update 2021

Author: trayc7

.gitignore

@@ -5,3 +5,4 @@
 .sass-cache
 __pycache__
 _site
+.jekyll-cache

_config.yml

@@ -6,7 +6,7 @@
 carpentry: "swc"
 
 # Overall title for pages.
-title: "EEOB/BCB 546X: Programming with Python"
+title: "EEOB/BCB 546: Programming with Python"
 
 # Contact email address.
 email: trayc7@gmail.com
@@ -24,7 +24,7 @@ repository: <USERNAME>/<PROJECT>
 
 # Sites.
 amy_site: "https://amy.software-carpentry.org/workshops"
-bcb_site: "http://eeob-biodata.github.io/BCB546X-Spring2017"
+bcb_site: "https://eeob-biodata.github.io/EEOB-BCB-546/"
 dc_site: "http://datacarpentry.org"
 swc_github: "https://github.com/swcarpentry"
 swc_site: "https://software-carpentry.org"
@@ -37,8 +37,8 @@ workshop_site: "https://swcarpentry.github.io/workshop-template"
 training_site: "https://swcarpentry.github.io/instructor-training"
 
 # Surveys.
-pre_survey: "https://www.surveymonkey.com/r/swc_pre_workshop_v1?workshop_id="
-post_survey: "https://www.surveymonkey.com/r/swc_post_workshop_v1?workshop_id="
+# pre_survey: "https://www.surveymonkey.com/r/swc_pre_workshop_v1?workshop_id="
+# post_survey: "https://www.surveymonkey.com/r/swc_post_workshop_v1?workshop_id="
 
 # Start time in minutes (0 to be clock-independent, 540 to show a start at 09:00 am)
 start_time: 0

_episodes/01-intro.md

@@ -137,7 +137,7 @@ o
 >
 > Count the number of Gs in the sequence above using a `for` loop. What is the difference between Python (see above) and R (in solution below) implementations?
 >
-> > ## Solution
+<!-- > > ## Solution
 > > ~~~
 > > seq <- 'GACTTAATGGGCAATAGGCAAGCACTTGAAAAAGATGCCAACGACATGAAAACACAAGACAA'
 > > seq_split <- strsplit(seq, "")[[1]]
@@ -149,14 +149,14 @@ o
 > > }
 > > print(count)
 > > ~~~
-> {: .solution} 
+> {: .solution}  -->
 {: .challenge}
 
 > ## What is the simplest way to count the Gs?
 >
 > Count the number of Gs in the sequence above using either R or Python in a simpler way.
 >
-> > ## Python Solution
+<!-- > > ## Python Solution
 > > ~~~
 > > seq <- 'GACTTAATGGGCAATAGGCAAGCACTTGAAAAAGATGCCAACGACATGAAAACACAAGA'
 > > print(seq.count('G'))
@@ -170,7 +170,7 @@ o
 > > library(stringr)
 > > str_count(seq,'G')
 > > ~~~
-> {: .solution}
+> {: .solution} -->
 {: .challenge}
 
 There are a lot of blogs and articles comparing R and Python. Many of these comparisons (like this [infographic](https://www.datacamp.com/community/tutorials/r-or-python-for-data-analysis#gs.3P0PoiY)) do not tell you which is "better". That's because this is up to you. It really depends on what you're trying to do. Typically for a lot of bioinformatics projects, you will find yourself needing to know both. This is simply because many of the very useful tools for working with biological data are written in a variety of languages. Thus, it is up to the researcher to interact with them and develop cohesive pipelines for data curation and analysis.
@@ -187,8 +187,8 @@ You can run python in various tools. Perhaps the most straightforward is to use
 $ python
 ```
 ~~~
-Python 3.7.3 (default, Mar 27 2019, 16:54:48) 
-[Clang 4.0.1 (tags/RELEASE_401/final)] :: Anaconda, Inc. on darwin
+Python 3.8.5 (default, Sep  4 2020, 02:22:02) 
+[Clang 10.0.0 ] :: Anaconda, Inc. on darwin
 Type "help", "copyright", "credits" or "license" for more information.
 >>>
 ~~~
@@ -253,21 +253,21 @@ HELLO
 
 ### Python on the Cluster
 
-Our HPC systems do not use the Anaconda install of Python. Additionally, the default versions of Python that is available globally is Python 2.7. Thus, if you would like to use HPC-Class to interact with Python, you will have to load the Python 3 module after logging on to the cluster (`ssh <ISU Net ID>@hpc-class.its.iastate.edu`).
+Our HPC systems do not use the Anaconda install of Python. Additionally, the default versions of Python that is available globally is Python 2.7. Thus, if you would like to use HPC-Class to interact with Python, it is recommended that you load the Python 3 module after logging on to the cluster (`ssh <ISU Net ID>@hpc-class.its.iastate.edu`).
 
 ```
-$ module load python/3.6.5-fwk5uaj
+$ module load python
 ```
 
 Once you have loaded the Python 3 module, you can open the `python3` interpreter:
 
