16.1 Problem Definition
16.1.1 What are we trying to solve?
Before diving into any data analysis or machine learning project, it's crucial to clearly define the problem we're aiming to solve. It sets the path, allowing us to choose the most suitable techniques and algorithms.
In this Sales Data Analysis case study, our main objectives will be:
- Sales Trend Analysis: Understand the yearly, monthly, and seasonal sales trends.
- Customer Segmentation: Categorize customers based on their purchasing behavior.
- Product Analysis: Identify the best-selling products and categories.
- Sales Forecasting: Predict future sales using machine learning algorithms.
These objectives will guide us through data collection, preprocessing, analysis, and model building.
16.1.2 Python Code: Setting up the Environment
Before starting, let's set up our Python environment:
# Import necessary libraries
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns...