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

# # The Costs and Revenues Associated With Running a Hospital - Parking
# 
# How much does it cost to run a hospital, and what revenue streams are available to hospitals to help them raise money at a local level?
# 
# The NHS [Estates Returns Information Collection (ERIC)](https://digital.nhs.uk/data-and-information/publications/statistical/estates-returns-information-collection/england-2018-19) seems to provide cost reports at local level and income reports at trust level.
# 
# 
# Data link via [Owen Boswarva](https://www.owenboswarva.com/).

# ## Data Preview

# In[2]:


import pandas as pd

url_trust = 'https://files.digital.nhs.uk/83/4AF81B/ERIC%20-%20201819%20-%20TrustData%20v4.csv'

df_trust = pd.read_csv(url_trust, encoding='latin1')
df_trust.columns = [c.strip() for c in df_trust.columns]
df_trust.head(3)


# ## Data By Commissioning Region - Lookup

# In[14]:


cols = ['Income from car parking - patients and visitors (£)', 'Income from car parking - staff (£)']

from ipywidgets import Dropdown, interact

region_widget = Dropdown(options = df_trust['New Commissioning Region'].unique())
trust_widget = Dropdown()

# Define a function that updates the content of y based on what we select for x
def update_trusts(*args):
    trust_widget.options = df_trust[df_trust['New Commissioning Region']==region_widget.value]['Trust Name'].unique()
    
region_widget.observe(update_trusts)

# Some function you want executed
def trust_report(region, trust):
    return df_trust[df_trust['Trust Name']==trust][['Trust Name']+cols]

interact(trust_report, region = region_widget, trust = trust_widget);


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