/sqlite_database_operations

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sqlite_database_operations

Assignment

  • Course: HHA 504
  • Homework assignment #3: Introduction to the world of databases, starting with SQLite. Integrate data processing with Python, utilize Pandas for exploratory data analysis, and conduct database operations using SQLite.

Summary of the assignment

1. Details on the datasets:

  • Used datasets from New York Presbyterian Hospital and St. Joseph Hospital. The datasets contain information about standard pricing for hospital services.

2. Data analysis process:

  • Conducted summary statistics for both datasets. For the columns with numerical data, I calculated the count, mean, minimum, maximum, standard deviation, and quartiles. For the columns with catergorical data, I calculated the count, frequency, top data, and unique data.
  • Created histograms for both datasets. For the New York Presbyterian Hospital dataset, I specifically looked at the "minimum negotiated charges" column. For the St. Joseph Hospital dataset, I specifically looked at the "package size" column.

Steps to replicate my assignment

1. Import the following:

  • Import SQLite: import sqlite3.
  • Import create_engine: from sqlalchemy import create_engine.

2. Create the following:

  • Create a connection object using sqlite3.connect(<'name of database'>).
  • Create a cursor object using .cursor().
  • Create a new table with columns using the SQL command CREATE TABLE <name of table>. Then, execute it using execute(). Make sure to commit the changes using .commit().
  • Create and insert new rows with data into the table using the SQL command INSERT INTO <name of table>. Then, execute it using execute(). Make sure to commit the changes using .commit()
  • Turn the table into a pandas dataframe using pd.read_sql().

3. Close the following:

  • Close the connection and cursor using .close(). For more details about the code click here