Think Different

Combining multiple CSV files in time series data analysis typically involves concatenating or merging the data to create a single, unified dataset. Here's a step-by-step guide on how to do this in Python using the pandas library: Assuming you have several CSV files in the same directory and each CSV file represents a time series for a specific period: Step 1: Import the required libraries. ```python import pandas as pd import os ``` Step 2: List all CSV files in the directory. ```python directory_path = "/path/to/your/csv/files"  # Replace with the path to your CSV files csv_files = [file for file in os.listdir(directory_path) if file.endswith('.csv')] ``` Step 3: Initialize an empty DataFrame to store the combined data. ```python combined_data = pd.DataFrame() ``` Step 4: Loop through the CSV files, read and append their contents to the combined DataFrame. ```python for file in csv_files:     file_path = os.path.join(directory_path, file)     df = pd.read_csv(f...