remediate Ep10 plotting issue

include wget workaround

episodes/data-visualisation.md

@@ -20,7 +20,7 @@ exercises: 10
 
 :::::::::::::::::::::::::::::::::::::::::: spoiler
 
-## Setup instructions this session does not include Episode 7
+## Setup instructions if your Google Drive is not mounted
 
 You'll need to load the library `pandas` and make your google drive accessible:
 ```python
@@ -30,13 +30,40 @@ drive.mount('/content/drive')
 file_location = "drive/MyDrive/lc-python/"
 ```
 You'll need to grant Google all the permissions it requests to make your google drive accessible to Colab.
+:::::::::::::::::::::::::::::::::::::::::: spoiler
+
+### What if the files have not been copied to my Google Drive yet?
+
+We wanted you to know how to make files you have on your computer accessible for use in Colab and persist over time. To save time now, run `wget` to download files directly to the cloud:
+
+```bash
+!wget https://github.com/jlchang/cb-python-intro-lesson-template/raw/refs/heads/main/episodes/files/data.zip
+!unzip data.zip
+```
+```python
+file_location = ""
+```
+::::::::::::::::::::::::::::::::::::::::::::::::::
 ::::::::::::::::::::::::::::::::::::::::::::::::::
 
 For this module, we will use the tidy (long) version of our circulation data, where each variable forms a column, each observation forms a row, and each type of observation unit forms a row. If your workshop included the Tidy Data episode, you should be set and have an object called `df_long` in your Jupyter environment. If not, we’ll read that dataset in now, as it was provided for this lesson.
 
+:::::::::::::::::::::::::::::::::::::::::: spoiler
+## What version of `pandas` is Colab using?
+
+We can find out the version number of installed Python libraries with
+```bash
+!pip list
+```
+The output will be extensive but is sorted alphabetically. Look for the version number for `pandas`. If it is `2.2.2`, you'll need to:
+```bash
+!pip install pandas==2.3.3
+```
+there's a plotting bug in version `2.2.2`.
+::::::::::::::::::::::::::::::::::::::::::::::::::
 
 ``` python
-#import if it is already not
+#import if pandas is not already loaded
 import pandas as pd
 df_long = pd.read_pickle(file_location + 'data/df_long.pkl')
 ```

episodes/looping-data-sets.md

@@ -21,7 +21,7 @@ exercises: 10
 
 :::::::::::::::::::::::::::::::::::::::::: spoiler
 
-## Setup instructions this session does not include Episode 5
+## Setup instructions if your Google Drive is not mounted
 
 You'll need to load the library `pandas` and make your google drive accessible:
 ```python
@@ -31,6 +31,21 @@ drive.mount('/content/drive')
 file_location = "drive/MyDrive/lc-python/"
 ```
 You'll need to grant Google all the permissions it requests to make your google drive accessible to Colab.
+
+:::::::::::::::::::::::::::::::::::::::::: spoiler
+
+### What if the files have not been copied to my Google Drive yet?
+
+We wanted you to know how to make files you have on your computer accessible for use in Colab and persist over time. To save time now, run `wget` to download files directly to the cloud:
+
+```bash
+!wget https://github.com/jlchang/cb-python-intro-lesson-template/raw/refs/heads/main/episodes/files/data.zip
+!unzip data.zip
+```
+```python
+file_location = ""
+```
+::::::::::::::::::::::::::::::::::::::::::::::::::
 ::::::::::::::::::::::::::::::::::::::::::::::::::
 
 ## Use a `for` loop to process files given a list of their names.