|
|
|
|
LEADER |
00000cgm a22000007i 4500 |
001 |
OR_on1325584614 |
003 |
OCoLC |
005 |
20231017213018.0 |
006 |
m o c |
007 |
vz czazuu |
007 |
cr cnannnuuuuu |
008 |
220606s2022 xx 229 o vleng d |
040 |
|
|
|a ORMDA
|b eng
|e rda
|e pn
|c ORMDA
|d ORMDA
|d OCLCF
|d OCLCO
|
020 |
|
|
|a 9781804614396
|q (electronic video)
|
020 |
|
|
|a 1804614394
|q (electronic video)
|
029 |
1 |
|
|a AU@
|b 000072055604
|
035 |
|
|
|a (OCoLC)1325584614
|
037 |
|
|
|a 9781804614396
|b O'Reilly Media
|
050 |
|
4 |
|a QA76.73.P98
|
082 |
0 |
4 |
|a 005.133
|2 23/eng/20220607
|
049 |
|
|
|a UAMI
|
245 |
0 |
0 |
|a Data manipulation in Python :
|b master Python, NumPy, and Pandas.
|
250 |
|
|
|a [First edition].
|
264 |
|
1 |
|a [Place of publication not identified] :
|b Packt Publishing,
|c [2022]
|
300 |
|
|
|a 1 online resource (1 video file (3 hr., 49 min.)) :
|b sound, color.
|
306 |
|
|
|a 034900
|
336 |
|
|
|a two-dimensional moving image
|b tdi
|2 rdacontent
|
337 |
|
|
|a computer
|b c
|2 rdamedia
|
338 |
|
|
|a online resource
|b cr
|2 rdacarrier
|
344 |
|
|
|a digital
|2 rdatr
|
347 |
|
|
|a video file
|2 rdaft
|
380 |
|
|
|a Instructional films
|2 lcgft
|
500 |
|
|
|a "Updated in May 2022."
|
500 |
|
|
|a "Meta Brains."
|
520 |
|
|
|a Master important data manipulation techniques for data science in Python by learning Python, NumPy, and Pandas About This Video Discover the basics of Python programming The most important Python libraries for data science Learn how to use Python to clean, visualize, and analyze data In Detail Data science is quickly becoming one of the most promising careers in the twenty-first century. It is automated, program-driven, and analytical. As a result, it's no surprise that the demand for data scientists has been expanding in the job market over the last few years. We will begin with a quick refresher on Python fundamentals for beginners in this course. This is optional; if you're already familiar with Python, skip to the next chapter. Data science will be the topic of the next three sections. We will start with the essential Python libraries for data science, then go on to the fundamental NumPy properties, and lastly begin with mathematics and how to use it in data science. You will learn about Python Pandas DataFrames and series after learning about data science. Following that, we will get down to business and begin data cleaning. Following that, we will learn how to use Python to visualize data and do data analysis on some sample datasets. Finally, we will cover the Time series in Python and learn how to work with and convert datasets to Time series. By the end of this course, you will be able to execute data manipulation for data science in Python with ease. Audience This course is open to students of all skill levels, and you will be able to succeed even if you have no prior programming or statistical knowledge.
|
588 |
0 |
|
|a Online resource; title from title details screen (O'Reilly, viewed June 6, 2022).
|
590 |
|
|
|a O'Reilly
|b O'Reilly Online Learning: Academic/Public Library Edition
|
650 |
|
0 |
|a Python (Computer program language)
|
650 |
|
0 |
|a Electronic data processing.
|
650 |
|
0 |
|a Programming languages (Electronic computers)
|
650 |
|
6 |
|a Python (Langage de programmation)
|
650 |
|
7 |
|a Electronic data processing
|2 fast
|
650 |
|
7 |
|a Programming languages (Electronic computers)
|2 fast
|
650 |
|
7 |
|a Python (Computer program language)
|2 fast
|
655 |
|
7 |
|a Instructional films
|2 fast
|
655 |
|
7 |
|a Internet videos
|2 fast
|
655 |
|
7 |
|a Nonfiction films
|2 fast
|
655 |
|
7 |
|a Instructional films.
|2 lcgft
|
655 |
|
7 |
|a Nonfiction films.
|2 lcgft
|
655 |
|
7 |
|a Internet videos.
|2 lcgft
|
655 |
|
7 |
|a Films de formation.
|2 rvmgf
|
655 |
|
7 |
|a Films autres que de fiction.
|2 rvmgf
|
655 |
|
7 |
|a Vidéos sur Internet.
|2 rvmgf
|
710 |
2 |
|
|a Packt Publishing,
|e publisher.
|
856 |
4 |
0 |
|u https://learning.oreilly.com/videos/~/9781804614396/?ar
|z Texto completo (Requiere registro previo con correo institucional)
|
994 |
|
|
|a 92
|b IZTAP
|