In this project I use SQL to perform EDA on this data and Seaborn is used for visualization.
We first load the ipython-sql library into the notebook. Then configure it to return pandas DataFrame and finally we connect to the mysql server.
#load sql library
%load_ext sql
#configure sql cell function to return pandas DataFrame.
%config SqlMagic.autopandas = True
#Connect to mysql server
%sql mysql+pymysql://root@localhost/
To load data to a database you can check the code in the notebook.
To query the database we just use sql magic function like below:
%%sql
Select *
FROM hospital_er
LIMIT 5
To store the query results to a variable that we can access for visualization:
df = %sql select monthname(date) as Month, \
count(patient_id) AS Count \
from hospital_er \
group by monthname(date) \
order by 1, 2 desc
To visualize the data e.g using seaborn alias sns:
sns.barplot(data=df, x='Month',y='Count')