Data Analysis Tutorials

Review three methods to add comments in SQL: single-line comments, multiline comments, and inline comments using the following syntax: --, /*, and */.

Learn the statistical concept of correlation, and follow along in calculating and interpreting correlations for a sample dataset, in a step-by-step tutorial.

Database normalization is an important process used to organize and structure relational databases. This process ensures that data is stored in a way that minimizes redundancy, simplifies querying, and improves data integrity.

Python offers three logical operators: and, or, and not. These operators, also known as Boolean operators, evaluate multiple conditions and determine an expression's overall truth value.

Set operations in SQL are techniques for combining or comparing the results of two or more SELECT statements.

Implementing the assert statement in Python is straightforward: We use assert to test conditions and display a message if the condition is false.

Read our comprehensive guide on how to work with data structures in R programming: vectors, lists, arrays, matrices, factors, and data frames.

Discover advantages of Python pathlib over the os module by exploring path objects, path components, and common path operations for file system interaction.

Learn how to create a line break for a string in Python and create proper indentation using backslashes, parentheses, and other delimiters.

Learn more about Data Manipulation Language (DML), how it compares to DQL and DDL, and master DML commands including SELECT, INSERT, DELETE, and UPDATE.

Marketing mix modeling (MMM) is a data-driven analytical approach used by businesses to evaluate the effectiveness of their marketing strategies and allocate resources optimally.

Calculating the coefficient of variation in Excel is a straightforward process: we divide STDEV.P by AVERAGE.