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Jan 17, 2024 · In this tutorial, you'll learn the importance of having a structured data analysis workflow, and you'll get the opportunity to practice using Python for data analysis while following a common workflow process.
- Overview
- Prerequisites
- License
- Help and further information
Welcome to the official GitHub repository for the Data analysis and visualisation in Python (2021) series by Carberra Tutorials!
This repository is designed purely as a supplementary aid to the series, and should NOT be downloaded without having watched it first.
Things you'll need
•Python 3.7.1 or greater •A Jupyter-compatible development environment •Visual Studio Code •The Jupyter online IDE •Some data to analyse! If you're stuck for ideas, you can use these datasets.
Dependency table
*This is only needed if you are using IPython notebooks. These are used in the series. **This library was used to get the data being analysed, and does not feature in the series.
Installing required libraries
To install the necessary libraries, run one of the the following commands:
This repository is made available via the BSD 3-Clause License.
If you need help using this repository, watch the series. If you still need help beyond that, join the Carberra Tutorials Discord server.
Apr 8, 2024 · In this step-by-step guide, we’ll show you a Python data analysis example and demonstrate how to analyze a dataset. A great way to get practical experience in Python and accelerate your learning is by doing data analysis challenges.
Mar 6, 2023 · This cheatsheet to get started with Python for data analysis. There’s a lot more to learn, but I hope these cheat helps you to understand and play with data! NumPy is a popular Python library...
- Ram Giri
Jan 24, 2024 · Dive into the world of data analysis with our comprehensive guide on Python’s Pandas library. Designed for both beginners and seasoned data scientists, this blog post demystifies the...
Jul 6, 2024 · When we talk about using Python for data analysis, we're referring to the process of leveraging Python's capabilities to examine, clean, transform, and model data in order to extract valuable insights, make decisions, and communicate findings. In this tutorial, we will indulge into all steps for Data Analysis with Python. Table of Content.
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Data Analysis With Python - Summer 2021. An MOOC offered by the University of Helsinki. The course is based on Jake VanderPlas' renowned book, Python Data Science Handbook: Essential Tools for Working with Data. https://jakevdp.github.io/PythonDataScienceHandbook/ Topics covered: Programming in Python. Numpy. Pandas. Matplotlib.
