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Data Analysis and Visualization Using Python

Data Analysis and Visualization Using Python


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About the Book

Chapter 1: Introduction to data science with python
1.1 What is data science? 1.2 Why Python?1.3 Python learning resources.1.4 Python environment and editors (Jupyter Notebook, Netbeans, etc)1.5 The basics of the python programming1.6 Fundamental python programming techniques 1.6.1 The Tabular data, and data formats1.6.2 Python pandas data science library 1.6.3 Python lambdas, and the numpy library. 1.6.4 Introduce the data cleaning and manipulation techniques1.6.5 Introduce the abstraction of the Series and DataFrame1.6.6 Run basic inferential statistical analysis. 1.7 Exercises and answers
Chapter 2: The importance of data visualization in business intelligence
2.1 Shift from input to output data preference2.2 Why Data visualization is important?2.3 How is the modern business needs Data visualization? 2.4 The future of Data Visualization2.5 How data visualization is used for Business decision making 2.6 Introduce data visualization tchniques 2.6.1 Loading libraries2.6.2 Popular Libraries for Data Visualization in PythonMatplotlibSeabornGeoplotlib PandasPlotly2.6.3 Introduce Plots in Python2.7 Exercises and answers
Chapter 3: Data collections structure
3.1 Lists 3.1.1 Create lists 3.1.2 Accessing values in lists 3.1.3 Add and update lists 3.1.4 Delete list elements 3.1.5 Basic list operations 3.1.6 Indexing, slicing, and matrices 3.1.7 Built-in list functions & methods 3.1.8 List methods 3.1.9 List sorting and traversing 3.1.10 Lists and strings 3.2 Parsing lines 3.3 Aliasing 3.4 Dictionaries3.4.1 Create dictionaries3.4.2 Updating and accessing values in dictionary 3.4.3 Delete dictionary elements 3.4.4 Built-in dictionary functions & methods 3.5 Tuples 3.5.1 Create tuples3.5.2 Updating tuples 3.5.3 Accessing values in tuples 3.5.4 Basic tuples operations 3.6 Series data structure 3.7 DataFrame data structure 3.8 Panel data structure 3.9 Exercises and answers
Chapter 4: File I/O processing & Regular expressions
4.1 File I/O processing 4.1.1 Screen in/out processing 4.1.2 Opening and closing files 4.1.3 The file object attributes 4.1.4 Reading and writing files 4.1.5 Directories in python 4.2 Regular expressions 4.2.1 Regular expression patterns 4.2.2 Special character classes 4.2.3 Repetition cases Alternatives Anchors 4.3 Exercises and answers
Chapter 5: Data gathering and cleaning
5.1 Data cleaning Check missing values Handle the missing values 5.2 Read and clean csv file 5.3 Data integration 5.4 Read the json file 5.5 Reading the html file 5.6 Exercises and answers
Chapter 6: Data exploring and analysis 6.1 Series data structure 6.1.1 Create a series 6.1.2
About the Author: 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.


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Product Details
  • ISBN-13: 9781484241080
  • Publisher: Apress
  • Publisher Imprint: Apress
  • Height: 234 mm
  • No of Pages: 374
  • Spine Width: 21 mm
  • Weight: 603 gr
  • ISBN-10: 1484241088
  • Publisher Date: 20 Nov 2018
  • Binding: Paperback
  • Language: English
  • Returnable: Y
  • Sub Title: Analyze Data to Create Visualizations for Bi Systems
  • Width: 156 mm


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