For our last data analysis-inspired problem, let's go back to one of my favorite examples: Pokemon. Pokemon is a popular video game franchise by Nintendo which features over 800 monsters, called Pokemon, each with unique names, types, and statistics. The dataset you'll have for this problem contains every Pokemon through Generation 7, including their alternate forms. You don't need to understand Pokemon to solve this problem, though: games are just good candidates for this kind of analysis because they often have well-formed, complete datasets. To solve these problems, you just need to know a couple things. First, each row of the dataset corresponds to a Pokemon. Each row has 13 columns, in this order: Number: The numbered ID of the Pokemon, an integer
Name: The name of the Pokemon, a string
Type1: The Pokemon's primary type, a string
Type2: The Pokemon's secondary type, a string (this may be blank; you may assume Type1 and Type2 will never be the same)
HP: The Pokemon's HP statistic, an integer in the range 1 to 255
Attack: The Pokemon's Attack statistic, an integer in the range 1 to 255
Defense: The Pokemon's Defense statistic, an integer in the range 1 to 255
SpecialAtk: The Pokemon's Special Attack statistic, an integer in the range 1 to 255
SpecialDef: The Pokemon's Special Defense statistic, an integer in the range 1 to 255
Speed: The Pokemon's Speed statistic, an integer in the range 1 to 255
Generation: What generation the Pokemon debuted in, an integer in the range 1 to 7
Legendary: Whether the Pokemon is considered "legendary" or not, either TRUE or FALSE (for you hardcore fans, we've grouped Legendary and Mythical Pokemon together for simplicity)
Mega: Whether the Pokemon is "Mega" or not, either TRUE or FALSE

Required:
Create a Pokemon object with the 13 attributes above.