#!/usr/bin/env python
# coding: utf-8

# # FHIR for Research Workshop

# ## Exercise 1 

# Intro: see https://github.com/NIH-NCPI/fhir-101/blob/master/FHIR%20101%20-%20Practical%20Guide.ipynb as a great example
# 
# ## What is this notebook?
# 
# (common overview of the FHIR Training)
# 
# (overview of this specific notebook)
# 
# 
# 
# 
# ### Icons in this Guide
#  📘 A link to a useful external reference related to the section the icon appears in  
# 
#  ⚡️ A key takeaway for the section that this icon appears in  
# 
#  🖐 A hands-on section where you will code something or interact with the server  
# 
# 
# (any required MITRE legalese should either go here or at the very bottom of the notebook)

# ## Motivation / Purpose

# ## Scenario
# 
# (this section describes the specifics of the use case: what is the problem statement, what is the basic approach we are going to take, etc)
# 

# ## Initial Setup

# In[ ]:


# import any required libraries here.
#  - requests
#  - fhirclient: https://github.com/smart-on-fhir/client-py
#  - Pandas - DataFrames
#  - NumPy - basic data analysis
#  - matplotlib
#  - maybe seaborn for viz on top of matplotlib ?


# ## Step 1 Connect to Client

# sync to source server for data extraction

# In[ ]:





# ## Step 2 Query Data

# Submit query to source and retreive data. Save it locally

# In[ ]:





# ## Step 3 Mount Data onto Pandas Dataframe

# Take FHIR formatted data and convert it to a pandas dataframe for subsequent analysis.

# This resource seems like a good one! https://github.com/dermatologist/fhiry

# In[ ]:





# ## Step 4 Exploratory Data Analysis 

# Conduct some limited, EDA for demonstration purposes.

# In[ ]:





# ## Summary
# 
# (A review of what was done in this notebook, possibly reinforcing how this kind of use case could be useful in the real world)