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Here is a summary of the code:
This code block uses the Pandas library to normalize a database table. It first reads in the data from a CSV file into a pandas dataframe (df) and removes any duplicates using the "drop_duplicates" method. It then creates a list of tables from the dataframe.

The code then defines a function "normalize_table" which takes a table as input and splits it into smaller tables based on the relationships between the columns. This is done by iterating over the columns in the input table and for each column, creating a new table for each unique value in the column. The new table is created by filtering the input table based on the current value in the loop and removing the column used for filtering from the new table.

Finally, the code normalizes each table in the list of tables by calling the "normalize_table" function and adding its output to the list of tables. The normalized tables are then written to separate CSV files with unique names based on their index in the list.
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