Python Pandas Et Les 36 Probl Mes De Data Science Probl Mes Et Exercices Corrig S Pas Pas

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Python Pandas Et Les 36 Probl Mes De Data Science

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Author : Frédéric Bro
language : fr
Publisher:
Release Date : 2021-10-12

Python Pandas Et Les 36 Probl Mes De Data Science written by Frédéric Bro and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-12 with categories.

Python Pandas Et Les 36 Probl Mes De Data Science Probl Mes Et Exercices Corrig S Pas Pas

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Author : Frédéric Bro
language : fr
Publisher: Editions Ellipses
Release Date : 2021-10-12

Python Pandas Et Les 36 Probl Mes De Data Science Probl Mes Et Exercices Corrig S Pas Pas written by Frédéric Bro and has been published by Editions Ellipses this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-12 with Mathematics categories.

Ce livre contient 36 problèmes corrigés pour apprendre à traiter les données de toutes tailles (big data), et des vidéos et figures dynamiques en bonus accessibles via des QR codes. • Problèmes corrigés pas à pas • Data visualisation, cartes statistiques • Fouille et analyse de données • Modélisation, simulation, lanceur d’alerte • Prédiction et premiers pas vers l’IA

Python Du Grand D Butant La Programmation Objet

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Author : Nicolas Bourgeois
language : fr
Publisher: Editions Ellipses
Release Date : 2024-07-09

Python Du Grand D Butant La Programmation Objet written by Nicolas Bourgeois and has been published by Editions Ellipses this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-09 with Computers categories.

Cet ouvrage propose : une pédagogie par l’exemple et la pratique.100 exercices et problèmes corrigés.une découverte pas à pas de nombreux concepts informatiques fondamentaux structures de données, analyse de complexité, programmation orientée objet). Il recouvre l'équivalent de quatre semestres d'enseignement de licence : initiation à la programmation, algorithmique, fouille de données et initiation à la programmation orientée objet. Cet ouvrage s’adresse aux étudiants en licence d'informatique ou de mathématiques appliquées, en master d'économétrie ou de data science, professionnels d'analyse de données.

Python For Data Analysis

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Author : Wes Mckinney
language : en
Publisher:
Release Date : 2017

Python For Data Analysis written by Wes Mckinney and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with Data mining categories.

Hands On Data Analysis With Pandas

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Author : Stefanie Molin
language : en
Publisher: Packt Publishing Ltd
Release Date : 2021-04-29

Hands On Data Analysis With Pandas written by Stefanie Molin and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-29 with Computers categories.

Get to grips with pandas by working with real datasets and master data discovery, data manipulation, data preparation, and handling data for analytical tasks Key Features Perform efficient data analysis and manipulation tasks using pandas 1.x Apply pandas to different real-world domains with the help of step-by-step examples Make the most of pandas as an effective data exploration tool Book DescriptionExtracting valuable business insights is no longer a ‘nice-to-have’, but an essential skill for anyone who handles data in their enterprise. Hands-On Data Analysis with Pandas is here to help beginners and those who are migrating their skills into data science get up to speed in no time. This book will show you how to analyze your data, get started with machine learning, and work effectively with the Python libraries often used for data science, such as pandas, NumPy, matplotlib, seaborn, and scikit-learn. Using real-world datasets, you will learn how to use the pandas library to perform data wrangling to reshape, clean, and aggregate your data. Then, you will learn how to conduct exploratory data analysis by calculating summary statistics and visualizing the data to find patterns. In the concluding chapters, you will explore some applications of anomaly detection, regression, clustering, and classification using scikit-learn to make predictions based on past data. This updated edition will equip you with the skills you need to use pandas 1.x to efficiently perform various data manipulation tasks, reliably reproduce analyses, and visualize your data for effective decision making – valuable knowledge that can be applied across multiple domains.What you will learn Understand how data analysts and scientists gather and analyze data Perform data analysis and data wrangling using Python Combine, group, and aggregate data from multiple sources Create data visualizations with pandas, matplotlib, and seaborn Apply machine learning algorithms to identify patterns and make predictions Use Python data science libraries to analyze real-world datasets Solve common data representation and analysis problems using pandas Build Python scripts, modules, and packages for reusable analysis code Who this book is for This book is for data science beginners, data analysts, and Python developers who want to explore each stage of data analysis and scientific computing using a wide range of datasets. Data scientists looking to implement pandas in their machine learning workflow will also find plenty of valuable know-how as they progress. You’ll find it easier to follow along with this book if you have a working knowledge of the Python programming language, but a Python crash-course tutorial is provided in the code bundle for anyone who needs a refresher.

Solving Data Science Case Studies With Python

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Author : Aman Kharwal
language : en
Publisher: Thecleverprogrammer
Release Date : 2021-06-28

Solving Data Science Case Studies With Python written by Aman Kharwal and has been published by Thecleverprogrammer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-28 with Computers categories.

