Working on MAT-204 - Good Progress
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,slimbook,wins-slimbook,23.11.2024 10:25,file:///home/slimbook/.var/app/org.libreoffice.LibreOffice/config/libreoffice/4;
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,winsdominoes,fedora,23.11.2024 20:14,file:///home/winsdominoes/.var/app/org.libreoffice.LibreOffice/config/libreoffice/4;
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,slimbook,wins-slimbook,23.11.2024 10:26,file:///home/slimbook/.var/app/org.libreoffice.LibreOffice/config/libreoffice/4;
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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# MAT-204:00010 - Probability\n",
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"Author: Thanawin Pattanaphol - Date: 23th December 2024 - Description: Basic probability calculations"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Importing Libraries"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 50,
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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@ -12,12 +27,26 @@
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"\n",
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"Dat = pd.read_csv('DataLoL.csv')\n",
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"\n",
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"nGame = len(Dat)"
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"num_games = len(Dat)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Questions"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### Probability: Blue Team wins"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 51,
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"execution_count": null,
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"metadata": {},
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"outputs": [
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{
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@ -29,13 +58,23 @@
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}
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],
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"source": [
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"ProbBlueWins = len(Dat[Dat['blueWins'] == 1]) / nGame\n",
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"print(\"Probability that Blue Team wins is: \", ProbBlueWins)"
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"# Calculating the probability by diving the amount of games that blue won\n",
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"# dividing it by the amount of total games\n",
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"# Thus: p = Number of time an event occurs / Total nmumber of possible events\n",
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"prob_blue_wins = len(Dat[Dat['blueWins'] == 1]) / num_games\n",
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"print(\"Probability that Blue Team wins:\", prob_blue_wins)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### Probability: Blue Team wins and kills the dragon"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 52,
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"execution_count": null,
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"metadata": {},
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"outputs": [
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{
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@ -47,13 +86,24 @@
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}
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],
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"source": [
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"ProbBlueWinsAndDragon = len(Dat[(Dat['blueWins'] == 1) & (Dat['blueDragons'] == 1)]) / nGame\n",
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"print(\"Probability that Blue Team wins and kills the dragon is: \", ProbBlueWinsAndDragon)"
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"# Doing a similar calculation with the difference being\n",
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"# the number of time an event occurs now only counts\n",
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"# the number of times blue team wins and kills the dragon\n",
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"\n",
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"prob_blue_wins_dragons = len(Dat[(Dat['blueWins'] == 1) & (Dat['blueDragons'] == 1)]) / num_games\n",
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"print(\"Probability that Blue Team wins and kills the dragon:\", prob_blue_wins_dragons)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### Probability: Blue Team wins and kills the herald"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 53,
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"execution_count": null,
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"metadata": {},
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"outputs": [
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{
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@ -65,13 +115,23 @@
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}
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],
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"source": [
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"ProbBlueWinsAndHerald = len(Dat[(Dat['blueWins'] == 1) & (Dat['blueHeralds'] == 1)]) / nGame\n",
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"print(\"Probability that Blue Team wins and kills the herald is: \", ProbBlueWinsAndHerald)"
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"# Similar calculation but with the number of events that\n",
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"# team blue wins and kills the herald\n",
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"\n",
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"prob_blue_wins_heralds = len(Dat[(Dat['blueWins'] == 1) & (Dat['blueHeralds'] == 1)]) / num_games\n",
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"print(\"Probability that Blue Team wins and kills the herald:\", prob_blue_wins_heralds)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### Count: All possible cases (Venn Diagram)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 54,
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"execution_count": null,
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"metadata": {},
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"outputs": [
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{
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@ -86,16 +146,19 @@
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}
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],
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"source": [
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"game_blue_wins = set()\n",
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"game_blue_dragon = set()\n",
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"game_blue_herald = set()\n",
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"# Declaring variable for each set\n",
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"# Loop through the whole games dataset and if the item-\n",
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"# -matches the condition, add it to the set for that\n",
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"# condition list\n",
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"\n",
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"for game in range(nGame):\n",
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"game_blue_wins, game_blue_dragon, game_blue_herald = set()\n",
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"\n",
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"for game in range(num_games):\n",
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" if(Dat['blueWins'][game] == 1):\n",
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" game_blue_wins.add(game)\n",
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" if(Dat['blueDragons'][game] == 1):\n",
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" else if(Dat['blueDragons'][game] == 1):\n",
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" game_blue_dragon.add(game)\n",
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" if(Dat['blueHeralds'][game] == 1):\n",
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" else if(Dat['blueHeralds'][game] == 1):\n",
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" game_blue_herald.add(game)\n",
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"\n",
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"venn3([game_blue_wins, game_blue_dragon, game_blue_herald], ('A', 'B', 'C'))\n",
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@ -103,9 +166,16 @@
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"plt.show()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### Probability: Each possible events (Venn Diagram)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 55,
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"execution_count": null,
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"metadata": {},
