عنوان

Data analysis and visualization using Python :

(Number (ISBN

1484241096

(Number (ISBN

9781484241097

Erroneous ISBN

1484241088

Erroneous ISBN

9781484241080

Title Proper

Data analysis and visualization using Python :

General Material Designation

[Book]

Other Title Information

analyze data to create visualizations for BI systems /

First Statement of Responsibility

Ossama Embarak.

Place of Publication, Distribution, etc.

[Berkeley, CA] :

Name of Publisher, Distributor, etc.

Apress,

Date of Publication, Distribution, etc.

2018.

Specific Material Designation and Extent of Item

1 online resource

Text of Note

Includes bibliographical references and index.

Text of Note

Intro; Table of Contents; About the Author; About the Technical Reviewers; Introduction; Chapter 1: Introduction to Data Science with Python; The Stages of Data Science; Why Python?; Basic Features of Python; Python Learning Resources; Python Environment and Editors; Portable Python Editors (No Installation Required); Azure Notebooks; Offline and Desktop Python Editors; The Basics of Python Programming; Basic Syntax; Lines and Indentation; Multiline Statements; Quotation Marks in Python; Multiple Statements on a Single Line; Read Data from Users; Declaring Variables and Assigning Values

Text of Note

Chapter 2: The Importance of Data Visualization in Business IntelligenceShifting from Input to Output; Why Is Data Visualization Important?; Why Do Modern Businesses Need Data Visualization?; The Future of Data Visualization; How Data Visualization Is Used for Business Decision-Making; Faster Responses; Simplicity; Easier Pattern Visualization; Team Involvement; Unify Interpretation; Introducing Data Visualization Techniques; Loading Libraries; Popular Libraries for Data Visualization in Python; Matplotlib; Seaborn; Plotly; Geoplotlib; Pandas; Introducing Plots in Python; Summary

Text of Note

Exercises and AnswersChapter 3: Data Collection Structures; Lists; Creating Lists; Accessing Values in Lists; Adding and Updating Lists; Deleting List Elements; Basic List Operations; Indexing, Slicing, and Matrices; Built-in List Functions and Methods; List Functions; List Methods; List Sorting and Traversing; Lists and Strings; Parsing Lines; Aliasing; Dictionaries; Creating Dictionaries; Updating and Accessing Values in Dictionaries; Deleting Dictionary Elements; Built-in Dictionary Functions; Built-in Dictionary Methods; Tuples; Creating Tuples; Concatenating Tuples

Text of Note

Multiple AssignsVariable Names and Keywords; Statements and Expressions; Basic Operators in Python; Arithmetic Operators; Relational Operators; Assign Operators; Logical Operators; Python Comments; Formatting Strings; Conversion Types; The Replacement Field, {}; The Date and Time Module; Time Module Methods; Python Calendar Module; Fundamental Python Programming Techniques; Selection Statements; Iteration Statements; The Use of Break, Continues, and Pass Statements; try and except; String Processing; String Special Operators; String Slicing and Concatenation

Text of Note

String Conversions and Formatting SymbolsLoop Through String; Python String Functions and Methods; The in Operator; Parsing and Extracting Strings; Tabular Data and Data Formats; Python Pandas Data Science Library; A Pandas Series; A Pandas Data Frame; A Pandas Panels; Python Lambdas and the Numpy Library; The map() Function; The filter() Function; The reduce () Function; Python Numpy Package; Data Cleaning and Manipulation Techniques; Abstraction of the Series and Data Frame; Running Basic Inferential Analyses; Summary; Exercises and Answers

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Text of Note

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.--Provided by publisher.

Source for Acquisition/Subscription Address

Springer Nature

Stock Number

com.springer.onix.9781484241097

Title

Data analysis and visualization using Python.

International Standard Book Number

9781484241080

Data mining.

Programming languages (Electronic computers)

Python (Computer program language)

Qualitative research-- Methodology.

Computer programming-- software development.

COMPUTERS-- Programming Languages-- Python.

Data mining.

Databases.

Programming & scripting languages: general.

Programming languages (Electronic computers)

Python (Computer program language)

Qualitative research-- Methodology.

COM-- 051360

UMX

UMX

Number

Edition

Class number

Book number

Embarak, Ossama

Date of Transaction

20200823032530.0

Cataloguing Rules (Descriptive Conventions))

pn

Electronic name

[Book]

Y