Data Analysis Tutorials

Learn how to append key-value pairs in a Python dictionary using methods such as square bracket notation, .update() for bulk additions, and .setdefault() for conditional inserts.

To calculate standard deviation in Excel, enter your data into a range of cells and use either =STDEV.S() for sample data or =STDEV.P() for population data.

Understand how to remove items from a list in Python. Familiarize yourself with methods like remove(), pop(), and del for list management.

Learn how to use Python's pop() method to remove elements from lists and dictionaries, including how to remove items while iterating. Learn to avoid common errors like IndexError and KeyError.

Enhance your SQL skills with the SQL PIVOT operator. Learn to convert rows into columns to create pivot tables in SQL Server and Oracle.

Discover the power of the SQL SUM() function for data aggregation. Learn how to implement rolling sums, cumulative sums, and sum multiple columns effectively.

Discover three straightforward techniques to round up numbers in Python: using math.ceil() from the math module, using the decimal module, and NumPy.

Discover the output and performance differences between UNION and UNION ALL: UNION removes duplicates while UNION ALL includes them.

Combine VLOOKUP() with IF() for efficient data analysis, including conditional lookups, error handling, and dynamic column indexing.

Learn how to rank data in Excel with RANK(), RANK.EQ(), and RANK.AVG() functions. Understand their differences, applications, and tips for accurate data analysis.

Read our step-by-step instructions for how to upgrade Pip and Python on Windows, macOS, and Linux. Keep your environment up-to-date and compatible.

Learn to use the Python pass statement in loops, functions, and classes. Understand the pass statement's importance in code execution and readability.