updating week 4 notebook

.gitignore

@@ -1,3 +1,8 @@
 data/*
 figures/*
 notebooks/.ipynb_checkpoints/*
+.DS_Store
+.ipynb_checkpoints/
+notebooks/.DS_Store
+scatterplot.png
+

README.md

@@ -2,34 +2,33 @@
 
 ## Description
 
-Description: This four-week course is designed to introduce attendees to Python programming and its broad applications. 
-Each two hour session will include brief tutorials interspersed with challenge exercises, and assumes attendees have 
-no prior computer coding experience. At the end of this course, you will be able to use Python to import, manipulate, 
+Description: This four-week course is designed to introduce attendees to Python programming and its broad applications.
+Each two hour session will include brief tutorials interspersed with challenge exercises, and assumes attendees have
+no prior computer coding experience. At the end of this course, you will be able to use Python to import, manipulate,
 and visualize data.
 
-This repository is adapted from content originally appearing in 
+This repository is adapted from content originally appearing in
 [Python for Ecologists](https://datacarpentry.org/python-ecology-lesson/),
-Copyright (c) Data Carpentry. 
+Copyright (c) Data Carpentry.
 
 **Required software**: Software requirements for this course can be found on [fredhutch.io's Software page](http://www.fredhutch.io/software/#python). The HackMD (interactive page used for sharing links and information) for this course is here: https://hackmd.io/@k8hertweck/introPython
 
 ## Schedule
 
-* Week 1: Intro to python, jupyter notebooks, and data types
-* Week 2: Using pandas to explore data frames
-* Week 3: Extracting data from data frames
-* Week 4: Data visualization with ggplot
+* [Week 1](week1.py): Intro to python, jupyter notebooks, and data types
+* [Week 2](week2.py): Using pandas to explore data frames
+* [Week 3](week3.py): Extracting data from data frames
+* [Week 4](week4.ipynb): Data visualization with ggplot
 
 ## Resources
 
-* Each week's materials are described in the python script prefaced with the number of the week. 
+* Each week's materials are described in the Jupyter notebook prefaced with the number of the week.
 * Data used for this lesson are identical to that used in [Introduction to R](https://github.com/fredhutchio/R_intro);
-details on obtaining these data from the [National Cancer Institute's Genomic Data Commons](https://gdc.cancer.gov) 
+details on obtaining these data from the [National Cancer Institute's Genomic Data Commons](https://gdc.cancer.gov)
 can be found in that lesson repository.
-* `exercises/` includes a file for each week representing both the aggregated in-class exercises as well as additional 
+* [`exercises/`](exercises) includes a file for each week representing both the aggregated in-class exercises as well as additional
 supplemental exercises for practice
-* `solutions/` includes the solutions for all files in `exercises/`
-* `resources.md` includes useful links mentioned during lessons; additional information about continued learning in Python as 
-well as Hutch-specific resources can be found on the 
-[Data Science Wiki](https://sciwiki.fredhutch.org/bioinformatics/prog_overview/)
-* `hackmdio.md` is an archive of the [interactive webpage](https://hackmd.io) used during lessons
+* [`solutions/`](solutions/) includes the solutions for all files in `exercises/`
+* [`instructors.md`](instructors.md) includes information for instructors to facilitate teaching each lesson
+* [`hackmdio.md`](hackio.md) is an archive of the [interactive webpage](https://hackmd.io) used during lessons
+* Information about use of Python and Jupyter notebooks at Fred Hutch is available on the [Data Science Wiki](https://sciwiki.fredhutch.org/scicomputing/software_python/)