Python Pandas Et Les 36 Probl Mes De Data Science
DOWNLOAD
Download Python Pandas Et Les 36 Probl Mes De Data Science PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Python Pandas Et Les 36 Probl Mes De Data Science book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Python Pandas Et Les 36 Probl Mes De Data Science
DOWNLOAD
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
DOWNLOAD
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 Data Science Essentials
DOWNLOAD
Author : Alberto Boschetti
language : en
Publisher: Packt Publishing Ltd
Release Date : 2015-04-30
Python Data Science Essentials written by Alberto Boschetti 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 2015-04-30 with Computers categories.
If you are an aspiring data scientist and you have at least a working knowledge of data analysis and Python, this book will get you started in data science. Data analysts with experience of R or MATLAB will also find the book to be a comprehensive reference to enhance their data manipulation and machine learning skills.
Introduction To Data Science With Python
DOWNLOAD
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.
Data Science With Jupyter
DOWNLOAD
Author : Gupta Prateek
language : en
Publisher: BPB Publications
Release Date : 2019-09-20
Data Science With Jupyter written by Gupta Prateek and has been published by BPB Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-20 with Computers categories.
Step-by-step guide to practising data science techniques with Jupyter notebooksKey features Acquire Python skills to do independent data science projects Learn the basics of linear algebra and statistical science in Python way Understand how and when they're used in data science Build predictive models, tune their parameters and analyze performance in few steps Cluster, transform, visualize, and extract insights from unlabelled datasets Learn how to use matplotlib and seaborn for data visualization Implement and save machine learning models for real-world business scenarios Description Modern businesses are awash with data, making data driven decision-making tasks increasingly complex. As a result, relevant technical expertise and analytical skills are required to do such tasks. This book aims to equip you with just enough knowledge of Python in conjunction with skills to use powerful tool such as Jupyter Notebook in order to succeed in the role of a data scientist. The book starts with a brief introduction to the world of data science and the opportunities you may come across along with an overview of the key topics covered in the book. You will learn how to setup Anaconda installation which comes with Jupyter and preinstalled Python packages. Before diving in to several supervised, unsupervised and other machine learning techniques, you'll learn how to use basic data structures, functions, libraries and packages required to import, clean, visualize and process data. Several machine learning techniques such as regression, classification, clustering, time-series etc have been explained with the use of practical examples and by comparing the performance of various models. By the end of the book, you will come across few case studies to put your knowledge to practice and solve real-life business problems such as building a movie recommendation engine, classifying spam messages, predicting the ability of a borrower to repay loan on time and time series forecasting of housing prices. Remember to practice additional examples provided in the code bundle of the book to master these techniques.Who this book is forThe book is intended for anyone looking for a career in data science, all aspiring data scientists who want to learn the most powerful programming language in Machine Learning or working professionals who want to switch their career in Data Science. While no prior knowledge of Data Science or related technologies is assumed, it will be helpful to have some programming experience.Table of contents1. Data Science Fundamentals2. Installing Software and Setting up3. Lists and Dictionaries4. Function and Packages5. NumPy Foundation6. Pandas and Dataframe7. Interacting with Databases8. Thinking Statistically in Data Science9. How to import data in Python?10. Cleaning of imported data11. Data Visualization12. Data Pre-processing13. Supervised Machine Learning14. Unsupervised Machine Learning15. Handling Time-Series Data16. Time-Series Methods 17. Case Study - 118. Case Study - 219. Case Study - 320. Case Study - 4About the authorPrateek is a Data Enthusiast and loves the data driven technologies. Prateek has total 7 years of experience and currently he is working as a Data Scientist in an MNC. He has worked with finance and retail clients and has developed Machine Learning and Deep Learning solutions for their business. His keen area of interest is in natural language processing and in computer vision. In leisure he writes posts about Data Science with Python in his blog.
Python For Data Analysis 2nd Edition
DOWNLOAD
Author : William McKinney Wesley
language : en
Publisher:
Release Date : 2017
Python For Data Analysis 2nd Edition written by William McKinney Wesley and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with categories.
