Data Visualization With Python - Portal
Data Visualization with PythonGenerate beautiful plots with pandas andmatplotlib.Dr. Michael Horn, Fachreferat Naturwissenschaften, UB BernCoffee & Bit(e)s Fall 2020
This LectureContent why data visualization? why data visualization with python and python tools? what are these tools? presentation of a jupyter notebook conclusion2
Why Data Visualization (DV) ?Understand data and communicate informationUnderstanding of dataCommunication of information DV makes data perceptible by humans. DV highlights the essence of a survey(by putting all information in a nutshell). DV highlights patterns in data(correlations, outliers, etc.). DV is esthetical. DV promotes scientific ideation. DV is fundamental for storytelling.Data visualization is essential in a scientific context.3
Why DV with Python and Python Tools ?Extraordinary open source tools free of cost, non-proprietary very flexible and versatileoocan be integrated in various workflowshave a good interoperability (among each other and with other types of software) well-established and reliableoo4have a large user community, are maintained and refined by a large community ofindependent developershave a good documentation, are transparent
What are these Tools ?Python, jupyter, pandas, matplotlib python:ooo pandas:programming (scripting) languageeasy to learnvery powerful, flexible and versatile jupyter notebook:oo5browser based applicationintegrates code (e.g. python), code output(e.g. plots) and documentationooopython library for data processingfast, powerful, flexible, easy to useintegrates matplotlib matplotlib:ooopython library for data visualizationenables DV in matlab styleis platform independent and very robust
Data VisualizationPresentation of a jupyter notebookJupyter notebook on r/data visualization/Data Visualization with Python CL HS2020.ipynb6
ConclusionTake home message data visualization is fundamental for understanding data and communicatinginformation. python, jupyter, pandas and matplotlib are extraordinary open source tools thatcan be used for data visualization. the University Library constructs a digital toolbox which offers exemplary use ofsuch tools.7
Further ReadingUseful literature and documentationUseful literature:Useful links: VanderPlas J.:Python data science handbook.O’Reilly Media, 2016. python: https://www.python.org/ Yim A., Chung C., Yu A.:Matplotlib for Python Developers.Packt Publishing, 2018. pandas: https://pandas.pydata.org8 jupyter: https://jupyter.org/ matplotlib: https://matplotlib.org
Thank youfor your attentionDr. Michael Horn, Fachreferat Naturwissenschaften, UB BernCoffee & Bit(e)s Fall 2020www.unibe.ch/ub/sciencelibrary see «Coffee & Bit(e)s» for lecture notes
o integrates code (e.g. python), code output (e.g. plots) and documentation pandas: o python library for data processing o fast, powerful, flexible, easy to use o integrates matplotlib matplotlib: o python library for data visualization o enables DV in matlab style o is platform independent and very robust
Python Programming for the Absolute Beginner Second Edition. CONTENTS CHAPTER 1 GETTING STARTED: THE GAME OVER PROGRAM 1 Examining the Game Over Program 2 Introducing Python 3 Python Is Easy to Use 3 Python Is Powerful 3 Python Is Object Oriented 4 Python Is a "Glue" Language 4 Python Runs Everywhere 4 Python Has a Strong Community 4 Python Is Free and Open Source 5 Setting Up Python on .
Python 2 versus Python 3 - the great debate Installing Python Setting up the Python interpreter About virtualenv Your first virtual environment Your friend, the console How you can run a Python program Running Python scripts Running the Python interactive shell Running Python as a service Running Python as a GUI application How is Python code .
Python is readable 5 Python is complete—"batteries included" 6 Python is cross-platform 6 Python is free 6 1.3 What Python doesn't do as well 7 Python is not the fastest language 7 Python doesn't have the most libraries 8 Python doesn't check variable types at compile time 8 1.4 Why learn Python 3? 8 1.5 Summary 9
site "Python 2.x is legacy, Python 3.x is the present and future of the language". In addition, "Python 3 eliminates many quirks that can unnecessarily trip up beginning programmers". However, note that Python 2 is currently still rather widely used. Python 2 and 3 are about 90% similar. Hence if you learn Python 3, you will likely
There are currently two versions of Python in use; Python 2 and Python 3. Python 3 is not backward compatible with Python 2. A lot of the imported modules were only available in Python 2 for quite some time, leading to a slow adoption of Python 3. However, this not really an issue anymore. Support for Python 2 will end in 2020.
The Monty Python : œuvres (62 ressources dans data.bnf.fr) Œuvres audiovisuelles (y compris radio) (20) Monty Python live (mostly) (2014) Monty Python live (mostly) (2014) Monty Python live (mostly) (2014) "Monty Python, almost the truth" (2014) de Alan Parker et autre(s) avec The Monty Python comme Acteur "Monty Python, almost the truth" (2014)
Introduction to basic Python Contents 1. Installing Python 2. How to run Python code 3. How to write Python code 4. How to troubleshoot Python code 5. Where to go to learn more Python is an astronomer's secret weapon. With Python, the process of visualizing, processing, and interacting with data is made extremely simple.
A Python Book A Python Book: Beginning Python, Advanced Python, and Python Exercises Author: Dave Kuhlman Contact: dkuhlman@davekuhlman.org
