Here is an example code block for normalizing a database table in Python using the Pandas library:

sql

import pandas as pd

# Load the data into a pandas dataframe
df = pd.read_csv("data.csv")

# Drop any duplicates in the dataframe
df = df.drop_duplicates()

# Create a list of tables based on the dataframe
tables = [df]

# Function to normalize a table
def normalize_table(table):
  # Split the table into smaller tables based on the relationships between the columns
  tables = []
  for column in table.columns:
    # Create a new table for each unique value in the column
    unique_values = table[column].unique()
    for value in unique_values:
      new_table = table[table[column] == value]
      new_table = new_table.drop(column, axis=1)
      tables.append(new_table)

  return tables

# Normalize each table in the list
for table in tables:
  tables = tables + normalize_table(table)

# Write the normalized tables to separate CSV files
for i, table in enumerate(tables):
  table.to_csv(f"table_{i}.csv", index=False)
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