{ "cells": [ { "cell_type": "markdown", "id": "c1dd690d-65e3-4a54-9bff-66d8fa7042cb", "metadata": {}, "source": [ "# Practicum 1 Review - Key Concepts" ] }, { "cell_type": "markdown", "id": "02497de9-4171-4502-baa0-c78eb494f048", "metadata": {}, "source": [ "## Allowed" ] }, { "cell_type": "markdown", "id": "33542612-ab63-4cff-b88a-45d4e7f94ae9", "metadata": {}, "source": [ "- Your laptop\n", "- Any Jupyter notebooks available on your laptop\n", "- Resources available from the course syllabus\n", "- Libraries introduced by Data 8 (e.g. datascience, numpy, etc.)\n", "- The Regular Expression library (e.g. re)\n", "- A double-sided sheet of notes\n", "- The internet (to submit your solution to Canvas, to access library reference documentation)" ] }, { "cell_type": "markdown", "id": "a6d61e4f-de67-4ea3-b745-0a0c9e4f82c3", "metadata": {}, "source": [ "## Not Allowed" ] }, { "cell_type": "markdown", "id": "4717f27e-6db3-4da1-8be0-fb04e7c5e3c1", "metadata": {}, "source": [ "- All other uses of the internet (e.g. Generative AI, e-mail, stack overflow, asking Google how to do something, etc.)" ] }, { "cell_type": "markdown", "id": "2f8dd2ca-e426-4f16-8535-5eaa3b7b2b48", "metadata": {}, "source": [ "## Chapter 6 - Tables" ] }, { "cell_type": "markdown", "id": "12c5eeef-44ee-4450-8f70-980ff088a5aa", "metadata": {}, "source": [ "Table operators\n", "- column\n", "- drop\n", "- relabeled\n", "- read_table\n", "- select\n", "- set_format\n", "- show\n", "- sort\n", "- take\n", "- with_column\n", "- with_columns\n", "- where" ] }, { "cell_type": "markdown", "id": "251940e3-5b54-4a3d-a84d-d9304f1487cd", "metadata": {}, "source": [ "## Chapter 7 - Visualization" ] }, { "cell_type": "markdown", "id": "3982227e-e800-4454-a9a7-6c1fb57b51d6", "metadata": {}, "source": [ "Types of graphs (all can be **overlaid**):\n", "- barh (bar graph)\n", "- hist (histogram)\n", "- plot (line graph)\n", "- scatter (scatter graph)\n", "\n", "Useful supporting concepts\n", "- bin\n", "- group" ] }, { "cell_type": "markdown", "id": "977f93a9-ca5e-436f-b2e4-0fc751765604", "metadata": {}, "source": [ "## Chapter 8 - Functions and Tables" ] }, { "cell_type": "markdown", "id": "59a87457-a802-4baf-8fd4-3f347622ee07", "metadata": {}, "source": [ "- apply\n", "- join\n", "- pivot" ] }, { "cell_type": "markdown", "id": "7c1ee0bf-3cbb-4e54-a620-f5c0df3a9e9e", "metadata": {}, "source": [ "## Regular Expressions" ] }, { "cell_type": "markdown", "id": "c7c7fa61-401a-4094-9c32-4d6fde46f908", "metadata": {}, "source": [ "- Be able to apply re.fullmatch to validate the format of entries in a table\n", "- Be able to apply re.sub to clean entries in a table" ] }, { "cell_type": "markdown", "id": "d2b4022d-eed0-46b0-9ad8-07fef395c0b6", "metadata": {}, "source": [ "## A Few Practice Problems" ] }, { "cell_type": "markdown", "id": "073f076a-1eff-4c07-957c-056a0731c487", "metadata": {}, "source": [ "To check your general understanding of the material, work this [Practice Practicum](https://www.cs.montana.edu/paxton/classes/fall-2025/intro-ds/notebooks/reviews/practice/practice-1/). Note that these problems do not comprehensively cover the topics above!" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.13.7" } }, "nbformat": 4, "nbformat_minor": 5 }