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Replication of “SeeDB: Efficient Data-Driven Visualization Recommendations to Support Visual Analytics”. Includes Exploratory Data Analysis and various pruning techniques to optimize the system.

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AyusheGangal/SeeDB_Replication

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SeeDB_Project

SeeDB

This is the readme file for executing SeeDB on the census dataset, and it contains the instructions to run the seeDB iPython notebook. Follow the below steps:

  1. Run the Preprocessing iPython notebook present in the SeeDB folder.
  2. Ensure that the data path is correctly specified in the read_csv function. Make sure the destination of the partitioned files is correctly specified in the split_csv function.
  3. Connect to the PostgreSQL database and run the queries in the “SeeDB/sql_script.sql” file. Properly update the file names in accordance with the file names you updated in the “Preprocessing.ipynb”.
  4. Run the ipython notebook “SeeDB/main.ipynb”.

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Replication of “SeeDB: Efficient Data-Driven Visualization Recommendations to Support Visual Analytics”. Includes Exploratory Data Analysis and various pruning techniques to optimize the system.

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