Data Analysis | Python 7 | Dynamic Reading of CSV or XLS Files

In the data world, when working with Python, it is often necessary to read CSV or Excel files using a function. To accomplish this, a dynamic method can be implemented, which will take the input file and check its file extension type, such as csv, xls, or xlsx.

 

The purpose of this dynamic method is to determine the file type and then appropriately read the file and process the data. This approach allows for flexibility in handling different file formats, ensuring that the data can be efficiently retrieved and utilized.

 

This scenario is a commonly encountered problem in real-time projects that involve handling and analyzing data. By implementing a dynamic method to read and process different file types, it becomes easier and more efficient to work with varied data sources, ultimately enhancing productivity and data extraction capabilities.

 

Step1 : Import Librearies

import csv

import sys

import pandas as pd

 

Step 2 read csv: This method will read CSV file

 

def read_csv(file):

    try:

        df=pd.read_csv(file)

        print(df)

    except FileNotFoundError:

        print("File not found")

    except Exception as err:

        print("An Exception error",err)

 

Step 3: This method will read XLS/XLSX file

def read_xls(file):

    try:

        df=pd.read_excel(file,sheet_name='data')

        print(df)

    except FileNotFoundError:

        print("File not found")

    except Exception as err:

        print("An Exception error",err)

 

Step 4: Enter your input file

def file_process(filename):

    if filename.endswith(".csv"):

        read_csv(filename)

    elif filename.endswith('.xls') or filename.endswith('.xlsx'):

        read_xls(filename)

    else:

        print("Unsupported file type")

 

filename=r'G:\ETL_Automation\data\datasingle.xlsx'

file_process(filename)