{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Problem 1\n", "Import NumPy under the alias `np`." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Problem 2\n", "Import pandas under the alias `pd`." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Problem 3\n", "We will again be using salesperson data to test your knowledge of the `groupby` method. Given the dataset `data`, print a new DataFrame that shows the mean sales per salesperson, grouped by `Organization`." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "data = pd.DataFrame([ ['Coca-Cola', 'Nick', 200],\n", "\n", " ['Coca-Cola', 'Joel', 120],\n", "\n", " ['Pepsi','Taylor', 125],\n", "\n", " ['Pepsi','Josiah', 250],\n", "\n", " ['Dr. Pepper','Josh', 150],\n", "\n", " ['Dr. Pepper','Micaiah', 500]], \n", " columns = ['Organization', 'Salesperson Name', 'Sales'])\n", "\n", "data" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "#Solution goes here" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Problem 4\n", "Given the dataset `data`, print a new DataFrame that shows the total sales for each `Organization`." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Problem 5\n", "Given the dataset `data`, print a new DataFrame that applies the `describe` method to each organization." ] }, { "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": "3.7.6" } }, "nbformat": 4, "nbformat_minor": 4 }