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"outputs": [
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{
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@ -120,6 +190,11 @@
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}
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],
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"source": [
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"# Setting the variable for each section of the venn diagram\n",
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"# Use these values to calculate its probability by\n",
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"# diving with the total amount of games\n",
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"# Produce venn diagram of the values\n",
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"\n",
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"count_a = 2055\n",
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"count_b = 1096\n",
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"count_c = 564\n",
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@ -130,22 +205,29 @@
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"\n",
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"count_abc = 522\n",
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"\n",
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"p_a = round(2055 / nGame, 3)\n",
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"p_b = round(1096 / nGame, 3)\n",
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"p_c = round(564 / nGame, 3)\n",
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"p_a = round(2055 / num_games, 3)\n",
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"p_b = round(1096 / num_games, 3)\n",
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"p_c = round(564 / num_games, 3)\n",
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"\n",
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"p_ab = round(1770 / nGame, 3)\n",
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"p_ac = round(583 / nGame, 3)\n",
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"p_bc = round(188 / nGame, 3)\n",
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"p_ab = round(1770 / num_games, 3)\n",
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"p_ac = round(583 / num_games, 3)\n",
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"p_bc = round(188 / num_games, 3)\n",
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"\n",
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"p_abc = round(522 / nGame, 3)\n",
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"p_abc = round(522 / num_games, 3)\n",
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"\n",
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"venn = venn3(subsets=(p_a, p_b, p_ab, p_c, p_ac, p_bc, p_abc), set_labels=('A', 'B', 'C'))"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### Probability: Blue Team does not manage to do any of the events (Outer White Section)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 56,
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"execution_count": null,
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"metadata": {},
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"outputs": [
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{
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@ -157,12 +239,25 @@
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}
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],
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"source": [
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"print(\"Probabilty that Blue Team loses, doesn't kill dragons and heralds: \", (nGame - (count_a + count_b + count_c + count_ab + count_abc + count_ac + count_bc)) / nGame)"
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"# Calculate the total amount of the games in the venn diagram\n",
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"# Find the complement of (A ∪ B ∪ C)\n",
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"\n",
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"count_all = count_a + count_b + count_c + count_ab + count_abc + count_ac + count_bc\n",
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"did_not_win_all = num_games - p_all_wins\n",
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"\n",
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"print(\"Probabilty that Blue Team loses, doesn't kill dragons and heralds:\", did_not_win_all / num_games)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### Probability: Blue Team wins and kills dragon and herald"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 57,
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"execution_count": null,
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"metadata": {},
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"outputs": [
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{
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@ -174,12 +269,22 @@
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}
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],
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"source": [
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"print(\"Probability that blue team wins, kills dragon and herald: \", p_abc)"
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"# The probability of this event is essentially the intersection of\n",
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"# A (Blue Team Wins), B (Kills Dragon) and C (Kills Herald)\n",
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"\n",
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"print(\"Probability that blue team wins, kills dragon and herald:\", p_abc)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### Probability: Blue Team does not win but kills dragon and the herald "
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]
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},
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{
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"cell_type": "code",
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"execution_count": 58,
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"execution_count": null,
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"metadata": {},
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"outputs": [
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{
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@ -191,12 +296,22 @@
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}
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],
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"source": [
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"print(\"Probability that blue team kills dragon and the herald but does not win: \", p_bc)"
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"# Same with above but only with the intersection between\n",
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"# B (Kills Dragon) and C (Kills Herald)\n",
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"\n",
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"print(\"Probability that blue team does not win but kills dragon and the herald :\", p_bc)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### Probability: Blue Team wins but does not kill dragon and herald. "
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]
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},
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{
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"cell_type": "code",
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"execution_count": 59,
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"execution_count": null,
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"metadata": {},
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"outputs": [
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{
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@ -208,7 +323,9 @@
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}
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],
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"source": [
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"print(\"Probability that blue team wins without killing the graon and the herald: \", p_a)"
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"# Same with above but only with the A section (Blue Team wins)\n",
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"\n",
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"print(\"Probability that blue team wins without killing the dragon and the herald:\", p_a)"
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]
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}
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],
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@ -228,7 +345,7 @@
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.12.6"
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"version": "3.11.2"
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}
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},
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"nbformat": 4,
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