diff --git a/README.md b/README.md
index e505dbf..6e828d9 100644
--- a/README.md
+++ b/README.md
@@ -1,11 +1,43 @@
+[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/datastory-org/weekly-chart/master?urlpath=%2Flab%2Ftree%2Fnotebooks)
+
 # Datastory Weekly Chart
 This repository contains data and analysis for the [Datastory Weekly Charts](https://datastory.org/sv/veckans-graf) which are posted on Datastory.org and on social media.
 
+## Run the code in the cloud
+The Jupyter notebooks within this repository can be run using mybinder.org, just
+press the 'launch: binder' button above.
+
 ## Installation
+To work with the notebooks on your own computer, we recommend to [download and
+install Python as part of the anaconda
+distribution](https://www.anaconda.com/distribution/). That way, you get `git`
+to fetch the source code from this repository and Jupyter installed for you.
+
+To install the Python dependencies required for this project, do the following
+from a terminal or command prompt.
+
+```sh
+# get the content of this git repository
+git clone https://github.com/datastory-org/weekly-chart
+
+# enter the weekly-chart directory
+cd weekly-chart
+
+# install pipenv (https://pipenv.readthedocs.io)
+pip install pipenv
+
+# install the Python dependencies from the Pipfile
+pipenv install
+
+# enter the environment
+pipenv shell
 
-To run the notebooks, you need to install the packages listed in the `Pipfile`. The easiest way is to use [Pipenv](https://pipenv.readthedocs.io/en/latest/): `pipenv install`. This will install all dependencies as well as the local `src` package that contain some utility functions that are used in various notebooks.
+# start jupyter lab to work with the notebooks
+jupyter lab
+```
 
-An additional dependency (ImageMagick) is needed to generate GIFs. Please refer to the ImageMagick website for installation documentation.
+> **NOTE:** You also need [ImageMagick](https://imagemagick.org) to generate
+> GIFs, see their instructions on how to install it.
 
 ## Data
 Data is collected from a variety of sources. Each notebook contains a source reference and a date for when the data was originally obtained.
@@ -19,7 +51,7 @@ Data is collected from a variety of sources. Each notebook contains a source ref
 - **The Datastory Brand:** The Logo of Datastory and any other product names, trademarks or service marks are proprietary and are protected by applicable trademark and copyright laws. Nothing contained in this code base should be construed as granting any license or right to use any of the Datastory Marks without the express written permission of the owner of such Marks.
 
 ## Styling
-To create your own style, make a copy of the `assets/datastory.mplstyle` stylesheet to the location of your local matplotlib configuration directory (which can be found with `matplotlib.get_configdir()`). Assuming the config dir is located at `~/.matplotlib/`, move the stylesheet to `~/.matplotlib/stylelib/your-name.mplstyle`. Now you can use `plt.style.use("your-style")` to create custom styled charts.
+To adjust the style of the plots, modify `assets/datastory.mplstyle`.
 
 Unfortunately, some styling options are not customizable via stylesheets and have to be configured in code, which is what the `ds_plot` (in src/plot) function is for. Whenever possible, initialize your plots with the command `fig, ax = ds_plot()` and all basic styling should be set up appropriately.