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Python Data Analysis - Third Edition

You're reading from  Python Data Analysis - Third Edition

Product type Book
Published in Feb 2021
Publisher Packt
ISBN-13 9781789955248
Pages 478 pages
Edition 3rd Edition
Languages
Authors (2):
Avinash Navlani Avinash Navlani
Profile icon Avinash Navlani
Ivan Idris Ivan Idris
Profile icon Ivan Idris
View More author details
Toc

Table of Contents (20) Chapters close

Preface 1. Section 1: Foundation for Data Analysis
2. Getting Started with Python Libraries 3. NumPy and pandas 4. Statistics 5. Linear Algebra 6. Section 2: Exploratory Data Analysis and Data Cleaning
7. Data Visualization 8. Retrieving, Processing, and Storing Data 9. Cleaning Messy Data 10. Signal Processing and Time Series 11. Section 3: Deep Dive into Machine Learning
12. Supervised Learning - Regression Analysis 13. Supervised Learning - Classification Techniques 14. Unsupervised Learning - PCA and Clustering 15. Section 4: NLP, Image Analytics, and Parallel Computing
16. Analyzing Textual Data 17. Analyzing Image Data 18. Parallel Computing Using Dask 19. Other Books You May Enjoy

Dependency parsing

Dependency parsing finds the relationship among words – how words are related to each other. It helps computers to understand sentences for analysis; for example, "Taj Mahal is one of the most beautiful monuments." We can't understand this sentence just by analyzing words. We need to dig down and understand the word order, sentence structure, and parts of speech:

# Import spacy
import spacy

# Load English model for tokenizer, tagger, parser, and NER
nlp = spacy.load('en')

# Create nlp Object to handle linguistic annotations in a documents.
docs=nlp(sentence)

# Visualize the using render function
displacy.render(docs, style="dep", jupyter= True, options={'distance': 150})

This results in the following output:

In the preceding example, we have imported the display class and called its render() method with a NLP text object, style as 'dep', jupyter as True, and options as a dictionary with a distance key and a value...

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