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Python Data Analysis, Second Edition

You're reading from   Python Data Analysis, Second Edition Data manipulation and complex data analysis with Python

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Product type Paperback
Published in Mar 2017
Publisher Packt
ISBN-13 9781787127487
Length 330 pages
Edition 2nd Edition
Languages
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Author (1):
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Ivan Idris Ivan Idris
Author Profile Icon Ivan Idris
Ivan Idris
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Table of Contents (16) Chapters Close

Preface 1. Getting Started with Python Libraries FREE CHAPTER 2. NumPy Arrays 3. The Pandas Primer 4. Statistics and Linear Algebra 5. Retrieving, Processing, and Storing Data 6. Data Visualization 7. Signal Processing and Time Series 8. Working with Databases 9. Analyzing Textual Data and Social Media 10. Predictive Analytics and Machine Learning 11. Environments Outside the Python Ecosystem and Cloud Computing 12. Performance Tuning, Profiling, and Concurrency A. Key Concepts
B. Useful Functions C. Online Resources

Storing data in memcache


The memcache is an in-memory, key-value database store, just like Redis. After you install and run the memcached server, install the memcache Python client using the following command:

$ pip3 install python3-memcache

The code in the ch-08.ipynb file creates a memcache client and then stores the DataFrame to memcache with an auto-expire value of 600 seconds. The code is similar to the code for Redis:

import memcache 
import statsmodels.api as sm 
import pandas as pd 
 
client = memcache.Client([('127.0.0.1', 11211)]) 
data_loader = sm.datasets.sunspots.load_pandas() 
df = data_loader.data 
data = df.T.to_json() 
client.set('sunspots', data, time=600) 
print("Stored data to memcached, auto-expire after 600 seconds") 
blob = client.get('sunspots') 
print(pd.read_json(blob)) 
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