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Required modules to be imported to run the function

import numpy as np
import pandas as pd
import xml.etree.ElementTree as ET

Function for reading the file from the file_path and returning it as the data frame

Load data from CSV, XML, Excel, or JSON file into a Pandas DataFrame.

Parameters: - file_path (str): Path to the file to be loaded.

Returns: - df (DataFrame): Pandas DataFrame containing the loaded data.

def load_to_df(file_path):
    try:
        # Determine file type based on extension
        file_type = file_path.split(".")[-1].lower()

        if file_type == "csv":
            df = pd.read_csv(file_path)
        elif file_type == "xml":
            tree = ET.parse(file_path)
            root = tree.getroot()

            data = []
            for item in root.findall("row"):
                row = {}
                for child in item:
                    row[child.tag] = child.text
                data.append(row)

            df = pd.DataFrame(data)
        elif file_type in ["xls", "xlsx"]:
            df = pd.read_excel(
                file_path, sheet_name="Sheet1"
            )  # Specify sheet name if necessary
        elif file_type == "json":
            df = pd.read_json(file_path)
        else:
            raise ValueError(f"Unsupported file type: {file_type}")

        # Print information about columns
        print(f"Loaded {file_type.upper()} file successfully.")
        print("Columns:")
        print(df.columns)

        return df

    except FileNotFoundError:
        print(f"Error: File '{file_path}' not found.")
        return None

    except Exception as e:
        print(f"Error loading file '{file_path}':")
        print(e)
        return None