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    "# Data Engineering and Analytics\n",
    "Master Software Engineering\n",
    "\n",
    "Eva Zangerle\n",
    "\n",
    "## General Notes\n",
    "* Code is partly taken from further sources, such as books.\n",
    "* Sources are annotated (and acknowledged!) as follows:\n",
    "    * (CleaningData): Cleaning Data for Effective Data Science: Doing the other 80% of the work with Python, R, and command-line tools; David Mertz; Packt Publishing, 2021; [Github repo](https://github.com/PacktPublishing/Cleaning-Data-for-Effective-Data-Science/)\n",
    "    * (FeatureEng): Feature Engineering for Machine Learning; Alice Zheng and Amanda Casari; O'Reilly, 2018; [Github repo](https://github.com/alicezheng/feature-engineering-book)\n",
    "    * (DSHandbook): Python Data Science Handbook; Jake VanderPlas; O'Reilly, 2016; [Github repo](https://github.com/jakevdp/PythonDataScienceHandbook)\n",
    "    * (PracticalStatistics): Practical Statistics for Data Scientists: 50+ Essential Concepts Using R and Python; Peter Bruce, Andrew Bruce, and Peter Gedeck; O'Reilly, 2nd edition, 2020; [Github repo](https://github.com/gedeck/practical-statistics-for-data-scientists/)\n",
    "    \n",
    "* Unless marked otherwise, code was written by Eva Zangerle.\n",
    "* I deliberately mix different Python packages (e.g., for visualization matplotlib, pandas and seaborn) to showcase their use.\n",
    "\n",
    "\n",
    "\n",
    "## Virtual environments\n",
    "\n",
    "![xkcd python environment](https://imgs.xkcd.com/comics/python_environment.png)\n",
    "\n",
    "Comic taken from XKCD Comics https://xkcd.com/1987/ (CC-BY)\n",
    "\n",
    "\n",
    "\n",
    "Good tutorial on pipenv and jupyter(-lab): https://towardsdatascience.com/virtual-environments-for-data-science-running-python-and-jupyter-with-pipenv-c6cb6c44a405#\n",
    "\n",
    "\n",
    "## Useful python stuff\n",
    "* Startup files: https://ipython.readthedocs.io/en/stable/interactive/tutorial.html#startup-files\n",
    "* tqdm progress bars (also for Jupyter): https://github.com/tqdm/tqdm\n",
    "* nbval for validating Jupyter notebooks: https://github.com/computationalmodelling/nbval\n",
    "* nbqa for quality assurance for Jupyter notebooks: https://github.com/nbQA-dev/nbQA\n",
    "\n",
    "## Further tools\n",
    "* jq command line json processor: https://stedolan.github.io/jq/"
   ]
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