diff --git a/website/_containers/dataviz/2013-01-03-part-2.md b/website/_containers/dataviz/2013-01-03-part-2.md
index dfdd1c47..66043a76 100644
--- a/website/_containers/dataviz/2013-01-03-part-2.md
+++ b/website/_containers/dataviz/2013-01-03-part-2.md
@@ -28,7 +28,7 @@ Graph our sample data with matplotlib.
 - We include the parse function here so we build on the process of parse → plot.  We need to parse the data into the list of dictionaries so that we can easily tell matplotlib what and how to plot. We could, however, imported it from `parse.py`. As a **challenge** to you, try editing away the parse function in `graph.py` and import it from your `parse.py`.
 
 ### Visualize Functions
-Let’s first take a look at a chuck of data that we just parsed to get a better idea of what sort of data we’re working with:
+Let’s first take a look at a chunk of data that we just parsed to get a better idea of what sort of data we’re working with:
 
 ```bash
 {
@@ -121,7 +121,7 @@ item["DayOfWeek"] for item in data_file
 This is called a list comprehension. You can read it as, “iterate every dictionary value of every dictionary key set to ‘DayOfWeek’ for every line item in `data_file`.” A list comprehension just a for-loop put in a more elegant, “Pythonic” way.
 
 <div class="well">
-<b>Challenge yourself:</b> write out a for-loop for our <code>counter</code> variable.
+<b>Challenge yourself:</b> Write out a for-loop for our <code>counter</code> variable.
 </div>
 
 
@@ -145,6 +145,10 @@ The counter object is a dictionary with the keys as days of the week, and values
 
 Here, `data_list` takes each key of `counter` to grab the value associated with each day.  Because we manually write out each `counter` key, we force the order that we want. **Note:** a dictionary does _not_ preserve order, but a list does; this is why we’re electing to manually key into each value of a dictionary to make a list of each value.
 
+<div class="well">
+<b>Challenge yourself:</b> Write out the <code>data_list</code> variable code as a list comprehension.
+</div>
+
 The `day_tuple` is just a tuple of strings that we will use for our x-axis labels.  **A quick note:** we had to make our `day_tuple` variable a tuple because `plt.xticks()` only accepts tuples for labeling the x-axis.  This is because tuples are an immutable type of data structure in Python’s library, meaning you can’t change it (not without making a copy of the variable onto a new variable), as well as it preserves order.
 
 We now tell `matplotlib` to use our `data_list` as data points to plot. The `pyplot` module, what we’ve renamed as `plt`, has a function called `plot()` which takes a list of data points to plot on the y-axis:
@@ -163,7 +167,7 @@ Just creating the variable `day_tuple` for our x-axis isn’t enough — we also
     plt.xticks(range(len(day_tuple)), day_tuple)
 ```
 
-We give `plt.xticks()` two parameters, one being a list and the other being our tuple, `labels`.
+We give `plt.xticks()` two parameters, one being a list and the other being our tuple, `day_tuple`.
 
 The first parameter is `range(len(day_tuple))`.  Here, we call `len()` on our `day_tuple` variable — `len()` returns an integer, a count of the number of items in our tuple `day_tuple`. Since we have seven items in our `day_tuple` (**pop quiz:** why do we have seven items?), the `len()` will return 7. Now we have `range()` on our length of the `day_tuple`. If you feed `range()` one parameter `x`, it will produce a list of integers from `0` to `x` (not including `x`). So, deconstructed, we fed `plt.xticks()` the following: