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add first tutorial and remove build
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‎.gitignore

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dsc_tutorials/_builds/
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# Created by https://www.toptal.com/developers/gitignore/api/jupyternotebooks
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# Edit at https://www.toptal.com/developers/gitignore?templates=jupyternotebooks
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‎README.md

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[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/bckrlab/dsc-tutorials/HEAD)
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# DSC Tutorials
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> Machine Learning Tutorials for the Data Science Club.

‎dsc_tutorials/01_python-intro.ipynb

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"id": "e71f1f45-a62c-4e71-acdc-636706992f9e",
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"metadata": {},
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"source": [
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"Task: Change the text of this cell!"
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"> Change the text of this cell!"
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]
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},
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{
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"cell_type": "markdown",
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"id": "ce251bdc-3b8a-4c10-8e9d-87f2aeaae8d5",
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"metadata": {},
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"source": [
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"Task: Create a new cell that reads \"Hi!\", then delete this cell!"
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"> Create a new cell that reads \"Hi!\", then delete this cell!"
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]
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},
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{
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"cell_type": "markdown",
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"id": "139fcdec-3e99-47af-8a49-bbbb2c786e88",
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"metadata": {},
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"source": [
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"Task: Create a new Jupyter Notebook!"
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"> Create a new Jupyter Notebook!"
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]
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},
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{
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"id": "9210defe-4352-4790-89c6-db1a148c5449",
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"metadata": {},
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"source": [
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"# Python"
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"# Python\n",
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"\n",
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"> *\"Python is the \"most powerful language you can still read\".*\n",
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">\n",
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"> Paul Dubois "
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]
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{
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"cell_type": "markdown",
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"id": "a08d6422-e6c6-405f-ab6c-3a0483e63d1e",
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"metadata": {},
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"source": [
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"[Python](https://en.wikipedia.org/wiki/Python_(programming_language)) is a programming language that was developed in 1991 by Guido van Rossum.\n",
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"[Python](https://en.wikipedia.org/wiki/Python_(programming_language)) is a programming language that was developed in 1991 by \"Benevolent dictator for life\" Guido van Rossum.\n",
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"\n",
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"Python is:\n",
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"\n",
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"- **Interpreted**:\n",
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"- **Object-Oriented**: Most things in Python are Objects.\n",
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"- **Interpreted**: Programs are executed line by line by an interpreter instead of being compiled into machine code first.\n",
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"- **multi-paradigm**: programmers can choose their favorite way to conceptualize and structure programs\n",
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" - **Object-Oriented**: Programs are implemented via interacting objects. Most things in Python are objects, including functions.\n",
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" - **Procedural**: Programs are implemented via interacting functions.\n",
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" - **functional**: \n",
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"- **dynamically typed**: type-safety of operations is checked at runtime. This allows programmers to write very flexible code, but eventually, the program will fail during runtime due to operations on unsupperted types.\n",
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"\n",
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"- **Grabage Collected**: Dead variables are automatically identified and released. Programmers don't have to worry about memory management, but running the garbage collector takes time."
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"- **Grabage Collected**: Dead variables are automatically identified and released. Programmers don't have to worry about memory management, but running the garbage collector takes time.\n",
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"- etc."
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]
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},
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{
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" Namespaces are one honking great idea – let's do more of those!"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"id": "d0f745bf-8293-48fa-a33a-b3b8a36154a6",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Hello World!\n"
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]
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}
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],
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"source": [
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"print(\"Hello World!\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "8da08c56-274f-49da-862e-b6cb5499e0d1",
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"metadata": {},
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"outputs": [],
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"source": [
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"# TODO: Add Python tasks"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 20,
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"id": "ac17c77c-49d1-453b-ba25-05d039e04671",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"6"
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]
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},
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"execution_count": 20,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"# import packages\n",
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"import random\n",
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"\n",
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"def throw_dice():\n",
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" return random.randint(1,6)\n",
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"\n",
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"throw_dice()"
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]
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},
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"# Package Management in Python"
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]
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{
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"cell_type": "markdown",
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"id": "5b9422bf-84e3-4c60-bd22-90badd0521f1",
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"metadata": {},
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"source": [
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"While Python's standard library is already pretty powerful, there are many more great packages for data science.\n",
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"Existing Data Science projects will probably depend on some of them.\n",
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"Next, let's have a look how to install and manage packages in Python."
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]
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},
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"id": "6e7e6447-0dd9-4b72-8920-5acfc014931d",
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"metadata": {},
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"source": [
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"## Pip"
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"## pip\n",
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"\n",
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"pip is Python's package-management tool for installing new packages.\n",
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"Python packages are provided by an online repository called the **Python Package Index**, or short [PyPI](https://pypi.org/)."
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]
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},
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{
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"cell_type": "markdown",
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"id": "254e4992-81b6-4676-9cea-65429c0094da",
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"metadata": {},
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"source": [
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"```sh\n",
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"pip install {PACKAGE NAME}\n",
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"```"
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]
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},
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{
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"cell_type": "markdown",
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"id": "0d65e168-f265-46a7-8ece-ddb006a20207",
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"metadata": {},
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"source": [
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"Often projects come with a `requirements.txt` file that specifies their requirements. It can be installed with pip:\n",
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"\n",
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"```sh\n",
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"pip install -r requirements.txt\n",
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"```"
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]
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},
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{
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"cell_type": "markdown",
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"id": "4ba3d734-4570-4883-b69c-1db012431ffd",
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"metadata": {},
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"source": [
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"> install the package pyjokes and run the next cell"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 21,
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"id": "c539f499-e744-43b6-b6fc-eedc5c793f5b",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Collecting pyjokes\n",
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" Downloading pyjokes-0.8.3-py3-none-any.whl.metadata (3.4 kB)\n",
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"Downloading pyjokes-0.8.3-py3-none-any.whl (47 kB)\n",
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"Installing collected packages: pyjokes\n",
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"Successfully installed pyjokes-0.8.3\n"
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]
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}
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],
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"source": [
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"!pip install pyjokes"
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]
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},
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{
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"cell_type": "code",
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"id": "7aa1feaa-e9db-4085-984d-93038671b76f",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"\"There are 10 types of people: those who understand binary and those who don't.\""
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]
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},
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"execution_count": 22,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"import pyjokes\n",
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"\n",
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"pyjokes.get_joke()"
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]
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},
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{
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"cell_type": "markdown",
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"id": "8d8fd3e0-74e2-43b6-974c-e3f86dc6ccc0",
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"metadata": {},
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"source": [
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"## Virtual Environments"
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]
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},
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{
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"cell_type": "markdown",
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"id": "6f921af2-652f-45a9-855c-e146cb8e48da",
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"metadata": {},
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"source": [
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"pip is great! But things start to get messy as soon as you have multiple projects, each requiring their own dependencies.\n",
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"Fortunately, there is one solution: [Virtual Environments](https://docs.python.org/3/library/venv.html)!"
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]
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},
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{
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"cell_type": "markdown",
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"id": "a1082271-20c8-433b-8d7d-5aac760823d2",
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"metadata": {},
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"source": [
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"```sh\n",
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"# create a new virtual environment\n",
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"python -m venv myproject\n",
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"\n",
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"# don't forget to activate it!\n",
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"source myenv/bin/activate\n",
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"\n",
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"# install your packages\n",
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"pip install jupyter\n",
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"\n",
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"# try to start a new jupyter notebook\n",
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"jupyter notebook\n",
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"\n",
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"# deactivate the environment\n",
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"deactivate\n",
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"```"
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]
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},
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{
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"cell_type": "markdown",
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"id": "0b5e65d4-3995-4b8b-bc5c-f6fda9b3567e",
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"metadata": {},
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"source": [
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"## Conda"
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]
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},
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{
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"cell_type": "markdown",
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"id": "adf69db9-7594-4b10-ade4-e3d05b4257e9",
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"metadata": {},
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"source": [
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"- https://docs.conda.io\n",
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"- Miniconda: https://docs.anaconda.com/miniconda/"
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]
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},
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{
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"cell_type": "markdown",
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"id": "c069f3b6-fe16-4836-abab-16337903076c",
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"metadata": {},
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"source": [
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"```sh\n",
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"conda create -n myenv\n",
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"conda activate myenv\n",
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"conda install python=3.12 numpy jupyter\n",
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"```"
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]
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},
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{
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"cell_type": "markdown",
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"id": "720d22f6-ed29-4385-ae9f-b0afbbe15841",
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"metadata": {},
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"source": [
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"Quick Reference:\n",
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"\n",
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"```sh\n",
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"# create a new conda environment with a name\n",
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"conda create -n myenv\n",
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"# create a conda environment from a yml file\n",
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"conda env create -f environment.yml\n",
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"# list available conda environments\n",
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"conda env list\n",
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"# activate a conda environment\n",
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"conda activate myenv\n",
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"# install dependencies in active environment\n",
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"conda install numpy \n",
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"# export your environment to a yml file\n",
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"conda env export -f environment.yml\n",
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"conda env export > environment.yml\n",
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"# deactivate an environment\n",
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"conda deactivate\n",
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"# remove an environment\n",
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"conda remove --name myenv --all\n",
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"```"
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]
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},
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"cell_type": "markdown",
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"id": "91adae1a-892b-40f3-908f-0cf99801d981",
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"metadata": {},
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"source": [
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"## Pointers"
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]
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},
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"cell_type": "markdown",
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"id": "5ff781fc-3d42-4415-ae02-c97576161939",
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"metadata": {},
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"source": [
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"- https://ipython.readthedocs.io/en/stable/interactive/magics.html"
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"id": "9a2be204-a8d8-4b84-a454-1982b858076b",
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"metadata": {},
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"source": []

‎dsc_tutorials/_toc.yml

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format: jb-book
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root: intro
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chapters:
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- file: markdown
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- file: notebooks
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- file: markdown-notebooks
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- file: 01_python-intro
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- file: bookmarks

‎dsc_tutorials/bookmarks.md

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# Bookmarks
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> Good reads
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WIP

‎dsc_tutorials/intro.md

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# Welcome to your Jupyter Book
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# Welcome to the Data Science Club!
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This is a small sample book to give you a feel for how book content is
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structured.
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It shows off a few of the major file types, as well as some sample content.
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It does not go in-depth into any particular topic - check out [the Jupyter Book documentation](https://jupyterbook.org) for more information.
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> A common misconception: you actually CAN talk about Data Science Club.
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Data Science Tutorials
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Check out the content pages bundled with this sample book to see more.
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```{tableofcontents}
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```
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```

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