Data Analysis and Visualization Using Python: Analyze Data to Create Visualizations for BI Systems - Brossura

Embarak, Dr. Ossama

Brossura

ISBN 10: 1484241088 ISBN 13: 9781484241080

Casa editrice: Apress, 2018

Riassunto

Look at Python from a data science point of view and learn proven techniques for data visualization as used in making critical business decisions. Starting with an introduction to data science with Python, you will take a closer look at the Python environment and get acquainted with editors such as Jupyter Notebook and Spyder. After going through a primer on Python programming, you will grasp fundamental Python programming techniques used in data science. Moving on to data visualization, you will see how it caters to modern business needs and forms a key factor in decision-making. You will also take a look at some popular data visualization libraries in Python. 

Shifting focus to data structures, you will learn the various aspects of data structures from a data science perspective. You will then work with file I/O and regular expressions in Python, followed by gathering and cleaning data. Moving on to exploring and analyzing data, you will look at advanced data structures in Python. Then, you will take a deep dive into data visualization techniques, going through a number of plotting systems in Python. 

In conclusion, you will complete a detailed case study, where you’ll get a chance to revisit the concepts you’ve covered so far.

What You Will Learn

• Use Python programming techniques for data science
  
• Master data collections in Python 
  
• Create engaging visualizations for BI systems
  
• Deploy effective strategies for gathering and cleaning data
  
• Integrate the Seaborn and Matplotlib plotting systems
  

Who This Book Is For

Developers with basic Python programming knowledge looking to adopt key strategies for data analysis and visualizations using Python.

Su questo libro

Informazioni sull?autore

Dr. Ossama Embarak holds a Doctorate in Computer Science from the Heriot-Watt University in Scotland, UK. He has more than 2 decades of training and teaching experience with a number of programming languages including C++, Java, C#, R, and Python. He is presently the lead CIS Program Coordinator for Higher Colleges of Technology, UAE’s largest applied higher educational institution, with over 23,000 students attending campuses throughout the region.

Recently, he got an interdisciplinary research grant of 199000 AED to implement a machine learning system for mining students’ knowledge and skills.

He has participated in many scholarly activities as a reviewer for journals in the field of computer and information sciences, artificial intelligence, mobile and web technologies. He has published numerous papers in datamining and knowledge discovery, and was also involved as a co-chair for the Technical Program Committee (TPC) for various regional and international conferences.

Dalla quarta di copertina

Look at Python from a data science point of view and learn proven techniques for data visualization as used in making critical business decisions. Starting with an introduction to data science with Python, you will take a closer look at the Python environment and get acquainted with editors such as Jupyter Notebook and Spyder. After going through a primer on Python programming, you will grasp fundamental Python programming techniques used in data science. Moving on to data visualization, you will see how it caters to modern business needs and forms a key factor in decision-making. You will also take a look at some popular data visualization libraries in Python. 

Shifting focus to data structures, you will learn the various aspects of data structures from a data science perspective. You will then work with file I/O and regular expressions in Python, followed by gathering and cleaning data. Moving on to exploring and analyzing data, you will look at advanced data structures in Python. Then, you will take a deep dive into data visualization techniques, going through a number of plotting systems in Python. 

In conclusion, you will complete a detailed case study, where you’ll get a chance to revisit the concepts you’ve covered so far.

You will:

• Use Python programming techniques for data science
  
• Master data collections in Python 
  
• Create engaging visualizations for BI systems
  
• Deploy effective strategies for gathering and cleaning data
  
• Integrate the Seaborn and Matplotlib plotting systems

Dettagli dell'edizione

• Editore: Apress
• Data di pubblicazione: 2018
• Lingua: Inglese
• ISBN 10: 1484241088
• ISBN 13: 9781484241080
• Rilegatura: Copertina flessibile
• Numero edizione: 1
• Numero di pagine: 396
• Contatto del produttore: Springer Nature Customer Service Center GmbH; ProductSafety@springernature.com; ; Europaplatz 3,69115 Heidelberg, Germany; Heidelberg; 69115; Germania