Language:
English
繁體中文
Help
圖資館首頁
Login
Back
Switch To:
Labeled
|
MARC Mode
|
ISBD
Data analysis and visualization usin...
~
Embarak, Ossama.
Data analysis and visualization using Pythonanalyze data to create visualizations for BI systems /
Record Type:
Electronic resources : Monograph/item
Title/Author:
Data analysis and visualization using Pythonby Dr. Ossama Embarak.
Reminder of title:
analyze data to create visualizations for BI systems /
Author:
Embarak, Ossama.
Published:
Berkeley, CA :Apress :2018.
Description:
xx, 374 p. :ill., digital ;24 cm.
Contained By:
Springer eBooks
Subject:
Python (Computer program language)
Online resource:
https://doi.org/10.1007/978-1-4842-4109-7
ISBN:
9781484241097$q(electronic bk.)
Data analysis and visualization using Pythonanalyze data to create visualizations for BI systems /
Embarak, Ossama.
Data analysis and visualization using Python
analyze data to create visualizations for BI systems /[electronic resource] :by Dr. Ossama Embarak. - Berkeley, CA :Apress :2018. - xx, 374 p. :ill., digital ;24 cm.
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.
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.
ISBN: 9781484241097$q(electronic bk.)
Standard No.: 10.1007/978-1-4842-4109-7doiSubjects--Topical Terms:
215247
Python (Computer program language)
LC Class. No.: QA76.73.P98
Dewey Class. No.: 005.133
Data analysis and visualization using Pythonanalyze data to create visualizations for BI systems /
LDR
:02902nmm a2200325 a 4500
001
547426
003
DE-He213
005
20181120151107.0
006
m d
007
cr nn 008maaau
008
190709s2018 cau s 0 eng d
020
$a
9781484241097$q(electronic bk.)
020
$a
9781484241080$q(paper)
024
7
$a
10.1007/978-1-4842-4109-7
$2
doi
035
$a
978-1-4842-4109-7
040
$a
GP
$c
GP
041
0
$a
eng
050
4
$a
QA76.73.P98
072
7
$a
UMX
$2
bicssc
072
7
$a
COM051360
$2
bisacsh
072
7
$a
UMX
$2
thema
082
0 4
$a
005.133
$2
23
090
$a
QA76.73.P98
$b
E53 2018
100
1
$a
Embarak, Ossama.
$3
826694
245
1 0
$a
Data analysis and visualization using Python
$h
[electronic resource] :
$b
analyze data to create visualizations for BI systems /
$c
by Dr. Ossama Embarak.
260
$a
Berkeley, CA :
$b
Apress :
$b
Imprint: Apress,
$c
2018.
300
$a
xx, 374 p. :
$b
ill., digital ;
$c
24 cm.
505
0
$a
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.
520
$a
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.
650
0
$a
Python (Computer program language)
$3
215247
650
0
$a
Programming languages (Electronic computers)
$3
184586
650
0
$a
Data mining.
$3
184440
650
0
$a
Qualitative research
$x
Methodology.
$3
220954
650
1 4
$a
Python.
$3
763308
650
2 4
$a
Open Source.
$3
758930
650
2 4
$a
Big Data.
$3
760530
710
2
$a
SpringerLink (Online service)
$3
273601
773
0
$t
Springer eBooks
856
4 0
$u
https://doi.org/10.1007/978-1-4842-4109-7
950
$a
Professional and Applied Computing (Springer-12059)
based on 0 review(s)
ALL
電子館藏
Items
1 records • Pages 1 •
1
Inventory Number
Location Name
Item Class
Material type
Call number
Usage Class
Loan Status
No. of reservations
Opac note
Attachments
000000163662
電子館藏
1圖書
電子書
EB QA76.73.P98 E53 2018 2018
一般使用(Normal)
On shelf
0
1 records • Pages 1 •
1
Multimedia
Multimedia file
https://doi.org/10.1007/978-1-4842-4109-7
Reviews
Add a review
and share your thoughts with other readers
Export
pickup library
Processing
...
Change password
Login