First steps with Python in Life Sciences

Overview

First steps with Python in Life Sciences

This course material is part of the "First Steps with Python in Life Science" three-day course of SIB-training and is addressed to beginners wanting to become familiar with the Python syntax, environment, and the most common commands.

This course material provides an introduction to python and jupyter notebooks (a web based notebook system for creating and sharing computational documents) in an interactive manner.

prerequisite installation

You can find tips and instructions to ensure you have installed all the required software before starting the course.

course material organization

The course revolves around a sery of jupyter notebooks which take you on your first steps in you python journey.

Each jupyter notebook interleaves theory and examples of codes. We heartily recommend you execute and play around with these bits of code as you follow along : in programming, perhaps even more than anywhere else, practice makes perfect.

Additionally, each notebook is associated with a number of exercises (often in a separate notebook) of varying difficulty, with associated corrections.

If you are attending this course with a teacher (or if you are just curious), you can take a look at our schedule. In short, lessons 00 to 04 deals with generalistic aspect of the python language, while notebooks 05 or 08 present some of the most common modules used in data analysis and/or life sciences.

The notebooks/ folder contains each lesson:

Exercise notebooks:

The data used in the practicals can be found in the data notebooks/data folder, and solutions codes can be found in the notebooks/solutions/ folder (NB: micro-exercises do not have a correction).

You might also like...
Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs (CIKM 2020)
Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs (CIKM 2020)

Karate Club is an unsupervised machine learning extension library for NetworkX. Please look at the Documentation, relevant Paper, Promo Video, and Ext

Probabilistic Programming in Python: Bayesian Modeling and Probabilistic Machine Learning with Theano
Probabilistic Programming in Python: Bayesian Modeling and Probabilistic Machine Learning with Theano

PyMC3 is a Python package for Bayesian statistical modeling and Probabilistic Machine Learning focusing on advanced Markov chain Monte Carlo (MCMC) an

Statsmodels: statistical modeling and econometrics in Python

About statsmodels statsmodels is a Python package that provides a complement to scipy for statistical computations including descriptive statistics an

A computer algebra system written in pure Python

SymPy See the AUTHORS file for the list of authors. And many more people helped on the SymPy mailing list, reported bugs, helped organize SymPy's part

ForecastGA is a Python tool to forecast Google Analytics data using several popular time series models.
ForecastGA is a Python tool to forecast Google Analytics data using several popular time series models.

ForecastGA is a tool that combines a couple of popular libraries, Atspy and googleanalytics, with a few enhancements.

Multiple Pairwise Comparisons (Post Hoc) Tests in Python
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

Hidden Markov Models in Python, with scikit-learn like API

hmmlearn hmmlearn is a set of algorithms for unsupervised learning and inference of Hidden Markov Models. For supervised learning learning of HMMs and

Deep universal probabilistic programming with Python and PyTorch
Deep universal probabilistic programming with Python and PyTorch

Getting Started | Documentation | Community | Contributing Pyro is a flexible, scalable deep probabilistic programming library built on PyTorch. Notab

Fast, flexible and easy to use probabilistic modelling in Python.
Fast, flexible and easy to use probabilistic modelling in Python.

Please consider citing the JMLR-MLOSS Manuscript if you've used pomegranate in your academic work! pomegranate is a package for building probabilistic

Comments
  • Module 2-create your own functions - text columns

    Module 2-create your own functions - text columns

    Your tutorials are fantastic! minor format issues: the multiple column format in some pages (ex: module 2 in python training) collapse the text and making it unreadable. Hope to see it fixed to complete the tutorial! thank you.

    opened by catalicu 1
Releases(October2022)
Owner
SIB Swiss Institute of Bioinformatics
SIB Swiss Institute of Bioinformatics
Created covid data pipeline using PySpark and MySQL that collected data stream from API and do some processing and store it into MYSQL database.

Created covid data pipeline using PySpark and MySQL that collected data stream from API and do some processing and store it into MYSQL database.

