# Data & Charts to Answer Questions¶

Have cleaned the data, combined it together and done some exploratory analysis to answer the questions. Here is where I'll collate the answers and output the data ready for sending to the designers.

The questions Ineed to answer are below:

1. How have absence days due to stress/anxiety changed:
a. For all the services combined?
b. For each of the three services?
2. How has the number of absence episodes due to stress/anxiety changed:
a. For NBT/SWAS together?
b. For NBT/SWAS separately?
3. How has the average length of an anxiety episode changed (NBT & SWAS only)?
4. Which staff groups have the biggest rate of change (NBT & UHBT only)?
5. What are the top 5 absence reasons (excluding Maternity & other non-sickness absences) for NBT & SWAS?
6. What proportion of all sickness absences are due to stress & anxiety?
In [2]:
#Imports:
import pandas as pd
import plotly.offline as pyo
pyo.init_notebook_mode()

import nbformat
from nbconvert.preprocessors import ExecutePreprocessor