Lecture

Advanced Pandas Functions

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In course

ENG-209: Data science for engineers with Python

Ce cours propose une immersion progressive et complète dans le domaine de la Data Science à travers le langage Python. Il guide les étudiants depuis la manipulation de données brutes jusqu'à la modélisation et l'extraction de connaissances utiles à partir ...

Description

This lecture covers advanced functions of Pandas, focusing on filtering, labeling, and manipulating dataframes. Topics include selecting elements, creating dataframes, grouping, aggregating, and rearranging data. The instructor demonstrates how to create, inspect, and modify dataframes using Pandas methods. Additionally, the lecture explores grouping operations, applying functions to groups, and aggregating data. Students will learn how to handle missing values, calculate statistics, and perform complex operations on dataframes.

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Instructors (2)

Olivier Verscheure

SWISS DATA SCIENCE CENTER Housed at both EPFL and ETH Zurich, the newly created Swiss Data Science Center (SDSC) will address the fragmentation within today's data and analytics landscapes. The SDSC will be composed of a distributed multi-disciplinary team of data scientists and experts in domains including personalized health and personalized medicine, transportation, earth and environmental science, social science and digital humanities, and economics. The center aims to federate data providers, data and

Jean-Philippe Pellet

Teaching & PhD Courses Data science for engineers with Python ENG-209 This course offers a gradual and comprehensive introduction to the field of Data Science through the Python programming language. It guides students from raw data manipulation to modeling and the extraction of meaningful insights from real-world data.

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Related concepts (32)

Data science

Data science is an interdisciplinary academic field that uses statistics, scientific computing, scientific methods, processes, algorithms and systems to extract or extrapolate knowledge and insights from noisy, structured, and unstructured data. Data science also integrates domain knowledge from the underlying application domain (e.g., natural sciences, information technology, and medicine). Data science is multifaceted and can be described as a science, a research paradigm, a research method, a discipline, a workflow, and a profession.

Data

In common usage and statistics, data (USˈdætə; UKˈdeɪtə) is a collection of discrete or continuous values that convey information, describing the quantity, quality, fact, statistics, other basic units of meaning, or simply sequences of symbols that may be further interpreted formally. A datum is an individual value in a collection of data. Data is usually organized into structures such as tables that provide additional context and meaning, and which may themselves be used as data in larger structures.

Data analysis

Data analysis is the process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making. Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, and is used in different business, science, and social science domains. In today's business world, data analysis plays a role in making decisions more scientific and helping businesses operate more effectively.

Big data

Big data primarily refers to data sets that are too large or complex to be dealt with by traditional data-processing application software. Data with many entries (rows) offer greater statistical power, while data with higher complexity (more attributes or columns) may lead to a higher false discovery rate. Though used sometimes loosely partly because of a lack of formal definition, the interpretation that seems to best describe big data is the one associated with a large body of information that we could not comprehend when used only in smaller amounts.

Data (computer science)

In computer science, data (treated as singular, plural, or as a mass noun) is any sequence of one or more symbols; datum is a single symbol of data. Data requires interpretation to become information. Digital data is data that is represented using the binary number system of ones (1) and zeros (0), instead of analog representation. In modern (post-1960) computer systems, all data is digital. Data exists in three states: data at rest, data in transit and data in use. Data within a computer, in most cases, moves as parallel data.

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