Python Data Analytics
DOWNLOAD
Author : Stephen Ward
language : en
Publisher:
Release Date : 2020-10-15
Python Data Analytics written by Stephen Ward and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-15 with categories.
Unlock the programming skills you need to prepare for a lucrative career in Data Science with this comprehensive introduction to Python programming for data analytics! Are you completely new to programming and want to learn how to code, but don't know where to begin? Are you looking to upgrade your data wrangling skills to future-proof your career and break into Data Science and Analytics? If you answered yes to any of the questions above, then keep reading... Data analysis has become a huge industry with tons of career potential and will remain relevant far into the foreseeable future. With the exponential growth and explosion of new data and the focus on using data to improve customer experiences and carry out research, data analysts will be needed to process and make sense of large amounts of information, with Python being the language of choice because of its versatility. In this guide, you're going to be shown everything you need to break into the world of Data Analysis with Python. Filled with tutorials for powerful libraries and practical, hands-on exercises, you're going to learn how to aggregate, munge, analyze and visualize data in Python. Here's a sample of what you're going to discover in Python Data Analytics Why Python is the perfect language to learn if you want to break into Big Data and data analytics Core statistical models and computation methods you need to know about as a budding data analyst How to master the CSV library for reading, writing and handling tabular data Using the Xlrd library to extract data from Microsoft Excel files How to convert text to speech using the powerful Win32.com library How to use the NumPy library to carry out fundamental and basic scientific and technical computing How to use the SciPy library to carry out advanced scientific and highly technical computing Surefire ways to manipulate the easy-to-use data structures of the Pandas framework for high-performance data analysis How to plot complex data, create figures and visualize data using the Python Matplotlib library ...and tons more! If you're completely new to programming and have never written a single line of code, but want to get started, this guide is perfect for as a crash guide to getting up to speed with programming in general. Whether you're a programmer looking to switch into an exciting new field with lots of potential for the future, or a regular data analyst looking to acquire the skills needed to remain relevant in a fast-changing world, this guide will teach you how to master powerful libraries used in the real-world by experienced data scientists.
Introduction To Data Science
DOWNLOAD
Author : Laura Igual
language : en
Publisher: Springer
Release Date : 2017-02-22
Introduction To Data Science written by Laura Igual and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-02-22 with Computers categories.
This accessible and classroom-tested textbook/reference presents an introduction to the fundamentals of the emerging and interdisciplinary field of data science. The coverage spans key concepts adopted from statistics and machine learning, useful techniques for graph analysis and parallel programming, and the practical application of data science for such tasks as building recommender systems or performing sentiment analysis. Topics and features: provides numerous practical case studies using real-world data throughout the book; supports understanding through hands-on experience of solving data science problems using Python; describes techniques and tools for statistical analysis, machine learning, graph analysis, and parallel programming; reviews a range of applications of data science, including recommender systems and sentiment analysis of text data; provides supplementary code resources and data at an associated website.
Hands On Data Analysis With Pandas
DOWNLOAD
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.
Python Data Analytics
DOWNLOAD
Author : Fabio Nelli
language : en
Publisher:
Release Date : 2015
Python Data Analytics written by Fabio Nelli and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with categories.
Python Data Analytics will help you tackle the world of data acquisition and analysis using the power of the Python language. At the heart of this book lies the coverage of pandas, an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language. Author Fabio Nelli expertly shows the strength of the Python programming language when applied to processing, managing and retrieving information. Inside, you will see how intuitive and flexible it is to discover and communicate meaningful patterns of data using Python scripts, reporting systems, and data export. This book examines how to go about obtaining, processing, storing, managing and analyzing data using the Python programming language. You will use Python and other open source tools to wrangle data and tease out interesting and important trends in that data that will allow you to predict future patterns. Whether you are dealing with sales data, investment data (stocks, bonds, etc.), medical data, web page usage, or any other type of data set, Python can be used to interpret, analyze, and glean information from a pile of numbers and statistics. This book is an invaluable reference with its examples of storing and accessing data in a database; it walks you through the process of report generation; it provides three real world case studies or examples that you can take with you for your everyday analysis needs.