Data manipulation language

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Computer engineering
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Related lectures (28)

Data Modeling: Concepts and Applications

Introduces data modeling concepts, SQL usage, and Pandas library applications for efficient data processing.

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Covers structured data representation, arrays, structures, variable declaration, initialization, and functions with multiple return values.

Handling Data: Data Models and Wrangling

Explores data handling fundamentals, including models, sources, and wrangling, emphasizing the importance of understanding and addressing data problems.

Scopes and Lambdas: Data Science with Python

Covers scopes, lambdas, and pandas in data science with Python, including nested declarations, scoping, assignments, and pandas manipulation.

Structuring exploratory spatial data analysis

Explores the structured approach to exploratory spatial data analysis, emphasizing the importance of analytical frameworks and the Visual Seeking Mantra.

Numpy: Creation of Objects

Covers the creation of ndArray objects with Numpy, including intervals, random values, manipulation, operations, and copying.

Opinions: Influence and Manipulation

Examines the formation of opinions, their manipulation, and strategies for protection.

Data Science for Engineers: Part 2

Explores data manipulation, exploration, and visualization in data science projects using Python.

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