Data Analysis | Python | Read CSV or Excel file

This article will explore a common real-time challenge: reading CSV, TXT, and Excel files in Python using appropriate functions.

 

To read CSV, TXT, or Excel files using a Python function, you can follow the steps below:

 

1. Import the required libraries.

2. Define a function to read the file, taking the file path as a parameter.

3. Determine the file extension to identify the file type.

4. For CSV files:

    a. Use the "csv" module to open the file.

    b. Read the contents of the file using the CSV reader.

5. For TXT files:

    a. Open the file using the Python builtin "open" function.

    b. Read the contents of the file using the "readlines" function.

6. For Excel files:

    a. Use the "pandas" library to read the Excel file using the "read_excel" function.

    b. Specify the sheet index or name if required.

7. Return the data read from the file.

 

The initial step is to validate the file extension of the input file, such as csv, xls, xlsx, txt, dat, etc. Afterwards, the following Python code will read and process the appropriate file depending on the detected extension. However, it is important to note that this is a generic example and may differ in a real-time environment.

Here's an example Python function implementing these steps:

 

```python

import csv

import pandas as pd

 

def read_file(file_path):

    file_extension = file_path.split('.')[-1].lower()

   

    if file_extension == 'csv':

        with open(file_path, 'r') as file:

            csv_reader = csv.reader(file)

            data = list(csv_reader)

        return data

   

    elif file_extension == 'txt':

        with open(file_path, 'r') as file:

            data = file.readlines()

        return data

   

    elif file_extension == 'xlsx':

        data = pd.read_excel(file_path, sheet_name='Sheet1')

        return data

 

    else:

        return None

       

```

 

You can use this function by passing the file path as an argument. It will return the contents of the file as a list for CSV and TXT files, or a pandas dataframe for Excel files.