{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Assignment 3: Working with Relational Databases and SQL" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**1**. 75 points\n", "\n", "Convert the flat file data in `data/flat.csv` into a well-structured relational database in SQLite3 stored as `data/faculty.db`. Note - salary information is confidential and should be kept in a separate table from other personal data." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "\n", "\n", "\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**2**. 25 points\n", "\n", "We want to find potential mentors for Abram\tBoyer. Find all faculty members who know one or more of the same languages as Christopher Robbins whose salary is at least $50,000 higher than his using SQL statements. Assume that the only information you have is that you need to find mentors meeting the criteria for the faculty member named `Abram Boyer`. In other words, the ONLY hard coded terms in your SQL query are `Abram` and `Boyer` and the salary differential.\n", "\n", "You can use the `sql` magic extension or the `sqlite3` driver for this question." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "\n", "\n", "\n" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "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": "3.6.5" } }, "nbformat": 4, "nbformat_minor": 2 }