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Jupyter for Data Science

You're reading from   Jupyter for Data Science Exploratory analysis, statistical modeling, machine learning, and data visualization with Jupyter

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Product type Paperback
Published in Oct 2017
Publisher Packt
ISBN-13 9781785880070
Length 242 pages
Edition 1st Edition
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Author (1):
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Dan Toomey Dan Toomey
Author Profile Icon Dan Toomey
Dan Toomey
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Toc

Table of Contents (11) Chapters Close

Preface 1. Jupyter and Data Science FREE CHAPTER 2. Working with Analytical Data on Jupyter 3. Data Visualization and Prediction 4. Data Mining and SQL Queries 5. R with Jupyter 6. Data Wrangling 7. Jupyter Dashboards 8. Statistical Modeling 9. Machine Learning Using Jupyter 10. Optimizing Jupyter Notebooks

Plotting using Plotly

Plotly is an interesting mix. It is a subscription website that provides significant data analysis graphing functionality. You can use the free version of the software, but you still need to log in with credentials to use it. The graphics functions are available in a variety of languages from Node.js to Python and the like.

Further, the graphics generated are available in Plotly and in your local notebook. If you mark the graphic as public, then you can access it from the notebook, just like any other graphic over the internet. Similarly, as a web graphic, you can select from the display and save locally as needed.

In this example, we use the voting histogram again, but using Plotly's capabilities.

The script becomes the following:

import plotly
import plotly.graph_objs as go
import plotly.plotly as py
import pandas as pd
import numpy as np

#once you...
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