updates for conda forge

Author: chennesy

episodes/data-visualisation.md

@@ -141,15 +141,9 @@ albany['circulation'].plot(kind='hist', bins=20,
 ## Use Plotly for interactive plots 
 
 Let’s switch back to the full DataFrame in `df_long` and use another
-plotting package in Python called Plotly. First let’s install and then use the package.
+plotting package in Python called Plotly. 
 
 ```python
-# uncomment below to install plotly if the import fails. 
-# !pip install plotly
-
-# if you didn't install Jupyter via Anaconda, you may also need to install ipywidgets.
-# !pip install ipywidgets
-
 import plotly.express as px
 ```
 

episodes/getting-started.md

@@ -51,7 +51,7 @@ Here a few areas where you might apply Python in your work.
 
 ## Use JupyterLab to edit and run Python code.
 
-If you haven't already done so, see [the setup instructions](../learners/setup.md) for details on how to install JupyterLab and Python via Anaconda. The setup instructions also walk you through the steps you should follow to create an `lc-python` folder on your Desktop, and to download and unzip the dataset we'll be working with inside of that directory. 
+If you haven't already done so, see [the setup instructions](../learners/setup.md) for details on how to install JupyterLab and Python using Miniforge. The setup instructions also walk you through the steps you should follow to create an `lc-python` folder on your Desktop, and to download and unzip the dataset we'll be working with inside of that directory. 
 
 ### Getting started with JupyterLab
 To run Python, we are going to use Jupyter Notebooks via [JupyterLab][jupyterlab]. Jupyter notebooks are common tools for data science and visualization, and serve as a convenient environment for running Python code interactively where we can view and share the results of our Python code.
@@ -76,10 +76,15 @@ Once you have created the `lc-python` directory on your Desktop, you can start J
 #### Mac users - Command Line
 
 1. Press the <kbd>cmd</kbd> + <kbd>spacebar</kbd> keys and search for `Terminal`. Click the result or press <kbd>return</kbd>. (You can also find `Terminal` in your `Applications` folder, under `Utilities`.)
-2. After you have launched Terminal, change directories to the `lc-python` folder you created earlier and type `jupyter lab`. Note that the `$` sign is used to indicate a command to be typed on the command prompt, but we never type the `$` sign itself, just what follows after it.
+2. After you have launched Terminal, change directories to the `lc-python` folder you created earlier. 
+3. Next run `conda activate carpentries` to launch a Python environment which includes Jupyter Notebooks and other tools we will need to proceed through the lesson. 
+4. Finally, type `jupyter lab` which should open a browser window where you can run Jupyter Notebooks. 
+
+Note that the `$` sign is used to indicate a command to be typed on the command prompt, but we never type the `$` sign itself, just what follows after it.
 
 ```bash
 $ cd ../Desktop/lc-python
+$ conda activate carpentries
 $ jupyter lab
 ```
 
@@ -89,22 +94,15 @@ To start the JupyterLab server you will need to access the Anaconda Prompt.
 
 1. Press the <kbd>Windows Logo Key</kbd> and search for `Anaconda Prompt`, click the result or press enter.
 
-2. Once you have launched the Anaconda Prompt, type the command `jupyter lab`. Note that the `$` sign is used to indicate a command to be typed on the command prompt, but we never type the `$` sign itself, just what follows after it.
+2. Once you have launched the Anaconda Prompt, type the command `jupyter lab`. 
+
+Note that the `$` sign is used to indicate a command to be typed on the command prompt, but we never type the `$` sign itself, just what follows after it.
 
 ```bash
 $ cd ..\Desktop\lc-python
 $ jupyter lab
 ```
 
-#### Start JupyterLab from Anaconda Navigator
-If you are unfamiliar with the command line,  you can launch JupyterLab by opening the Anaconda Navigator app and choosing the `Launch` button underneath the JuypterLab icon. 
-
-First [start Anaconda Navigator (click for detailed instructions on macOS, Windows, and Linux)](https://docs.anaconda.com/free/navigator/getting-started/#navigator-starting-navigator). You can search for Anaconda Navigator via Spotlight on macOS (<kbd>Command</kbd> + <kbd>spacebar</kbd>), or by using the Windows search function (<kbd>Windows Logo Key</kbd>).
-
-After you have launched Anaconda Navigator, click the `Launch` button under JupyterLab. You may need to scroll down to find it. Here is a screenshot of an Anaconda Navigator page similar to the one that should open on either macOS or Windows.
-
-![Launch JupyterLab from Anaconda Navigator](../episodes/fig/0_anaconda_navigator_landing_page.png){alt='screenshot of the launch button for JuypterLab in Anaconda Navigator'}
-
 ## The JupyterLab Interface
 
 Launching JupyterLab opens a new tab or window in your preferred web browser. While JupyterLab enables you to run code from your browser, it does not require you to be online. If you take a look at the URL in your browser address bar, you should see that the environment is located at your localhost, meaning it is running from your computer: `http://localhost:8888/lab`.

index.md

@@ -19,7 +19,7 @@ This lesson is an introduction to programming in Python for library and informat
 
 2. Learners must install Python and JupyterLab, and download the dataset that will be used in the lesson, before the workshop begins.
 
-  Please see <a href="#installing-python-using-anaconda">setup instructions below</a> for details.
+  Please see <a href="#installing-python-using-miniforge">setup instructions below</a> for details.
 
 
 ::::::::::::::::::::::::::::::::::::::::::::::::::