Revnomix Solutions Junior Data Analyst Interview Questions, Process, and Tips

Forecasting is the process of making predictions about future trends based on past and present data.

• Forecasting involves analyzing historical data to make informed predictions about future outcomes.

• It helps businesses anticipate demand, plan resources, and make strategic decisions.

• Common methods of forecasting include time series analysis, regression analysis, and machine learning algorithms.

• Examples of forecasting inc...read more

Drop, delete, and truncate are SQL commands used to remove data from a table, but they differ in their functionality and impact on the table.

• DROP command removes the entire table structure along with data

• DELETE command removes specific rows based on a condition

• TRUNCATE command removes all rows from a table but keeps the table structure intact

• DROP is non-recoverable, DELETE is recoverable, and TRUNCATE is faster than DE

Series in Pandas is a one-dimensional labeled array while array in Numpy is a multi-dimensional container of items of the same type.

• Series in Pandas can hold data of any type and can be indexed by labels.

• Arrays in Numpy are homogeneous in nature, meaning they can only store elements of the same data type.

• Example: Pandas Series - s = pd.Series([1, 2, 3, 4, 5], index=['a', 'b', 'c', 'd', 'e'])

• Example: Numpy Array - arr =

Error handling in Python is the process of dealing with errors that occur during the execution of a program.

• Error handling allows for graceful handling of exceptions and prevents the program from crashing.

• Common error handling techniques include try-except blocks, try-finally blocks, and raising custom exceptions.

• Example: try: a = 10 / 0 except ZeroDivisionError as e: print('Error:', e)

• Example: try: f...read more