 ```
-$ python3
+$ python
 ```
 
 ~~~
-Python 3.6.5 (default, May 29 2018, 16:28:47)
-[GCC 4.8.5 20150623 (Red Hat 4.8.5-28)] on linux
+Python 3.7.7 (default, Jun 15 2020, 12:59:09) 
+[GCC 4.8.5 20150623 (Red Hat 4.8.5-36)] on linux
 Type "help", "copyright", "credits" or "license" for more information.
 >>>
 ~~~
@@ -339,8 +339,8 @@ Each cell in a Jupyter notebook can be executed and you can choose the type of c
 >
 > Replicate one of the solutions give above in a Jupyter notebook. Add some Markdown text to describe your program.
 >
-> > ## Solution
+<!-- > > ## Solution
 > >
 > > ![jupyter browser](../fig/jupyter3.png)
-> {: .solution}
+> {: .solution} -->
 {: .challenge}

_episodes/02-datatypes.md

@@ -179,7 +179,7 @@ my_list = [0,1,2]
 >
 > Change the value of a single element in `my_list ` and `my_tuple`.
 >
-> > ## Solution: List
+<!-- > > ## Solution: List
 > >
 > > ~~~
 > > my_list[1] = 5
@@ -206,7 +206,7 @@ my_list = [0,1,2]
 > >TypeError: 'tuple' object does not support item assignment
 > > ~~~
 > > {: .output}
-> {: .solution}
+> {: .solution} -->
 {: .challenge}
 
 ### Assigning Elements of a List or Tuple to New Variables
@@ -393,7 +393,7 @@ for key in numbers2:
 >
 > Try to reassign the second value of `numbers2` (in the *key value pair*) so that it no longer reads "two" but instead reads "spam and eggs". What does your dictionary look like after you make this change?
 >
-> > ## Solution
+<!-- > > ## Solution
 > >
 > > ~~~
 > > numbers2[2] = 'spam and eggs'
@@ -405,7 +405,7 @@ for key in numbers2:
 > >{1: 'one', 2: 'spam and eggs', 3: 'three', 4: 'four'}
 > > ~~~
 > > {: .output}
-> {: .solution}
+> {: .solution} -->
 {: .challenge}
 
 It is important to note that dictionaries in Python 3.6 or greater are insertion _ordered_ and preserve the

_includes/lesson_footer.html

@@ -2,7 +2,7 @@
   <div class="row">
     <div class="col-md-6" align="left">
       <h5>
-	Content adapted by T. Heath; Copyright &copy; 2018 <a href="{{ site.dc_site }}">Data Carpentry</a> & <a href="{{ site.swc_site }}">Software Carpentry</a>
+	Content adapted by T. Heath; Copyright &copy; 2021 <a href="{{ site.dc_site }}">Data Carpentry</a> & <a href="{{ site.swc_site }}">Software Carpentry</a>
 <!-- 
 	{% if site.carpentry == "swc" %}<a href="{{ site.swc_site }}">Software Carpentry Foundation</a>{% endif %}
 	{% if site.carpentry == "dc" %}<a href="{{ site.dc_site }}">Data Carpentry</a>{% endif %}

fig/jupyter2.png

@@ -5,7 +5,7 @@ root: .
 
 # Welcome to the Python part of the BCB546 course!
 
-The materials we will work through are a sample of the lessons created for [Data Carpentry](http://www.datacarpentry.org/python-ecology-lesson/00-short-introduction-to-Python/) and [Software Carpentry](http://swcarpentry.github.io/python-novice-inflammation). 
+The materials we will work through are a sample of the lessons created for [Data Carpentry](https://datacarpentry.org/python-ecology-lesson/) and [Software Carpentry](http://swcarpentry.github.io/python-novice-inflammation). 
 The goal of this section is to demonstrate the utility of Python for working with biological data. 
 
 ## Why Python?
@@ -36,7 +36,7 @@ More details about the files we'll use and where to download them are available
 {: .prereq}
 
 ### Getting Started
-To get started with installing Python, follow the directions given in the [Python section of the course Software page](https://eeob-biodata.github.io/EEOB-BCB-546X/software#python).
+To get started with installing Python, follow the directions given in the [Python section of the course Software page](https://eeob-biodata.github.io/EEOB-BCB-546/software#python).
 In addition to installing Python on your own computer, you will also need to download the data files used in the tutorials. Details for doing this are found in the [Setup](setup/) page.
 
 ### Format

index.md

@@ -8,19 +8,19 @@ You need to download some files to follow this lesson:
 
 1. Make a new folder in your Desktop (or anywhere else you like) called `python-bcb546`.
 2. Download the following files into this folder:
-    3. [surveys.csv](https://github.com/EEOB-BioData/BCB546X-Fall2019/raw/master/course-files/python/surveys.csv)
-    4. [species.csv](https://github.com/EEOB-BioData/BCB546X-Fall2019/raw/master/course-files/python/species.csv)
-    5. [surveys_complete.csv](https://github.com/EEOB-BioData/BCB546X-Fall2019/raw/master/course-files/python/surveys_complete.csv)
+    3. [surveys.csv](https://github.com/EEOB-BioData/BCB546-Spring2021/raw/main/course-files/python/surveys.csv)
+    4. [species.csv](https://github.com/EEOB-BioData/BCB546-Spring2021/raw/main/course-files/python/species.csv)
+    5. [surveys_complete.csv](https://github.com/EEOB-BioData/BCB546-Spring2021/raw/main/course-files/python/surveys_complete.csv)
 
-Or, you can pull from the [course repository](https://github.com/EEOB-BioData/BCB546X-Fall2019) and change to the directory containing the data files:
-1. `cd BCB546X-Fall2019`
-2. `git pull origin master`
+Or, you can pull from the [course repository](https://github.com/EEOB-BioData/BCB546-Spring2021) and change to the directory containing the data files:
+1. `cd BCB546-Spring2021`
+2. `git pull origin main`
 3. `cd course-files/python`
 
 
 Or if you haven't yet cloned the course repository:
-1. `git clone git@github.com:EEOB-BioData/BCB546X-Fall2019.git`
-2. `cd BCB546X-Fall2019/course-files/python`
+1. `git clone git@github.com:EEOB-BioData/BCB546-Spring2021.git`
+2. `cd BCB546-Spring2021/course-files/python`