2 Nov 20, 2021
Python Implementation of Scalable In-Memory Updatable Bitmap Indexing

PyUpBit CS490 Large Scale Data Analytics — Implementation of Updatable Compressed Bitmap Indexing Paper Table of Contents About The Project Usage Cont

Hyeong Kyun (Daniel) Park 1 Jun 28, 2022
Generate lookml for views from dbt models

dbt2looker Use dbt2looker to generate Looker view files automatically from dbt models. Features Column descriptions synced to looker Dimension for eac

lightdash 126 Dec 28, 2022
PandaPy has the speed of NumPy and the usability of Pandas 10x to 50x faster (by @firmai)

PandaPy "I came across PandaPy last week and have already used it in my current project. It is a fascinating Python library with a lot of potential to

Derek Snow 527 Jan 02, 2023
PyStan, a Python interface to Stan, a platform for statistical modeling. Documentation: https://pystan.readthedocs.io

PyStan PyStan is a Python interface to Stan, a package for Bayesian inference. Stan® is a state-of-the-art platform for statistical modeling and high-

Stan 229 Dec 29, 2022
Pyspark Spotify ETL

This is my first Data Engineering project, it extracts data from the user's recently played tracks using Spotify's API, transforms data and then loads it into Postgresql using SQLAlchemy engine. Data

16 Jun 09, 2022
EOD Historical Data Python Library (Unofficial)

EOD Historical Data Python Library (Unofficial) https://eodhistoricaldata.com Installation python3 -m pip install eodhistoricaldata Note Demo API key

Michael Whittle 20 Dec 22, 2022
AptaMat is a simple script which aims to measure differences between DNA or RNA secondary structures.

AptaMAT Purpose AptaMat is a simple script which aims to measure differences between DNA or RNA secondary structures. The method is based on the compa

GEC UTC 3 Nov 03, 2022
X-news - Pipeline data use scrapy, kafka, spark streaming, spark ML and elasticsearch, Kibana

X-news - Pipeline data use scrapy, kafka, spark streaming, spark ML and elasticsearch, Kibana

Nguyễn Quang Huy 5 Sep 28, 2022
Generates a simple report about the current Covid-19 cases and deaths in Malaysia

Generates a simple report about the current Covid-19 cases and deaths in Malaysia. Results are delay one day, data provided by the Ministry of Health Malaysia Covid-19 public data.

Yap Khai Chuen 7 Dec 15, 2022
Transform-Invariant Non-Negative Matrix Factorization

Transform-Invariant Non-Negative Matrix Factorization A comprehensive Python package for Non-Negative Matrix Factorization (NMF) with a focus on learn

EMD Group 6 Jul 01, 2022
Business Intelligence (BI) in Python, OLAP

Open Mining Business Intelligence (BI) Application Server written in Python Requirements Python 2.7 (Backend) Lua 5.2 or LuaJIT 5.1 (OML backend) Mong

Open Mining 1.2k Dec 27, 2022
Pizza Orders Data Pipeline Usecase Solved by SQL, Sqoop, HDFS, Hive, Airflow.

PizzaOrders_DataPipeline There is a Tony who is owning a New Pizza shop. He knew that pizza alone was not going to help him get seed funding to expand

Melwin Varghese P 4 Jun 05, 2022
Hydrogen (or other pure gas phase species) depressurization calculations

HydDown Hydrogen (or other pure gas phase species) depressurization calculations This code is published under an MIT license. Install as simple as: pi

Anders Andreasen 13 Nov 26, 2022
pyETT: Python library for Eleven VR Table Tennis data

pyETT: Python library for Eleven VR Table Tennis data Documentation Documentation for pyETT is located at https://pyett.readthedocs.io/. Installation

Tharsis Souza 5 Nov 19, 2022
Jupyter notebooks for the book "The Elements of Statistical Learning".

This repository contains Jupyter notebooks implementing the algorithms found in the book and summary of the textbook.

Madiyar 369 Dec 30, 2022
MidTerm Project for the Data Analysis FT Bootcamp, Adam Tycner and Florent ZAHOUI

MidTerm Project for the Data Analysis FT Bootcamp, Adam Tycner and Florent ZAHOUI Hallo

Florent Zahoui 1 Feb 07, 2022
Common bioinformatics database construction

biodb Common bioinformatics database construction 1.taxonomy (Substance classification database) Download the database wget -c https://ftp.ncbi.nlm.ni

sy520 2 Jan 04, 2022
Sample code for Harry's Airflow online trainng course

Sample code for Harry's Airflow online trainng course You can find the videos on youtube or bilibili. I am working on adding below things: the slide p

102 Dec 30, 2022
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