Add a description

app.py

@@ -292,4 +292,62 @@ f.update_layout({
 })
 
 st.set_page_config(layout='wide')
-st.plotly_chart(f, use_container_width=True, theme=None)
+st.plotly_chart(f, use_container_width=True, theme=None)
+
+col1, col2, col3 = st.columns(3)
+col2.markdown("""
+# What is this?
+
+I want to challenge myself to make a visualization I'm proud of.
+
+If I ever find myself thinking
+> I could probably clean that up but ugh that would be annoying I don't wanna
+
+then I absolutely have to clean that up.
+
+That's about the end of my thought process.
+
+
+I've seen a few antitrust cases involving Big Tech companies in the news recently.
+Those articles make me curious how common antitrust cases are in general.
+
+How many does the DOJ file each month?
+Are the numbers pretty consistent or are there large swings?
+
+What does it look like?
+""")
+
+col2.markdown("""
+# The data
+
+To get the data, I went to [the website for the Antitrust Division of the U.S. Department of Justice](https://www.justice.gov/atr/antitrust-case-filings), clicked "Filter by Case Open Date" in the left menu, and clicked "Show more." That gave me a pretty clean list that I could highlight and copy.
+
+```
+June 2023 (2)
+
+April 2023 (1)
+
+March 2023 (1)
+
+February 2023 (2)
+
+January 2023 (5)
+
+2023 (11)
+
+November 2022 (4)
+[ . . . ]
+```
+
+There are some obvious problems with this data.
+For example, I found [a Wikipedia article about U.S. antitrust law](https://en.wikipedia.org/wiki/United_States_antitrust_law).
+That page refers to a case that happened in 1943, but my data doesn't have any cases in 1943.
+My best guess is that this data only includes records the DOJ has digitized and made available on their website.
+
+There's also at least one typo in this random menu on the DOJ's website.
+For the annual count of all cases opened in 2022, they list the correct amount but they label it "2026" instead.
+I didn't notice any other typos.
+I'm sure there are a few I missed.              
+
+As I said above, I just want to turn some data into a pretty plot.
+""")