{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import pandas as pd\n", "import numpy as np\n", "import plotly.graph_objects as go\n", "import plotly.express as px\n", "import pycountry\n", "import seaborn as sns\n", "import matplotlib.pyplot as plt\n", "%matplotlib inline\n", "\n", "ufc_raw = pd.read_csv(\"data/data.csv\")\n", "ufc_final = pd.read_csv(\"data/UFC_processed.csv\")\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Choropleth Map: UFC Worldwide" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
| \n", " | country_code | \n", "matches | \n", "
|---|---|---|
| 0 | \n", "USA | \n", "3392 | \n", "
| 1 | \n", "BRA | \n", "405 | \n", "
| 2 | \n", "CAN | \n", "342 | \n", "
| 3 | \n", "GBR | \n", "255 | \n", "
| 4 | \n", "AUS | \n", "162 | \n", "