kinetic_energy.py

import numpy as np
class Trial(object):
    def __init__(self, mass, data, height):
        self.mass = mass
        self.data = data

        self.energy = self.mass * 9.8 * height
        self.average = np.average(self.data)
        self.std = np.std(self.data)
        self.error = self.std / np.sqrt(len(self.data))

    def __repr__(self):
        string = f"---- MASS = {self.mass * 1000: .3f}g ----\n"
        for entry in self.data:
            string += f"Data Point = {entry: .3f}m or {entry * 100: .1f}cm\n"

        string += f"Average = {self.average: .3f} m or {self.average * 100: .1f} cm\n"
        string += f"Standard Deviation = {self.std: .3f} m or {self.std * 100: .1f} cm\n"
        string += f"Error = {self.error: .5f} m or {self.error * 100: .5f} cm\n"
        string += f"Energy = {self.energy: .3f} J  or {self.energy * 1000: .1f} mJ\n"

        # +- 
        string += f"Percent Error = {self.error / self.average * 100: .1f}%\n"
        
        # final value
        string += f"Final Value = {self.average * 100: .1f} cm +- {self.error * 100: .5f} cm\n"

        return string

    

mass = [28.2, 8.4, 3.5]
data_large = [69, 71, 68, 70, 72, 71, 70]
data_medium = [50, 50, 50, 47, 50, 49, 51]
data_small = [40, 38, 38, 40, 39, 38, 38]
data = [data_large, data_medium, data_small]

mass = [x / 1000 for x in mass]

trials = []
for i, m in enumerate(mass):
    trials.append(Trial(mass=m, data=[x / 1000 for x in data[i]], height=1.2))

trials.append(Trial(mass=28.2/1000, data=[79/1000], height=1.18))

for trial in trials:
    print(trial)