Library Hours
Monday to Friday: 9 a.m. to 9 p.m.
Saturday: 9 a.m. to 5 p.m.
Sunday: 1 p.m. to 9 p.m.
Naper Blvd. 1 p.m. to 5 p.m.

LEADER 00000ngm a22003133i 4500 
003    LDC 
005    20221114203411.2 
006    m        c         
007    cr cna       a 
008    221114s2020    cau150        o   vleng d 
040    linkedin.com|beng 
099    Streaming Video LinkedIn Learning 
100 1  Vallisneri, Michele|espeaker. 
245 10 Python Data Analysis.|cwith Michele Vallisneri|h[LinkedIn 
       Learning electronic resource] 
264  1 Carpenteria, CA|blinkedin.com,|c2020. 
306    02h:30m:35s 
337    computer|2rdamedia 
338    online resource|2rdacarrier 
500    3/11/202012:00:00AM 
511 1  Presenter: Michele Vallisneri 
520    Interested in using Python for data analysis? Learn how to
       use Python, NumPy, and pandas together to analyze data 
       sets large and small. 
520    Data science is transforming the way that government and 
       industry leaders look at both specific problems and the 
       world at large. Curious about how data analysis actually 
       works in practice? In this course, instructor Michele 
       Vallisneri shows you how, explaining what it takes to get 
       started with data science using Python. Michele 
       demonstrates how to set up your analysis environment and 
       provides a refresher on the basics of working with data 
       structures in Python. Then, he jumps into the big stuff: 
       the power of arrays, indexing, and tables in NumPy and 
       pandas—two popular third-party packages designed 
       specifically for data analysis. He also walks through two 
       sample big-data projects: using NumPy to identify and 
       visualize weather patterns and using pandas to analyze the
       popularity of baby names over the last century. Challenges
       issued along the way help you practice what you've 
       learned. Note: This version of the course was updated to 
       reflect recent changes in Python 3, NumPy, and pandas. 
538    Latest version of the following browsers: Chrome, Safari, 
       Firefox, or Internet Explorer. Adobe Flash Player Plugin. 
       JavaScript and cookies must be enabled. A broadband 
       Internet connection. 
655  4 Instructional films.|2lcgft 
655  4 Educational films.|2lcgft 
710 2  linkedin.com (Firm) 
856 40 |uhttps://www.linkedin.com/learning/python-data-analysis-
       2?u=76281068&auth=true|zAvailable on LinkedIn Learning 
856 42 |3thumbnail|uhttps://cdn.lynda.com/course/2825705/2825705-
       1583515644004-16x9.jpg