ML - Code beginning

import numpy as np
import pandas as pd
from sklearn.preprocessing import OneHotEncoder


# Load a file .csv
print("**********************************")
people = pd.read_csv("people.txt", sep=";", header=None, names=["Age", "Height", "Weight"])
print(people)
print()
# Missing values are found by average
people = people.fillna(people.mean())
print(people)
print()
print()

# Statistical info
print("**********************************")
print("Head: ")
print(people.head())
print()
print("Describe: ")
print(people.describe())
print()
print("Null elements in each column: ")
print(people.isnull().sum())
print()
print()

# Convert categorial data to numerical
# Create Encoder
encoder = OneHotEncoder(handle_unknown="ignore", sparse=False)
encoder.fit(people)
people_one_hot = encoder.transform(people)
print("**********************************")
print(people_one_hot)