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Hands-On Data Science with Anaconda

You're reading from   Hands-On Data Science with Anaconda Utilize the right mix of tools to create high-performance data science applications

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Product type Paperback
Published in May 2018
Publisher Packt
ISBN-13 9781788831192
Length 364 pages
Edition 1st Edition
Languages
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Authors (2):
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James Yan James Yan
Author Profile Icon James Yan
James Yan
Yuxing Yan Yuxing Yan
Author Profile Icon Yuxing Yan
Yuxing Yan
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Table of Contents (15) Chapters Close

Preface 1. Ecosystem of Anaconda 2. Anaconda Installation FREE CHAPTER 3. Data Basics 4. Data Visualization 5. Statistical Modeling in Anaconda 6. Managing Packages 7. Optimization in Anaconda 8. Unsupervised Learning in Anaconda 9. Supervised Learning in Anaconda 10. Predictive Data Analytics – Modeling and Validation 11. Anaconda Cloud 12. Distributed Computing, Parallel Computing, and HPCC 13. References 14. Other Books You May Enjoy

Introduction to the cbsodata Python package

To install the cbsodata Python package, perform the following steps:

  1. We can use one of the following commands:
conda install cbsodata 
pip install cbsodata 

For more detailed instructions about how to install the Python package, please see Chapter 6, Managing Packages:

  1. The next program shows one example of using the package:
import pandas as pd 
import cbsodata as cb 
name='82070ENG' 
data = pd.DataFrame(cb.get_data(name)) 
print(data.head()) 
info=cb.get_info(name) 
print(info['Title']) 
  1. The corresponding output is shown in the following screenshot:

The last line in the screenshot gives the name of the dataset. In the previous example, we used the dataset with the name 82070ENG.

  1. To find out all the names of lists, we use the get_table_list() function; see the following code:
import cbsodata as cb 
list=cb...
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