Treffer: Python: Data Analytics and Visualization

Title:
Python: Data Analytics and Visualization
Publisher Information:
Packt Publishing 2017
Document Type:
E-Ressource Electronic Resource
Index Terms:
Availability:
Open access content. Open access content
copyrighted
Note:
English
Contributing Source:
CYBERLIBRIS
From OAIster®, provided by the OCLC Cooperative.
Accession Number:
edsoai.on1268803428
Database:
OAIster

Weitere Informationen

Understand, evaluate, and visualize dataAbout This BookLearn basic steps of data analysis and how to use Python and its packagesA step-by-step guide to predictive modeling including tips, tricks, and best practicesEffectively visualize a broad set of analyzed data and generate effective resultsWho This Book Is ForThis book is for Python Developers who are keen to get into data analysis and wish to visualize their analyzed data in a more efficient and insightful manner.What You Will LearnGet acquainted with NumPy and use arrays and array-oriented computing in data analysisProcess and analyze data using the time-series capabilities of PandasUnderstand the statistical and mathematical concepts behind predictive analytics algorithmsData visualization with MatplotlibInteractive plotting with NumPy, Scipy, and MKL functionsBuild financial models using Monte-Carlo simulationsCreate directed graphs and multi-graphsAdvanced visualization with D3In DetailYou will start the course with an introduction to the principles of data analysis and supported libraries, along with NumPy basics for statistics and data processing. Next, you will overview the Pandas package and use its powerful features to solve data-processing problems. Moving on, you will get a brief overview of the Matplotlib API .Next, you will learn to manipulate time and data structures, and load and store data in a file or database using Python packages. You will learn how to apply powerful packages in Python to process raw data into pure and helpful data using examples. You will also get a brief overview of machine learning algorithms, that is, applying data analysis results to make decisions or building helpful products such as recommendations and predictions using Scikit-learn.After this, you will move on to a data analytics specialization—predictive analytics. Social media and IOT have resulted in an avalanche of data. You will get started with predictive analytics using Python. You will see how to create predic