![]() ![]() Names = # list containg all the pokemon names Gen4_dex = gen4_dex.rename(columns= ) # creating list # changing Types 1 to Type to insure no error Note: S is M -> Image By Author Creating Binary Matrix A ijĪccording to the equation, we must store all the variable values achieved by iterating through all the required columns. Import pandas as pd team_df = pd.read_csv("Datasets/pokemon.csv") We start by loading the CSV file using pandas and printing a few results: import numpy as np It will be great to download both datasets(pokemon.csv & Pokemon Type Chart.csv), save them in a separate folder(datasets), and follow along. Type_chart: For type matchups and effects. Pokemon dataset from Kaggle: For pokemon names and stats. Datasetįor the Problem in hand, we will be using two datasets: Once entered, they are required to defeat four powerful trainers and the champion(uses a variety of different pokemon types)įinally, this clarifies our goal: Can we create a helpful team in fighting these 12 trainers and probably the last one?. Having chosen, they embark on a journey to defeat eight gym leaders, specializing in a specific type, to enter a Pokemon league tournament.ģ. One starts as a lead character who can choose their first pokemon called stater pokemon out of 3.Ģ. The game mechanics also allow for powerful pokemon(legendaries) caught at the end of the game and give upper advantages to the yielder.ġ. Evolution allows an increase in overall strengths, changes in forms, and even provides additional typings.ģ. They can also undergo a genetic transformation two times called evolution. Each one has its primary Type and weakness or advantage over the others. ![]() Pokemon are animal-like creatures that are obtainable by battling them. This section is optional and contains a summary of game mechanics in a few points:ġ. Here is a quick summary of the gameplay, which will be helpful later on. This article is a walkthrough to perform just that using PuLp, the linear programming and optimization library. What if I say one can do this by having some knowledge of python, data science, and python. I am sure you must have played pokemon games at some point in time and must have hated the issue of creating an optimal and balanced team to gain an advantage. This light and simple tool help create a strong team that works through the weaknesses of the opposite team and helps you win the tournament as a pokemon leader.This article was published as a part of the Data Science Blogathon Introduction You can create a strong team to fight against your opponent in the game by using the tool named Pokemon Team Builder. Whether it is Pikachu, Charizard, Bulbasaur, or Jiggly Puff, each of these pokemon comes with its own set of strengths and weaknesses. If you carry along the nostalgia of watching Pokemon cartoon series during your childhood, you must have heard of the Pokemon game. ![]()
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