive analysis of multidimensional datasets

HyperSpy is an open source Python library for the interactive analysis of multidimensional datasets that can be described as multidimensional arrays o

HyperSpy 411 Dec 27, 2022
A probabilistic programming language in TensorFlow. Deep generative models, variational inference.

Edward is a Python library for probabilistic modeling, inference, and criticism. It is a testbed for fast experimentation and research with probabilis

Blei Lab 4.7k Jan 09, 2023
Conduits - A Declarative Pipelining Tool For Pandas

Conduits - A Declarative Pipelining Tool For Pandas Traditional tools for declaring pipelines in Python suck. They are mostly imperative, and can some

Kale Miller 7 Nov 21, 2021