Getting Started

Goal: set up your environment and run your first notebooks in this repo.

What you’ll learn

• Install Python and Jupyter
• Open and run notebooks
• Understand the repository layout

Prerequisites

• Python 3.9+ (3.10+ recommended)
• pip or conda

Quick setup (pip)

1. Create a virtual environment
   • macOS/Linux: python3 -m venv .venv && source .venv/bin/activate
2. Install basics: pip install -U jupyter numpy pandas seaborn scikit-learn matplotlib
3. Start Jupyter: jupyter notebook

First notebooks

• Intro to Jupyter: read the code below
• Data cleaning (Iris): follow the Data Preprocessing lesson
• Classification on Iris: follow the Classification lesson
• To run the original notebooks, open the module’s notebooks folder on GitHub

Datasets

• Small CSVs live in data/
• Iris dataset: Iris.csv
• Iris (with missing values for cleaning practice): Iris for cleaning.csv

Next steps

• Continue to: data preprocessing
• Or jump to: classification

Intro notebook code

The code cells below are included in the original intro.ipynb notebook in the module’s notebooks folder on GitHub.

print("Hello World!")

# Variable declaration
a = 5
b = 3
# Arithmetic operations
sum_result = a + b
difference_result = a - b
product_result = a * b
quotient_result = a / b
print("Sum:", sum_result)
print("Difference:", difference_result)
print("Product:", product_result)
print("Quotient:", quotient_result)

# Data types
integer_var = 10
float_var = 3.14
string_var = "Hello"
print("Integer Variable:", integer_var)
print("Float Variable:", float_var)
print("String Variable:", string_var)

# List creation
numbers = [10, 5, 8, 15, 7]
# List operations
sum_of_numbers = sum(numbers)
average_of_numbers = sum_of_numbers / len(numbers)
sorted_numbers = sorted(numbers)
print("Sum of Numbers:", sum_of_numbers)
print("Average of Numbers:", average_of_numbers)
print("Sorted Numbers:", sorted_numbers)

# Looping through the list
for num in numbers:
    print("Current Number:", num)
# While loop example
i = 0
while i < len(numbers):
    print("Current Number (while loop):", numbers[i])
    i += 1

pip install pandas

import pandas as pd
# Creating a DataFrame
data = {'Name': ['Alice', 'Bob', 'Charlie'],
'Age': [25, 30, 22],
'City': ['New York', 'San Francisco', 'Los Angeles']}
df = pd.DataFrame(data)
print(df)

# Accessing columns
names = df['Name']
ages = df['Age']
# Adding a new column
df['Gender'] = ['Female', 'Male', 'Male']
print("Names:", names)
print("Ages:", ages)
print("Modified DataFrame:")
print(df)

# Creating a text file with sample data
with open('data.txt', 'w') as file:
    file.write("This is sample data.\nLine 2: More data.")

# Reading and printing contents of the file
with open('data.txt', 'r') as file:
    file_contents = file.read()
print("File Contents:")
print(file_contents)

# Reading CSV file into DataFrame
df_csv = pd.read_csv(r'C:\Users\ICT-LAPTOP\Downloads\sample_dataset.csv')

# Displaying DataFrame head, tail, and descriptive statistics
print("DataFrame Head:")
print(df_csv.head())
print("DataFrame Tail:")
print(df_csv.tail())
print("DataFrame Descriptive Statistics:")
print(df_csv.describe())

pip install matplotlib

import matplotlib.pyplot as plt
# Plotting a simple graph
x = [1, 2, 3, 4, 5]
y = [10, 5, 8, 15, 7]
plt.plot(x, y)
plt.xlabel('X-axis')
plt.ylabel('Y-axis')
plt.title('Simple Plot')
plt.show()