This book is specially written for those who know the basics of the Python programming language as well as the necessary Python libraries you need for data science like NumPy, Pandas, Matplotlib, Seaborn, Plotly, and Scikit-learn. This book aims to teach you how to think while solving a business problem with your data science skills. To achieve the goal of this book, I started by giving you all the knowledge you need to have before you apply for your first data science job. The technical skills and soft skills you need to become a Data Scientist are also discussed in this book. Next, you'll find some of the best data science case studies that will help you understand what your approach should be while solving a business problem. Ultimately, you will also find some of the most important data science interview questions with their solutions at the end. I hope this book will add a lot of value to your data science skills and that you will feel confident in your entire journey to become Data Scientist.

Data Science Using Python And R

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Author : Chantal D. Larose
language : en
Publisher: John Wiley & Sons
Release Date : 2019-03-20

Data Science Using Python And R written by Chantal D. Larose and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-20 with Computers categories.

Learn data science by doing data science! Data Science Using Python and R will get you plugged into the world’s two most widespread open-source platforms for data science: Python and R. Data science is hot. Bloomberg called data scientist “the hottest job in America.” Python and R are the top two open-source data science tools in the world. In Data Science Using Python and R, you will learn step-by-step how to produce hands-on solutions to real-world business problems, using state-of-the-art techniques. Data Science Using Python and R is written for the general reader with no previous analytics or programming experience. An entire chapter is dedicated to learning the basics of Python and R. Then, each chapter presents step-by-step instructions and walkthroughs for solving data science problems using Python and R. Those with analytics experience will appreciate having a one-stop shop for learning how to do data science using Python and R. Topics covered include data preparation, exploratory data analysis, preparing to model the data, decision trees, model evaluation, misclassification costs, naïve Bayes classification, neural networks, clustering, regression modeling, dimension reduction, and association rules mining. Further, exciting new topics such as random forests and general linear models are also included. The book emphasizes data-driven error costs to enhance profitability, which avoids the common pitfalls that may cost a company millions of dollars. Data Science Using Python and R provides exercises at the end of every chapter, totaling over 500 exercises in the book. Readers will therefore have plenty of opportunity to test their newfound data science skills and expertise. In the Hands-on Analysis exercises, readers are challenged to solve interesting business problems using real-world data sets.

Introduction To Data Science With Python

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Author : Mark Smart
language : en
Publisher: Independently Published
Release Date : 2018-11-09

Introduction To Data Science With Python written by Mark Smart and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-09 with categories.

This book is a guide for you on how to use Pandas and Numpy in Python programming language for data analysis. The author begins by helping you familiarize yourself with the basics of data science, Numpy and Pandas. You are guided on how to work with Numpy arrays and how to manipulate them. The various operations that you can perform on your data via the Pandas library have been discussed. You will also know how to create various data structures in Pandas for data storage. Data from the environment is dirty. The process of cleaning such data has been discussed. This involves handling outliers, missing values etc. The author guides you on how to work with data in various types of storage formats. Examples include MS Excel, CSV files, JSON, etc. You are also guided on how to calculate various measures for your data. The process of visualizing data has been explored in detail. About this book: Getting Started with Python for Data Science Working with Numpy Working with Pandas Cleansing Data Working with CSV Data Working with XLS Data Data Wrangling Measures of Central Tendency Calculating Variance Normal Distribution Working with JSON Data Data Visualization Tags: data science with python, python, pandas programming, numpy, pandas, pandas python, pandas in python, numpy in python, numpy python, numpy pandas, data science, ms excel books, json, python for data science, pivot tables, excel pivot tables, data visualisation, data visualisation python, data visualisation for dummies, data visualisation excel, algorithms for data science.

Hands On Data Analysis And Visualization With Pandas

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Author : PURNA CHANDER RAO KATHULA
language : en
Publisher: BPB Publications
Release Date : 2020-09-03

Hands On Data Analysis And Visualization With Pandas written by PURNA CHANDER RAO KATHULA and has been published by BPB Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-09-03 with Computers categories.

