readme

Author: toddbirchard

.DS_Store

@@ -102,3 +102,5 @@ venv.bak/
 
 # mypy
 .mypy_cache/
+
+.DS_Store

.gitignore

@@ -5,6 +5,8 @@
 ![SQLAlchemy](https://img.shields.io/badge/SQLAlchemy-1.3.6-red.svg?longCache=true&style=flat-square&logo=scala&logoColor=white&colorA=4c566a&colorB=bf616a)
 ![Psycopg2-Binary](https://img.shields.io/badge/Psycopg2--Binary-v2.7.7-red.svg?longCache=true&style=flat-square&logo=PostgreSQL&logoColor=white&colorA=4c566a&colorB=bf616a)
 ![GitHub Last Commit](https://img.shields.io/github/last-commit/google/skia.svg?style=flat-square&colorA=4c566a&colorB=a3be8c)
-[![GitHub Issues](https://img.shields.io/github/issues/toddbirchard/pandas-sqlalchemy-tutorial.svg?style=flat-square&colorA=4c566a&colorB=ebcb8b)](https://github.com/toddbirchard/googlecloud-storage-tutorial/issues)
-[![GitHub Stars](https://img.shields.io/github/stars/toddbirchard/pandas-sqlalchemy-tutorial.svg?style=flat-square&colorB=ebcb8b&colorA=4c566a)](https://github.com/toddbirchard/googlecloud-storage-tutorial/stargazers)
-[![GitHub Forks](https://img.shields.io/github/forks/toddbirchard/pandas-sqlalchemy-tutorial.svg?style=flat-square&colorA=4c566a&colorB=ebcb8b)](https://github.com/toddbirchard/googlecloud-storage-tutorial/network)
+[![GitHub Issues](https://img.shields.io/github/issues/hackersandslackers/pandas-sqlalchemy-tutorial.svg?style=flat-square&colorA=4c566a&colorB=ebcb8b)](https://github.com/hackersandslackers/pandas-sqlalchemy-tutorial/issues)
+[![GitHub Stars](https://img.shields.io/github/stars/hackersandslackers/pandas-sqlalchemy-tutorial.svg?style=flat-square&colorB=ebcb8b&colorA=4c566a)](https://github.com/hackersandslackers/pandas-sqlalchemy-tutorial/stargazers)
+[![GitHub Forks](https://img.shields.io/github/forks/hackersandslackers/pandas-sqlalchemy-tutorial.svg?style=flat-square&colorA=4c566a&colorB=ebcb8b)](https://github.com/hackersandslackers/pandas-sqlalchemy-tutorial/network)
+
+Source code for the accompanying tutorial.

README.md

@@ -50,5 +50,6 @@ def get_dataframe_from_sql(table_name):
 
 
 jobs_DF = prepare_data()
+print(jobs_DF.info())
 upload_dataframe_to_sql(jobs_DF)
 get_dataframe_from_sql('nyc_jobs')