Merge branch 'main' of https://github.com/bkamins/JuliaForDataAnalysis

README.md

@@ -2,20 +2,33 @@
 
 This repository contains source codes for the
 ["Julia for Data Analysis"](https://www.manning.com/books/julia-for-data-analysis?utm_source=bkamins&utm_medium=affiliate&utm_campaign=book_kaminski2_julia_3_17_22)
-book that is written by Bogumił Kamiński and is planned to be published in 2022
+book that has been written by Bogumił Kamiński and has been published by [Manning Publications Co.](https://www.manning.com/)
-by [Manning Publications Co.](https://www.manning.com/)
 
-Extras:
+## Contents
+
+* [Additional teaching materials](#additional-teaching-materials)
+* [Setting up your environment](#setting-up-your-environment)
+  * [General instructions](#general-instructions)
+  * [Note for Linux users](#note-for-linux-users)
+* [Organization of the code](#organization-of-the-code)
+* [Running the example codes](#running-the-example-codes)
+* [Accompanying materials](#accompanying-materials)
+* [Data used in the book](#data-used-in-the-book)
+* [Errata](#errata)
+
+## Additional teaching materials
 * in the `/exercises` folder for each book chapter you can find 10 additional
   exercises with solutions (they are meant for self study and are not discussed
   in the book)
 * in the `/lectures` folder for each book chapter you can find a Jupyter
   Notebook file with code from this chapter (note that the code is slightly
   adjusted in comparison to code contained in .jl files in the root folder
-  to accomodate it for running in Jupyter Notebook).
+  to accommodate it for running in Jupyter Notebook).
 
 ## Setting up your environment
 
+### General instructions
+
 In order to prepare the Julia environment before working with the materials
 presented in the book please perform the following setup steps:
 
@@ -140,3 +153,42 @@ They are respectively:
   <https://snap.stanford.edu/data/github-social.html> under GPL-3.0 License)
 * owensboro.zip (for chapter 13, available at The Stanford Open Policing Project
   under the Open Data Commons Attribution License)
+
+## Errata
+
+### Chapter 2, page 30
+
+I compare the following expressions:
+
+```
+x > 0 && println(x)
+```
+
+and
+
+```
+if x > 0
+    println(x)
+end
+```
+
+where `x = -7`.
+
+I write there that Julia interprets them both in the same way.
+It is true in terms of the fact that in both cases the `println` function is not called (and this is the focus point of the example).
+However, there is a difference in the value of these expressions.
+The first expression evaluates to `false`, while the second evaluates to `nothing`.
+
+Here is how you can check it:
+
+```
+julia> x = -7
+-7
+
+julia> show(x > 0 && println(x))
+false
+julia> show(if x > 0
+           println(x)
+       end)
+nothing
+```

exercises/README.md

@@ -19,7 +19,7 @@ purpose, require using more functionalities of Julia ecosystem that is covered
 in the book. This is meant to teach you how to use help and documentation,
 as this is a very important skill to master.
 
-The files containing exercises have a naming convention `execricesDD.md`, where
+The files containing exercises have a naming convention `exercisesDD.md`, where
 `DD` is book chapter number for which the exercises were prepared.
 
 All the exercises should be possible to solve using project environment setting

exercises/exercises02.md

@@ -64,7 +64,7 @@ and the error accumulates when we do addition multiple times.
 than rational 1/7 by increasing the precision of computations using the `big`
 function:
 ```
-julia> big(1/7) # convert Floa64 to high-precision float
+julia> big(1/7) # convert Float64 to high-precision float
 0.142857142857142849212692681248881854116916656494140625
 
 julia> 1/big(7) # construct high-precision float directly
@@ -187,7 +187,7 @@ Note the differences in the code:
 * if there are `0` or `1` element in the collection the function does not do
   anything (depending on the context we might want to throw an error instead)
 * in `x[begin], x[end] = x[end], x[begin]` we perform two assignments at the
-  same time to avoid having to use a temporaty variable `f` (this operation
+  same time to avoid having to use a temporary variable `f` (this operation
   is technically called tuple destructuring; we discuss it in later chapters of
   the book)
 

exercises/exercises04.md

@@ -302,7 +302,7 @@ julia> for i in 1:40
 20   18.100 μs (0 allocations: 0 bytes)
 ```
 
-Notice that execution time for number `n` is roughly sum of ececution times
+Notice that execution time for number `n` is roughly sum of execution times
 for numbers `n-1` and `n-2`.
 
 </details>

exercises/exercises07.md

@@ -9,11 +9,11 @@
 ### Exercise 1
 
 Random.org provides a service that returns random numbers. One of the ways
-how you can use it is by sending HTTP GET reguests. Here is an example request:
+how you can use it is by sending HTTP GET requests. Here is an example request:
 
 > https://www.random.org/integers/?num=10&min=1&max=6&col=1&base=10&format=plain&rnd=new
 
-If you want to understand all the parameters plese check their meaning
+If you want to understand all the parameters please check their meaning
 [here](https://www.random.org/clients/http/).
 
 For us it is enough that this request generates 10 random integers in the range

exercises/exercises14.md

@@ -385,7 +385,7 @@ plot([bar(string.(g.n), g.mv;
           yerror=(g.mv - g.lo95, g.hi95-g.mv)) for g in gdf]...)
 ```
 
-As expected error bandwidth gets smaller as `k` encreases.
+As expected error bandwidth gets smaller as `k` increases.
 Note that as `n` increases the estimated value tends to `1-exp(-1)`.
 
 </details>