Learn how to use JupyterLab, Numpy, pandas, Scipy, Matplotlib, and Seaborn for Data science Key Features a- Get familiar with different inbuilt Data structures, Functional programming, and Datetime objects. a- Handling heavy Datasets to optimize the data types for memory management, reading files in chunks, dask, and modin pandas. a- Time-series analysis to find trends, seasonality, and cyclic components. Seaborn to build aesthetic plots with high-level interfaces and customized themes. a- Exploratory data analysis with real-time datasets to maximize the insights about data. Description The book will start with quick introductions to Python and its ecosystem libraries for data science such as JupyterLab, Numpy, Pandas, SciPy, Matplotlib, and Seaborn. This book will help in learning python data structures and essential concepts such as Functions, Lambdas, List comprehensions, Datetime objects, etc. required for data engineering. It also covers an in-depth understanding of Python data science packages where JupyterLab used as an IDE for writing, documenting, and executing the python code, Numpy used for computation of numerical operations, Pandas for cleaning and reorganizing the data, handling large datasets and merging the dataframes to get meaningful insights. You will go through the statistics to understand the relation between the variables using SciPy and building visualization charts using Matplotllib and Seaborn libraries. What will you learn a- Learn about Python data containers, their methods, and attributes. a- Learn Numpy arrays for the computation of numerical data. a- Learn Pandas data structures, DataFrames, and Series. a- Learn statistics measures of central tendency, central limit theorem, confidence intervals, and hypothesis testing. a- A brief understanding of visualization, control, and draw different inbuilt charts to extract important variables, detect outliers, and anomalies using Matplotlib and Seaborn. Who this book is for This book is for anyone who wants to use Python for Data Analysis and Visualization. This book is for novices as well as experienced readers with working knowledge of the pandas library. Basic knowledge of Python is a must. Table of Contents 1. Introduction to Data Analysis 2. Jupyter lab 3. Python overview 4. Introduction to Numpy 5. Introduction to Pandas 6. Data Analysis 7. Time-Series Analysis 8. Introduction to Statistics 9. Matplotlib 10. Seaborn 11. Exploratory Data Analysis About the Author Purna Chander Rao.Kathula is a Data Science enthusiast, Data Manager, Seasoned Programmer, and a Technical trainer, with around 17+ years of experience in a vast array of languages, including Perl, C, C++, Java, and Python and wide variety set of domains like Insurance, Adtech, Storage, Gaming, Mobility, Big Data, and Analytics. He is a certified Applied Data Science with Python Specialization, from Coursera, University of Michigan. He graduated from the College of Engineering G.I.T.A.M with a degree in Mechanical Engineering. He is a frequent speaker at DataScience and Data Engineering user groups, and he regularly delivers webinars and conducts training on Hadoop, Big data, Data Analysis, and Visualization technologies. Your Blog links https://blog.imaginea.com/author/purna-chander-rao-kathula/ https://www.slideshare.net/PurnaChander1 https://www.slideshare.net/sriganesha/hive-and-data-analysis-using-pandas Your LinkedIn Profile: https://www.linkedin.com/in/purna-chander-rao-kathula-043852a/

Python For Data Science

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Author : William Krystal
language : en
Publisher: Independently Published
Release Date : 2020-09

Python For Data Science written by William Krystal and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-09 with categories.

Ready for the Data Science career?-Are you curious about Data Science and looking to start your self-learning journey into the world of data with Python?-Are you an experienced developer looking for a landing in Data Science!In both cases, you are at the right place!Welcome to Python for Data Science: Learn Data Science From Scratch bookPython is the most popular programming language for the data science process in recent years and also do not forget that data scientist has been ranked the number one job on several job search sites! With Python skills, you will encounter many businesses that use Python and its libraries for data science. Almost all companies working on machine learning and data science use Python's Pandas library. Thanks to the large libraries provided, The number of companies and enterprises using Python is increasing day by day. The world we are in is experiencing the age of informatics. Python and its Pandas library will be the right choice for you to take part in this world and create your own opportunities, In this book, we will open the door of the Data Science world and will move deeper. You will learn the fundamentals of Python and its beautiful libraries such as Numpy, Pandas, and Matplotlib step by step.Throughout the book, we will teach you how to use the Python to analyze data, create beautiful visualizations, and use powerful machine learning algorithms and we will also do a variety of exercises to reinforce what we have learned in this Python for Data Science book.In this book you will learn;-How to use Anaconda and Jupyter notebook, -Fundamentals of Python such as-Datatypes in Python, -Lots of datatype operators, methods and how to use them, -Conditional concept, if statements-The logic of Loops and control statements-Functions and how to use them-How to use modules and create your own modules-Data science and Data literacy concepts-Fundamentals of Numpy for Data manipulation such as-Numpy arrays and their features-How to do indexing and slicing on Arrays-Lots of stuff about Pandas for data manipulation such as-Pandas series and their features-Dataframes and their features-Hierarchical indexing concept and theory-Groupby operations-The logic of Data Munging-How to deal effectively with missing data effectively-Combining the Data Frames-How to work with Dataset files-And also you will learn fundamentals thing about Matplotlib library such as-Pyplot, Pylab and Matplotlb concepts-What Figure, Subplot and Axes are-How to do figure and plot customizationAnd we will do many exercises. Finally, we will also have 4 different final projects covering all of these subjects.Why would you want to take this book?We have prepared this book in the simplest way for beginners and have prepared many different exercises to help them understand better.No prior knowledge is needed!In this book, you need no previous knowledge about Python, Pandas or Data Science.This book will take you from a beginner to a more experienced level.If you are new to data science or have no idea about what data science does no problem, you will learn anything you need to start data science.If you are a software developer or familiar with other programming languages and you want to start a new world, you are also in the right place. You will learn step by step with hands-on examples.