{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Nutridrive analysis" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Intro\n", "- Python is a very popular programming language\n", "- There are a lot of libraries (e.g., think of them as plugins for a language)\n", "- The main plugin you will use is called [Pandas](https://pandas.pydata.org/)\n", "- It was [invented by someone working in Capital Management](https://en.wikipedia.org/wiki/Pandas_(software)#History)\n", "- [Run through a super fast 10 min tutorial first](https://pandas.pydata.org/docs/user_guide/10min.html)\n", "- [Get some inspiration for Optimization problems here](https://www.youtube.com/watch?v=ufYtueq2DCw)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Let's get started \n", "\n", "- below are some \"cells\"\n", "- each cell is a \"piece of code\"\n", "- click a cell to go to it (better start with the first one below 👇, it imports things..)\n", "- hit SHIFT+ENTER to execute a cell " ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "# we import pandas <- this is a comment \n", "import pandas as pd # <- this is code \n", "import matplotlib.pyplot as plt\n", "\n", "%matplotlib inline" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "# load data into pandas dataframe \n", "df = pd.read_csv(\"data/data.csv\", delimiter=\";\")" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", " | ID | \n", "Meal | \n", "Restaurant | \n", "Type | \n", "Cal | \n", "P | \n", "C | \n", "F | \n", "Like Trigger | \n", "Reg | \n", "... | \n", "Unnamed: 17 | \n", "Unnamed: 18 | \n", "Unnamed: 19 | \n", "Unnamed: 20 | \n", "Unnamed: 21 | \n", "Unnamed: 22 | \n", "Unnamed: 23 | \n", "Unnamed: 24 | \n", "Unnamed: 25 | \n", "Unnamed: 26 | \n", "
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
0 | \n", "1.0 | \n", "Protein Box | \n", "Chilango | \n", "Lunch / Dinner | \n", "480 | \n", "50 | \n", "16 | \n", "20 | \n", "1.0 | \n", "1.0 | \n", "... | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "
1 | \n", "2.0 | \n", "Rice Hot Box + chicken | \n", "Chilango | \n", "Lunch / Dinner | \n", "495 | \n", "39,9 | \n", "61,1 | \n", "10,7 | \n", "1.0 | \n", "1.0 | \n", "... | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "
2 | \n", "3.0 | \n", "Chicken & Black Beans Burrito | \n", "Chilango | \n", "Lunch / Dinner | \n", "606 | \n", "41 | \n", "73 | \n", "38 | \n", "1.0 | \n", "1.0 | \n", "... | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "
3 | \n", "4.0 | \n", "Naked Burrito (grilled chicken & guac) | \n", "Chilango | \n", "Lunch / Dinner | \n", "475 | \n", "34 | \n", "35 | \n", "22 | \n", "1.0 | \n", "1.0 | \n", "... | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "
4 | \n", "5.0 | \n", "Super Eggs + Smoked Salmon | \n", "Pure | \n", "Breakfast | \n", "279 | \n", "24,4 | \n", "1,8 | \n", "19,2 | \n", "1.0 | \n", "1.0 | \n", "... | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "
5 rows × 27 columns
\n", "