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  • Top 8 Python Data Engineering Interview Questions with SQL and Pandas Solutions

    Oct 7, 2025

    ·

    mysql, Pandas, Python
    Top 8 Python Data Engineering Interview Questions with SQL and Pandas Solutions
  • A Complete Guide to Databricks Utilities (DBUtils)

    PySparkDatabricks Utilities (DBUtils) provides functionalities like accessing DBFS files, managing clusters, and widgets. Read More ⇢

    A Complete Guide to Databricks Utilities (DBUtils)
  • SQL Query: Extracting Employees Sal > Avg Salary

    The SQL query, Pandas, and PySpark code extract employees earning more than the average salary. Read More ⇢

    SQL Query: Extracting Employees Sal > Avg Salary
  • Using PySpark to Compare Employee Salaries with Their Managers

    The PySpark code demonstrates two methods to compare employee salaries with their manager’s and retrieve the results. Read More ⇢

    Using PySpark to Compare Employee Salaries with Their Managers
  • Free E-book: 30 PySpark Interview Questions with Answers

    The provided content introduces a free e-book with 30 PySpark interview questions and answers for preparation. Read More ⇢

    Free E-book: 30 PySpark Interview Questions with Answers
  • 2 Easy Ways to Read Multiple Files into a Dataframe: PySpark

    The Infosys interview question asks how to read multiple files into a dataframe using wholeTextFiles() or recursiveFileLookup. Read More ⇢

    2 Easy Ways to Read Multiple Files into a Dataframe: PySpark
  • 5 Best Ways to Delete Rows in PySpark

    In PySpark, delete rows from DataFrame: filter, where, na.drop, drop, SQL Expression based on criteria. Read More ⇢

    5 Best Ways to Delete Rows in PySpark
  • Databricks: Essential Interview Questions for Data Engineers

    Interview questions for data engineer roles at top companies. Includes PySpark file reading, MySQL data retrieval, SQL comparison, Databricks workflow, and notebook sharing in Databricks accounts. Read More ⇢

    Databricks: Essential Interview Questions for Data Engineers
  • How to Add New-Column Particular Position: PySpark

    In PySpark, use withColumn() to add a column at a specific position by rearranging columns in a new DataFrame. Read More ⇢

    How to Add New-Column Particular Position: PySpark
  • PySpark: Splitting Text File into Columns Using Substring Function

    In PySpark, use substring and select statements to split text file lines into separate columns of fixed length. Read More ⇢

    PySpark: Splitting Text File into Columns Using Substring Function
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