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Hands-On Big Data Modeling

You're reading from   Hands-On Big Data Modeling Effective database design techniques for data architects and business intelligence professionals

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Product type Paperback
Published in Nov 2018
Publisher Packt
ISBN-13 9781788620901
Length 306 pages
Edition 1st Edition
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Authors (3):
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James Lee James Lee
Author Profile Icon James Lee
James Lee
Tao Wei Tao Wei
Author Profile Icon Tao Wei
Tao Wei
Suresh Kumar Mukhiya Suresh Kumar Mukhiya
Author Profile Icon Suresh Kumar Mukhiya
Suresh Kumar Mukhiya
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Toc

Table of Contents (17) Chapters Close

Preface 1. Introduction to Big Data and Data Management 2. Data Modeling and Management Platforms FREE CHAPTER 3. Defining Data Models 4. Categorizing Data Models 5. Structures of Data Models 6. Modeling Structured Data 7. Modeling with Unstructured Data 8. Modeling with Streaming Data 9. Streaming Sensor Data 10. Concept and Approaches of Big-Data Management 11. DBMS to BDMS 12. Modeling Bitcoin Data Points with Python 13. Modeling Twitter Feeds Using Python 14. Modeling Weather Data Points with Python 15. Modeling IMDb Data Points with Python 16. Other Books You May Enjoy

Importing Twitter feed data

In this chapter, we are going to use the Twitter dataset. The dataset can be downloaded from Kaggle (https://www.kaggle.com/kingburrito666/better-donald-trump-tweets). In addition to that, you can find the dataset inside this book's GitHub repository. The dataset is found inside the CH13 folder. The file is called Donald-Tweets!.csv.

Let's dive into the exercise by running the Jupyter notebook we've been using throughout this book. Once you have the notebook up and running, import the required essential packages. Most of the Python packages should be very familiar by now:

from textblob import TextBlob
import math
import pandas as pd
import numpy as np
import os
from pandas import DataFrame
from sklearn.cluster import KMeans
from sklearn import preprocessing
import matplotlib.pyplot as plt
from matplotlib import style
import matplotlib.pyplot as...
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