{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Assignment 1 Review" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**1**. There is an SQLite3 database `flowers.db` in the `data` sub-directory. Read this into a `pandas` DataFrame, and show lines 5-10 of the DataFrame." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**2**. Summmarize the mean and coefficient of variation of each measuremnt by `species`." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**3**. Make a multi-plot figure containing boxplots where the x-axis is the Species and the y-axis is one of the four measurements." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**4**. Add 2 columns `pc1` and `pc2` to the Datafame, where `pc1` and `pc2` are the first two principal componennts of the 4 measurements. " ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**5**. Save the DataFrame to a CSV file, not including the index." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "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 }