python dataframe duplicated returns multiple occurrences for same value

Python's Pandas library provides a powerful and flexible data manipulation tool called DataFrames. DataFrames are two-dimensional, tabular data structures with labeled axes (rows and columns). The .duplicated() method in Pandas is used to identify and handle duplicate values within a DataFrame. This tutorial will guide you through understanding and using the .duplicated() method with code examples.
The .duplicated() method is used to determine whether a particular row is a duplicate of another row in a DataFrame. It returns a boolean series indicating whether each row is a duplicate or not. By default, it considers all columns when identifying duplicates, but you can specify a subset of columns for checking duplicates.
Let's create a simple DataFrame to illustrate the use of .duplicated():
This will output a boolean series indicating whether each row is a duplicate or not.
The .duplicated() method in Pandas is a useful tool for identifying and handling duplicate rows within a DataFrame. By understanding its syntax and options, you can efficiently manage and analyze data with potential duplicates. Consider incorporating this method into your data cleaning and preprocessing workflows to ensure the integrity of your data.
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