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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 2. NumPy Arrays FREE CHAPTER 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

Reading and writing JSON with Pandas


We can easily create a pandas Series from the JSON string in the previous example. The pandas read_json() function can create a pandas Series or pandas DataFrame.

The following example code can be found in ch-05.ipynb of this book's code bundle:

import pandas as pd 
 
json_str = '{"country":"Netherlands","dma_code":"0","timezone":"Europe\/Amsterdam","area_code":"0","ip":"46.19.37.108","asn":"AS196752","continent_code":"EU","isp":"Tilaa V.O.F.","longitude":5.75,"latitude":52.5,"country_code":"NL","country_code3":"NLD"}' 
 
data = pd.read_json(json_str, typ='series') 
print("Series\n", data) 
 
data["country"] = "Brazil" 
print("New Series\n", data.to_json()) 

We can either specify a JSON string or the path of a JSON file. Call the read_json() function to create a pandas Series from the JSON string in the previous example:

data = pd.read_json(json_str, typ='series') 
print("Series\n", data) 

In the resulting...

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