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Today we’re going to talk about how to upload your data from a pandas dataframe to a database in the cloud. This is a continuation of building the one and only data science project you need ( • The One and Only Data Science Project... ) where I introduced the infrastructure you can build for data science projects. The first part is to collect data from an API as your data source. I walked you through how to do that in this video ( • Working with APIs in Python [For Your... ). Now that you have the data from the API saved in a pandas dataframe, we need to get it into a database table. Link to Github repo: https://github.com/Strata-Scratch/api... ______________________________________________________________________ 👉 Subscribe to my channel: https://bit.ly/2GsFxmA 👉 Playlist for more data science interview questions and answers: https://bit.ly/3jifw81 👉 Playlist for data science interview tips: https://bit.ly/2G5hNoJ 👉 Practice more real data science interview questions: https://platform.stratascratch.com/co... ______________________________________________________________________ Timeline: Intro: (0:00) Solve for memory and performance issues: (0:45) Have different version of the data: (1:02) Create your database on the cloud: (2:27) Create a Google Colab or Jupyter Notebook: (3:15) Connecting to your database: (5:34) Create your DB table: (8:02) Loading your data into the DB table: (11:16) Check to see if video exists: (13:10) Updating the table: (16:15) Inserting new videos to table: (19:58) Testing: (28:54) Conclusion: (31:55) ______________________________________________________________________ If you want data science interview practice with real data science interview questions, visit https://platform.stratascratch.com/co.... All questions are free and you can even execute SQL and python code in the IDE, but if you want to check out the solutions from me or from other users, you can use ss15 for a 15% discount on the premium plans. ______________________________________________________________________ Contact: If you have any questions, comments, or feedback, please leave them here! Feel free to also email me at [email protected] ______________________________________________________________________ #PandasDataframe #datascience