Python Interview Questions & Answers for Data Import and Export

Below are common interview questions and sample answers related to data import and export in Python.

Questions:

1. What are some common file formats used for data import/export in Python? Answer: The most common file formats include CSV, JSON, XML, Excel, and SQL databases. Python libraries like pandas, json, xml.etree.ElementTree, and sqlite3 make it easier to work with these formats.

2. How can you import data from a CSV file in Python? Answer: You can use Python’s built-in csv module or the pandas library to import data from a CSV file. With pandas, it’s as simple as df = pd.read_csv("file.csv").

3. How do you export a DataFrame to an Excel file using pandas? Answer: You can use the to_excel() function in pandas. For example, df.to_excel("output.xlsx") will save the DataFrame df to an Excel file named output.xlsx.

4. What is the JSON module and how do you import/export JSON data in Python? Answer: The json module in Python allows you to parse JSON files into Python objects and vice versa. You can use json.loads() to read JSON data and json.dumps() to write JSON data.

5. Explain how you would connect to an SQL database in Python. Answer: Python has several libraries like sqlite3, psycopg2, or sqlalchemy to connect to SQL databases. You usually establish a connection using a connection string and then use SQL queries to interact with the database.

6. How would you read an XML file in Python? Answer: You can use Python’s built-in ElementTree module to parse XML files. This module provides a way to manipulate and traverse the XML structure.

7. How do you handle missing or corrupted data during import? Answer: In pandas, you can use parameters like na_values and error_bad_lines to handle missing or corrupted data during the import process.

8. What is the role of the os module in data import/export? Answer: The os module allows you to interact with the operating system. This is useful for tasks like navigating to the directory where the data files are stored, checking if a file exists, or creating new directories to store exported data.

9. How would you import data from an API into Python? Answer: One common way is to use the requests library to make an HTTP request to the API endpoint, and then parse the returned JSON data into a Python object.

10. How can you schedule regular data imports/exports in Python? Answer: You can use task scheduling libraries like schedule or use cron jobs in Unix-like systems to run your Python scripts at specified times for regular data import/export.