corrections

Author: Xuemeng

index.Rmd

@@ -32,7 +32,7 @@ code[class^="sourceCode bash"]::before { content: "Bash Source"; }
 
 # Python Programing
 
-In the previous tutorial, we learned how to set up virtual environments to write and run python code. In today's tutorial, we will start using these environments in VS Code, which will serve as our default IDE. If you’re more comfortable with a different IDE, feel free to use it instead. Next week we will work with spatial data analysis which more often than not results in data being displayed on a map. 
+In the previous tutorial, we learned how to set up virtual environments to write and run python code. In today's tutorial, we will start using these environments in VS Code, which will serve as our default IDE. Next week we will work with spatial data analysis which more often than not results in data being displayed on a map. 
 
 During this tutorial, we will demonstrate different ways to visualize data on a map in both static and interactive formats. This can be done using several open source packages that built upon each other. To understand the functionality of these packages and how they can be integrated, we will refer to the concepts of Object Oriented Programming (OOP). Object Oriented Programming is a way of programming where objects are fundamental building blocks that supports code modularity and reusability. Since OOP is commonly used in the development of open source packages, we can reuse and adapt already developed code and its functionality. Therefore, before we go into the visualization part of this tutorial we will begin by explaining Object Oriented Programming. 
 
@@ -56,7 +56,7 @@ dependencies:
   - matplotlib
 ```
 
-In the terminal of VS Code, create the environment using `mamba env create --file env.yaml`. Then activate this environment using `source activate python-programming`. The select `python-programming` as interpreter, just as we did in the previous tutorial.
+In the terminal of VS Code, create the environment using `mamba env create --file env.yaml`. Then activate this environment using `source activate python-programming`. Then select `python-programming` as interpreter, just as we did in the previous tutorial.
 
 <!--# Python help (This content is already in Tutorial 8)
 

index.html

@@ -905,7 +905,7 @@
          <h4 class="author"><em>Arno Timmer, Jan Verbesselt, Jorge
 Mendes de Jesus, Aldo Bergsma, Johannes Eberenz, Dainius Masiliunas,
 David Swinkels, Judith Verstegen, Corné Vreugdenhil</em></h4>
-            <h4 class="date"><em>08 August, 2025</em></h4>
+            <h4 class="date"><em>22 August, 2025</em></h4>
 
 
 
@@ -951,9 +951,8 @@ <h1>Python Programing</h1>
 <p>In the previous tutorial, we learned how to set up virtual
 environments to write and run python code. In today’s tutorial, we will
 start using these environments in VS Code, which will serve as our
-default IDE. If you’re more comfortable with a different IDE, feel free
-to use it instead. Next week we will work with spatial data analysis
-which more often than not results in data being displayed on a map.</p>
+default IDE. Next week we will work with spatial data analysis which
+more often than not results in data being displayed on a map.</p>
 <p>During this tutorial, we will demonstrate different ways to visualize
 data on a map in both static and interactive formats. This can be done
 using several open source packages that built upon each other. To
@@ -991,7 +990,7 @@ <h2>Dependencies</h2>
   - matplotlib</code></pre>
 <p>In the terminal of VS Code, create the environment using
 <code>mamba env create --file env.yaml</code>. Then activate this
-environment using <code>source activate python-programming</code>. The
+environment using <code>source activate python-programming</code>. Then
 select <code>python-programming</code> as interpreter, just as we did in
 the previous tutorial.</p>
 <!--# Python help (This content is already in Tutorial 8)