General tidying up of the lesson based on first run through at NTNU.
General themes of this pr:
Improve the setting up experience
Link directly to all the relevant data files, instead of to (a few) of their github pages. add some general advice about where to save it. Getting the data, and then having Python find it were both ubiquitous problems in a first round
Add correct requirements to setup
Tidy up left-over references to the python Ecology course that (I assume) this course was translated from
Remove references to ecology data (e.g. surveys_df) and concepts (e.g. searching data by species, etc)
Replace figures with those relevant to the eebo example dataset
Delete now-unused figures and data in the repo
Adjust challenges where needed to better suit the nature of the eebo data
Polish lesson content
Expand explanations where certain topics proved difficult during teaching
Split some of the more complex statements across multiple lines to make it easier for novices to appreciate the different components of a command
Improve consistency of instructions (e.g. keeping the same variable name across lessons)
Use consistent file path to data files. Currently, some used pd.read_csv("eebo.csv"), others used pd.read_csv("data/eebo.csv"), and others used pd.read_csv("../data/eebo.csv"). All were standardised on pd.read_csv("eebo.csv"), since students are generally not encouraged to clone the entire repository, but just to grab the data files they require.
Fixed typographic errors in some example code
Rewrite Instructor's Guide to apply to this course - it looks like it was overlooked during the initial translation
I have left one known point outstanding. Lesson 7 - Plotting with bokeh (06-visualization-ggplot-python) focuses strongly on visualisations suitable to timeseries data, which makes sense given the ecology background. However, with the focus on literary data, the lesson probably needs to be re-pointed to some extent. I don't have the time to think through how best to do it right now.
iaine
commented
3 years ago
General tidying up of the lesson based on first run through at NTNU.
General themes of this pr:
Improve the setting up experience
Tidy up left-over references to the python Ecology course that (I assume) this course was translated from
surveys_df) and concepts (e.g. searching data by species, etc)Polish lesson content
pd.read_csv("eebo.csv"), others usedpd.read_csv("data/eebo.csv"), and others usedpd.read_csv("../data/eebo.csv"). All were standardised onpd.read_csv("eebo.csv"), since students are generally not encouraged to clone the entire repository, but just to grab the data files they require.Rewrite Instructor's Guide to apply to this course - it looks like it was overlooked during the initial translation
I have left one known point outstanding. Lesson 7 - Plotting with bokeh (06-visualization-ggplot-python) focuses strongly on visualisations suitable to timeseries data, which makes sense given the ecology background. However, with the focus on literary data, the lesson probably needs to be re-pointed to some extent. I don't have the time to think through how best to do it right now.