A tutorial on DataFrames.jl prepared for JuliaCon2021

Overview

JuliaCon2021 DataFrames.jl Tutorial

This is a tutorial on DataFrames.jl prepared for JuliaCon2021.

A video recording of the tutorial is available here.

In order to run the tutorial make sure that you have Julia executable installed. The tutorial was updated to Julia 1.7.0 and DataFrames.jl 1.3.0.

To check the version presented during JuliaCon 2021 please check out this commit from the repository.

Then the simplest way to run it is to proceed as follows:

  1. Clone the tutorial repository to a local folder on your computer.
  2. Start Julia in your local folder using the julia --project command.
  3. Run the following commands:
using Pkg
Pkg.instantiate()
Pkg.status()

The last command should produce the following output:

  [e28b5b4c] Bootstrap v2.3.3
  [336ed68f] CSV v0.9.11
  [324d7699] CategoricalArrays v0.10.2
  [8be319e6] Chain v0.4.10
  [a93c6f00] DataFrames v1.3.0
  [38e38edf] GLM v1.5.1
  [7073ff75] IJulia v1.23.2
  [91a5bcdd] Plots v1.25.1
  [f3b207a7] StatsPlots v0.14.29
  1. Start Jupyter Notebook with:
using IJulia
notebook(dir=pwd())
  1. In the Jupyter Notebook open the Tutorial.ipynb file and follow the tutorial.

Steps 3 and 4 need to be run only once. They are intended to make sure that you have the required packages properly instantiated.

You can find more tutorials on DataFrames.jl in its documentation and in my blog.

Owner
Bogumił Kamiński
Bogumił Kamiński
An implementation of Fastformer: Additive Attention Can Be All You Need in TensorFlow

Fast Transformer This repo implements Fastformer: Additive Attention Can Be All You Need by Wu et al. in TensorFlow. Fast Transformer is a Transformer

Rishit Dagli 139 Dec 28, 2022
ByteTrack(Multi-Object Tracking by Associating Every Detection Box)のPythonでのONNX推論サンプル

ByteTrack-ONNX-Sample ByteTrack(Multi-Object Tracking by Associating Every Detection Box)のPythonでのONNX推論サンプルです。 ONNXに変換したモデルも同梱しています。 変換自体を試したい方はByteT

KazuhitoTakahashi 16 Oct 26, 2022
make ASCII Art by Deep Learning

DeepAA This is convolutional neural networks generating ASCII art. This repository is under construction. This work is accepted by NIPS 2017 Workshop,

OsciiArt 1.4k Dec 28, 2022
AOT (Associating Objects with Transformers) in PyTorch

An efficient modular implementation of Associating Objects with Transformers for Video Object Segmentation in PyTorch

162 Dec 14, 2022
Streaming Anomaly Detection Framework in Python (Outlier Detection for Streaming Data)

Python Streaming Anomaly Detection (PySAD) PySAD is an open-source python framework for anomaly detection on streaming multivariate data. Documentatio

Selim Firat Yilmaz 181 Dec 18, 2022
Protect against subdomain takeover

domain-protect scans Amazon Route53 across an AWS Organization for domain records vulnerable to takeover deploy to security audit account scan your en

OVO Technology 0 Nov 17, 2022
Vector Neurons: A General Framework for SO(3)-Equivariant Networks

Vector Neurons: A General Framework for SO(3)-Equivariant Networks Created by Congyue Deng, Or Litany, Yueqi Duan, Adrien Poulenard, Andrea Tagliasacc

Congyue Deng 332 Dec 29, 2022
ICSS - Interactive Continual Semantic Segmentation

Presentation This repository contains the code of our paper: Weakly-supervised c

Alteia 9 Jul 23, 2022
Data manipulation and transformation for audio signal processing, powered by PyTorch

torchaudio: an audio library for PyTorch The aim of torchaudio is to apply PyTorch to the audio domain. By supporting PyTorch, torchaudio follows the

1.9k Dec 28, 2022
MASA-SR: Matching Acceleration and Spatial Adaptation for Reference-Based Image Super-Resolution (CVPR2021)

MASA-SR Official PyTorch implementation of our CVPR2021 paper MASA-SR: Matching Acceleration and Spatial Adaptation for Reference-Based Image Super-Re

DV Lab 126 Dec 20, 2022
Project page of the paper 'Analyzing Perception-Distortion Tradeoff using Enhanced Perceptual Super-resolution Network' (ECCVW 2018)

EPSR (Enhanced Perceptual Super-resolution Network) paper This repo provides the test code, pretrained models, and results on benchmark datasets of ou

Subeesh Vasu 78 Nov 19, 2022
Repository for the paper "From global to local MDI variable importances for random forests and when they are Shapley values"

From global to local MDI variable importances for random forests and when they are Shapley values Antonio Sutera ( Antonio Sutera 3 Feb 23, 2022

Banglore House Prediction Using Flask Server (Python)

Banglore House Prediction Using Flask Server (Python) 🌐 Links 🌐 📂 Repo In this repository, I've implemented a Machine Learning-based Bangalore Hous

Dhyan Shah 1 Jan 24, 2022
Regularizing Nighttime Weirdness: Efficient Self-supervised Monocular Depth Estimation in the Dark (ICCV 2021)

Regularizing Nighttime Weirdness: Efficient Self-supervised Monocular Depth Estimation in the Dark (ICCV 2021) Kun Wang, Zhenyu Zhang, Zhiqiang Yan, X

kunwang 66 Nov 24, 2022
Python package for downloading ECMWF reanalysis data and converting it into a time series format.

ecmwf_models Readers and converters for data from the ECMWF reanalysis models. Written in Python. Works great in combination with pytesmo. Citation If

TU Wien - Department of Geodesy and Geoinformation 31 Dec 26, 2022
Catch-all collection of generative art made using processing

Generative art with Processing.py Some art I have created for fun. Dependencies Processing for Python, see how to download/use here Packages contained

2 Mar 12, 2022
The official repository for "Revealing unforeseen diagnostic image features with deep learning by detecting cardiovascular diseases from apical four-chamber ultrasounds"

Revealing unforeseen diagnostic image features with deep learning by detecting cardiovascular diseases from apical four-chamber ultrasounds The why Im

3 Mar 29, 2022
Exploring Classification Equilibrium in Long-Tailed Object Detection, ICCV2021

Exploring Classification Equilibrium in Long-Tailed Object Detection (LOCE, ICCV 2021) Paper Introduction The conventional detectors tend to make imba

52 Nov 21, 2022
Official code repository for the publication "Latent Equilibrium: A unified learning theory for arbitrarily fast computation with arbitrarily slow neurons"

Latent Equilibrium: A unified learning theory for arbitrarily fast computation with arbitrarily slow neurons This repository contains the code to repr

Computational Neuroscience, University of Bern 3 Aug 04, 2022
Jupyter notebooks for using & learning Keras

deep-learning-with-keras-notebooks 這個github的repository主要是個人在學習Keras的一些記錄及練習。希望在學習過程中發現到一些好的資訊與範例也可以對想要學習使用 Keras來解決問題的同好,或是對深度學習有興趣的在學學生可以有一些方便理解與上手範例

ErhWen Kuo 2.1k Dec 27, 2022