IDRE

Institute for Digital Research and Education

Institute for Digital Research and Education

Python

Common Data formats: How to Access Them Programmatically

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Storing data in an open-standard format ensures the data’s long-term readability and reusability, which is an important component of achieving reproducible computing. In this class we will explore a number of common data formats, learn about their structures and show how to access them programmatically. The data formats considered include: CSV (several variants), JSON, XML, Excel and HDF5. The Python and Julia languages will be used in the programming examples.

Using SQL with Python for Data Analysis

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SQL is a standard language designed to query and extract data from tables stored in a database. Python, on the other hand, has well-known libraries specially designed for data analysis and manipulation. This course will introduce attendees to the basics of how to integrate SQL and relational database management systems with Python for data analysis….
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Learning Scikit-Learn: the basics

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As machine learning gains more and more popularity in science and technology in recent years, scikit-learn becomes one of the must-have libraries in the general machine learning toolbox. In this lecture we will present an introduction about the basics of scikit-learn python library. Prerequisite knowledge for the workshop includes Python programming and basic machine learning concepts.

High-Performance Data Science in Python (1) Interpreter War

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This workshop series will present an extensive discussion on how to improve the performance of Python in data science by looking under the hood of its language/libraries and using the technologies to make Python a practical solution for the high-performance big data analytics. In the first session, we will focus on how to boost the speed of python code in an interperter level by explaining the concepts (e.g. GIL, GIT) and introducing the packages of pypy, numba, pythran, cython etc. Although no specific prerequisite is required to attend the talk, having programming experience in Python will be helpful to fully understand the lecture content.

Data Visualization with Python II: Making Interactive Plots and Widgets

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Python is a very popular language for computational and data science, and it has many powerful capabilities for visualizing data.  Data visualization plays an essential role in representing data so that its underlying patterns might be conveyed and understood.  The second part of this series will explore various ways that Python can be used to…
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Introduction to Spatial Statistics with Python

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Registration link: https://ucla.zoom.us/meeting/register/tJwkdu6hqj4sG9ZioB0tM8VuXxA44AWGc6W- Visual interpretations are meaningful ways to determine spatial trends in our data. However, underlying factors—such as inconsistent geographies, scale, data gaps, overlapping data—have the potential to produce incorrect assumptions, as valuable information may be conveniently hidden from the visual output. One way to address this issue is to amend your visual output…
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Learning Scikit-Learn

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As machine learning gains more and more popularity in science and technology in recent years, scikit-learn becomes one of the must-have libraries in the general machine learning toolbox. In this lecture we will present an in-depth introduction to scikit-learn python library. Prerequisite knowledge for the workshop includes Python programming and basic machine learning concepts.

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