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+++ b/README.md
@@ -9,7 +9,7 @@ and pairing with smart people at Hashrocket.
 
 For a steady stream of TILs, [sign up for my newsletter](https://tinyletter.com/jbranchaud).
 
-_916 TILs and counting..._
+_917 TILs and counting..._
 
 ---
 
@@ -521,6 +521,7 @@ _916 TILs and counting..._
 ### Python
 
 - [Access Instance Variables](python/access-instance-variables.md)
+- [Create A Dummy DataFrame In Pandas](python/create-a-dummy-dataframe-in-pandas.md)
 - [Test A Function With Pytest](python/test-a-function-with-pytest.md)
 
 ### Rails
diff --git a/python/create-a-dummy-dataframe-in-pandas.md b/python/create-a-dummy-dataframe-in-pandas.md
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+# Create A Dummy DataFrame In Pandas
+
+[Pandas](https://pandas.pydata.org/pandas-docs/stable/index.html) has all kinds
+of utilities for pulling in and processing tabular data. You can pull in a
+bunch of data from a SQL database into a `DataFrame`. This `DataFrame` object
+is then something you could pass around, process, and read from.
+
+When you are sketching out an implementation or writing some tests, it may not
+be feasible to read data from a DB. Instead, you can create a little dummy
+`DataFrame` using the
+[`from_dict`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.from_dict.html#pandas.DataFrame.from_dict)
+function.
+
+
+```python
+import pd
+
+data = {'pokemon': ['Charmander', 'Squirtle', 'Bulbasaur'], 'type': ['Fire', 'Water', 'Grass']}
+pd.DataFrame.from_dict(data)
+```
+
+This creates a two column `DataFrame` with a `pokemon` header and a `type`
+header. The two lists of value will be matched up positionally, so `squirtle`
+will be paired with `water`.