differences for PR #650

Author: actions-user

01-run-quit.md

@@ -188,8 +188,6 @@ The main work area in JupyterLab enables you to arrange documents (notebooks, te
 and other activities (terminals, code consoles, etc.) into panels of tabs that can be resized or
 subdivided. A screenshot of the default Main Work Area is provided below.
 
-If you do not see the Launcher tab, click the blue plus sign under the "File" and "Edit" menus and it will appear.
-
 <p align='center'>   <img alt="JupyterLab Main Work Area" src="fig/0_jupyterlab_main_work_area.png" width="750"/>
 </p>
 

09-plotting.md

@@ -348,14 +348,22 @@ matplotlib will make this  variable refer to a new empty figure.
 Therefore, make sure you call `plt.savefig` before the plot is displayed to
 the screen, otherwise you may find a file with an empty plot.
 
+Sometimes, some elements of the figure may get truncated when saving the figure to a file. You can find an in-depth explanation why this happens [here](https://matplotlib.org/stable/tutorials/intermediate/tight_layout_guide.html). To avoid this, we can call `plt.tight_layout` before `plt.savefig` to make sure that everything fits into the figure area.
+
+```python
+plt.tight_layout()
+plt.savefig('my_figure.png')
+```
+
 When using dataframes, data is often generated and plotted to screen in one line.
 In addition to using `plt.savefig`, we can save a reference to the current figure
-in a local variable (with `plt.gcf`) and call the `savefig` class method from
+in a local variable (with `plt.gcf`) and call the `tight_layout` and `savefig` class method from
 that variable to save the figure to file.
 
 ```python
 data.plot(kind='bar')
 fig = plt.gcf() # get current figure
+fig.tight_layout()
 fig.savefig('my_figure.png')
 ```
 

md5sum.txt

@@ -4,15 +4,15 @@
 "config.yaml" "4c8c3b66083d754c51eae2c277d24ca0" "site/built/config.yaml" "2023-05-02"
 "index.md" "f019634aead94a6e24c7b0a414239caa" "site/built/index.md" "2023-05-03"
 "links.md" "fd719a41381bb145880b9220d70edec3" "site/built/links.md" "2023-05-03"
-"episodes/01-run-quit.md" "8503041b7590fbc507249282d847cba6" "site/built/01-run-quit.md" "2023-06-07"
+"episodes/01-run-quit.md" "29913e0b8a59c867135ac9f1a2b59e56" "site/built/01-run-quit.md" "2023-06-07"
 "episodes/02-variables.md" "9dacd8cd9968b5d0185f0c244a55eb84" "site/built/02-variables.md" "2023-05-02"
 "episodes/03-types-conversion.md" "9e3a08116a2124cd8e23d1d7c5dba432" "site/built/03-types-conversion.md" "2023-05-02"
 "episodes/04-built-in.md" "d3ea4aa2a49667b61cb21a62034c88c6" "site/built/04-built-in.md" "2023-05-02"
 "episodes/05-coffee.md" "c7616ec40b9e611c47b2bac1e11c47d2" "site/built/05-coffee.md" "2023-05-02"
 "episodes/06-libraries.md" "96899c58843e51f10eb84a8ac20ebb90" "site/built/06-libraries.md" "2023-05-02"
 "episodes/07-reading-tabular.md" "b5b65e50037a583dfc5a3a879e4404b0" "site/built/07-reading-tabular.md" "2023-05-02"
 "episodes/08-data-frames.md" "d1e90ca9269672f6ef02019d4238636a" "site/built/08-data-frames.md" "2023-06-05"
-"episodes/09-plotting.md" "fca733c5f699e089feebdab0dac2b5b3" "site/built/09-plotting.md" "2023-05-02"
+"episodes/09-plotting.md" "c83cc9614b5e6de53ff98c5091d4977b" "site/built/09-plotting.md" "2023-06-07"
 "episodes/10-lunch.md" "0624bfa89e628df443070e8c44271b33" "site/built/10-lunch.md" "2023-05-02"
 "episodes/11-lists.md" "ff1bb5ec301422cf8a4cad6c6429bf4f" "site/built/11-lists.md" "2023-05-02"
 "episodes/12-for-loops.md" "1da6e4e57a25f8d4fd64802c2eb682c4" "site/built/12-for-loops.md" "2023-05-02"