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210123 ||| eng |
| 050 |
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4 |
|a QA76.73.P98
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| 100 |
1 |
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|a Gerlanc, Daniel
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| 245 |
0 |
0 |
|a Programming with data
|b Python and Pandas : LiveLessons
|c Daniel Gerlanc
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| 260 |
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|a [Place of publication not identified]
|b Pearson
|c 2020
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| 300 |
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|a 1 streaming video file (4 hr., 1 min., 54 sec.)
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| 653 |
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|a Application program interfaces (Computer software) / http://id.loc.gov/authorities/subjects/sh98004527
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| 653 |
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|a Python (Computer program language) / http://id.loc.gov/authorities/subjects/sh96008834
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| 653 |
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|a APIs (interfaces) / aat
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| 653 |
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|a Application program interfaces (Computer software) / fast / (OCoLC)fst00811704
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| 653 |
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|a Visualisation de l'information
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| 653 |
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|a Information visualization / fast / (OCoLC)fst00973185
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| 653 |
|
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|a Interfaces de programmation d'applications
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| 653 |
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|a Electronic data processing / http://id.loc.gov/authorities/subjects/sh85042288
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| 653 |
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|a Electronic data processing / fast / (OCoLC)fst00906956
|
| 653 |
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|a Information visualization / http://id.loc.gov/authorities/subjects/sh2002000243
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| 653 |
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|a Python (Langage de programmation)
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| 653 |
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|a Python (Computer program language) / fast / (OCoLC)fst01084736
|
| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b OREILLY
|a O'Reilly
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| 490 |
0 |
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|a LiveLessons
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| 500 |
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|a Title from title screen (viewed July 20, 2020)
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| 856 |
4 |
0 |
|u https://learning.oreilly.com/videos/~/9780136623755/?ar
|x Verlag
|3 Volltext
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| 082 |
0 |
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|a 000
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| 520 |
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|a "In Programming with Data: Python and Pandas LiveLessons, data scientist Daniel Gerlanc prepares learners who have no experience working with tabular data to perform their own analysis. The video course focuses on both the distinguishing features of Pandas and the commonalities Pandas shares with other data analysis environments. In this LiveLesson, Dan starts by introducing univariate and multivariate data structures in Pandas and describes how to understand them both in the context of the Pandas framework and in relation to other libraries and environments for tabular data like R and relational databases. Next, Dan covers reading and writing to external file formats, split-apply-combine computations, introductory and advanced time series, and merging and reshaping datasets. After watching this video, Python programmers will gain a deep understanding of the Pandas framework through exposures to all of its APIs and feature sets."--Resource description page
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