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Jupyter Cookbook

You're reading from   Jupyter Cookbook Over 75 recipes to perform interactive computing across Python, R, Scala, Spark, JavaScript, and more

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Product type Paperback
Published in Apr 2018
Publisher Packt
ISBN-13 9781788839440
Length 238 pages
Edition 1st Edition
Languages
Tools
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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 (12) Chapters Close

Preface 1. Installation and Setting up the Environment 2. Adding an Engine FREE CHAPTER 3. Accessing and Retrieving Data 4. Visualizing Your Analytics 5. Working with Widgets 6. Jupyter Dashboards 7. Sharing Your Code 8. Multiuser Jupyter 9. Interacting with Big Data 10. Jupyter Security 11. Jupyter Labs

Generate an R lowess line graph


We can generate a lowess line on top of the Scatter diagram. The lowess line would likely show a better fit as smoothing is used to fit the line to the data.

How to do it...

We can use the same Scatter diagram as the basis and then call upon lines to add our lowess line:

# load the iris dataset
data <- read.csv("http://archive.ics.uci.edu/ml/machine-learning-databases/iris/iris.data")

#Let us also clean up the data so as to be more readable
colnames(data) <- c("sepal_length", "sepal_width", "petal_length", "petal_width", "species")

# call plot first
plot(data$sepal_length, data$petal_length)

# add the lowess line to the graph
lines(lowess(data$sepal_length, data$petal_length), col="blue")

Here is the resulting graph:

How it works...

Locally weighted scatterplot smoothing (LOWESS) is a useful mechanism when performing a regression to see a smoothed line drawn through our data. Once accomplished, you are likely to see relationships and possibly forecasts...

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