The Resource Data Analysis and Visualization Using Python : Analyze Data to Create Visualizations for BI Systems, by Dr. Ossama Embarak, (electronic resource)

Data Analysis and Visualization Using Python : Analyze Data to Create Visualizations for BI Systems, by Dr. Ossama Embarak, (electronic resource)

Label
Data Analysis and Visualization Using Python : Analyze Data to Create Visualizations for BI Systems
Title
Data Analysis and Visualization Using Python
Title remainder
Analyze Data to Create Visualizations for BI Systems
Statement of responsibility
by Dr. Ossama Embarak
Creator
Contributor
Author
Author
Provider
Subject
Language
eng
Summary
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
http://library.link/vocab/creatorName
Embarak, Dr. Ossama
http://bibfra.me/vocab/relation/httpidlocgovvocabularyrelatorsaut
JLksJSUteUQ
Image bit depth
0
LC call number
QA76.73.P98
Literary form
non fiction
http://library.link/vocab/relatedWorkOrContributorName
SpringerLink
http://library.link/vocab/subjectName
  • Python (Computer program language)
  • Open source software
  • Computer programming
  • Big data
  • Python
  • Open Source
  • Big Data
Label
Data Analysis and Visualization Using Python : Analyze Data to Create Visualizations for BI Systems, by Dr. Ossama Embarak, (electronic resource)
Instantiates
Publication
Antecedent source
mixed
Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
Color
not applicable
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
Chapter 1: Introduction to data science with python -- Chapter 2: The importance of data visualization in business intelligence -- Chapter 3: Data collections structure -- Chapter 4: File I/O processing & Regular expressions -- Chapter 5: Data gathering and cleaning -- Chapter 6: Data exploring and analysis -- Chapter 7: Data visualization -- Chapter 8: Case Study
Dimensions
unknown
Extent
XX, 374 p. 267 illus.
File format
multiple file formats
Form of item
electronic
Isbn
9781484241097
Level of compression
uncompressed
Media category
computer
Media MARC source
rdamedia
Media type code
c
Other control number
10.1007/978-1-4842-4109-7
Other physical details
online resource.
Quality assurance targets
absent
Reformatting quality
access
Specific material designation
remote
System control number
(DE-He213)978-1-4842-4109-7
Label
Data Analysis and Visualization Using Python : Analyze Data to Create Visualizations for BI Systems, by Dr. Ossama Embarak, (electronic resource)
Publication
Antecedent source
mixed
Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
Color
not applicable
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
Chapter 1: Introduction to data science with python -- Chapter 2: The importance of data visualization in business intelligence -- Chapter 3: Data collections structure -- Chapter 4: File I/O processing & Regular expressions -- Chapter 5: Data gathering and cleaning -- Chapter 6: Data exploring and analysis -- Chapter 7: Data visualization -- Chapter 8: Case Study
Dimensions
unknown
Extent
XX, 374 p. 267 illus.
File format
multiple file formats
Form of item
electronic
Isbn
9781484241097
Level of compression
uncompressed
Media category
computer
Media MARC source
rdamedia
Media type code
c
Other control number
10.1007/978-1-4842-4109-7
Other physical details
online resource.
Quality assurance targets
absent
Reformatting quality
access
Specific material designation
remote
System control number
(DE-He213)978-1-4842-4109-7

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