IntegerMan

string text = File.ReadAllText("MyFile.txt");

// Do something with text

IntegerMan

LastItemTracker<string> stringTracker = new();

stringTracker.TrackItem("Hello");
stringTracker.TrackItem("World");

Console.WriteLine(stringTracker.LastItem); // Prints out "World"

bool isLastItem = stringTracker.IsLastItem("Hello"); // false

IntegerMan

public class LastItemTracker<T>
{
   public T LastItem {get; private set;}
   public void TrackItem(T item)
   {
      LastItem = item;
   }
   public bool IsLastItem(T item)
   {
      return LastItem == item;

IntegerMan

public string CombineTypes<T1, T2>(T1 firstType, T2 secondType)
{
   // Implementation omitted...
} 

IntegerMan

List<int> numbers = new() { 1, 2, 3};
int[] intResults = BuildFirstLastArray<int>(numbers);
List<string> names = new() { "Priya", "Mohammed", "Alexis" };
string[] strResults = BuildFirstLastArray<string>(names);

IntegerMan

public T[] BuildFirstLastArray<T>(List<T> input)
{
   T[] result = new T[2]();
   // For ease of readability, let's just use LINQ here
   result[0] = input.First();
   result[1] = input.Last();
   return result;
}

IntegerMan

public string[] BuildFirstLastArray(List<string> input)
{
   string[] result = new string[2]();
   // For ease of readability, let's just use LINQ here
   result[0] = input.First();
   result[1] = input.Last();
   return result;
}

IntegerMan

public int[] BuildFirstLastArray(List<int> input)
{
   int[] result = new int[2]();
   // For ease of readability, let's just use LINQ here
   result[0] = input.First();
   result[1] = input.Last();
   return result;
}

IntegerMan

import pandas as pd

# CSV file is not relevant, just assuming you have some pre-existing data
df = pd.read_csv('models.csv')

# Define columns to add with an array of values for the new row(s)    
data = {
    "Model":["Linear Regression"], 
    "R2":   [0.042], 
    "MSE":  [3.14],  

IntegerMan

df = pd.concat([df_new_rows, df])