Merge pull request #2 from catalyst-cooperative/add-read-in-lesson

Add WIP draft of diverse filetypes lesson

config.yaml

@@ -67,6 +67,7 @@ contact: '[email protected]'
 # Order of episodes in your lesson
 episodes: 
 - introduction.md
+- working-with-diverse-filetypes.md
 
 # Information for Learners
 learners: 

episodes/working-with-diverse-filetypes.md

@@ -0,0 +1,31 @@
+---
+title: "Handling diverse filetypes in Pandas"
+teaching: 0
+exercises: 0
+---
+
+:::::::::::::::::::::::::::::::::::::: questions 
+
+- How can I read in different tabular data types to a familiar format in Python?
+- What are some common errors that occur when importing data, and how can I troubleshoot them?
+
+::::::::::::::::::::::::::::::::::::::::::::::::
+
+::::::::::::::::::::::::::::::::::::: objectives
+
+- Import tabular data from XML, JSON, and Parquet formats to pandas dataframes using the `pandas` library
+- Import a table from a SQL database using the `pandas` library
+- Implement strategies to handle common errors on data import
+
+::::::::::::::::::::::::::::::::::::::::::::::::
+
+
+::::::::::::::::::::::::::::::::::::: keypoints 
+
+- `pandas` has functionality to read in many data formats (e.g., XML, JSON, SQL,
+Parquet) into the same kind of DataFrame in Python. We can take advantage of this to
+transform many kinds of data with similar functions in Python.
+- `pandas` accepts both relative and absolute file paths on read-in.
+
+::::::::::::::::::::::::::::::::::::::::::::::::
+