Summary  
This chapter explains how to use built-in max() and min() methods to retrieve the highest and lowest values from an entire dataset or a specific column in a DataFrame.  

General domain of usage  
Data analysis

`pandas` provides the `max()` method, which returns the **highest value** from a dataset.

```python
df = pd.read_csv(file.csv)
max_value = df.max()
```

To identify the highest value of a specific column, you can use this approach:
```python
df = pd.read_csv(file.csv)
max_values = df['column_name'].max()
```

Similarly, `pandas` offers the `min()` method that fetches the **smallest value** from a dataset.
```python
df = pd.read_csv(file.csv)
min_value = df.min()
```

To determine the smallest value for a particular column, the same method is used:
```python
df = pd.read_csv(file.csv)
min_values = df['column_name'].min()
```

import unittest
import importlib


def _dynamic_test(test_case, condition, success_message, failure_message):
    if condition:
        test_case._testMethodName = success_message
        test_case.assertTrue(True, success_message)
    else:
        test_case._testMethodName = failure_message
        test_case.fail(failure_message)


class TestUserCode(unittest.TestCase):

    def test_highest_price_is_declared(self):
        import user_code
        _dynamic_test(
            self,
            hasattr(user_code, 'highest_price'),
            "The `highest_price` variable is declared.",
            "Expected `highest_price` to be declared."
        )

    def test_highest_price_is_correct(self):
        import user_code
        expected_value = max([12500, 16500, 16800, 17300, 16500])

        try:
            actual_value = user_code.highest_price
            condition = actual_value == expected_value
            failure_message = f"Expected `highest_price` to be `{expected_value}`, but got `{actual_value}`."
        except AttributeError:
            condition = False
            failure_message = "The `highest_price` variable is not declared."

        _dynamic_test(
            self,
            condition,
            f"The `highest_price` is `{expected_value}`.",
            failure_message
        )

    def test_lowest_price_is_declared(self):
        import user_code
        _dynamic_test(
            self,
            hasattr(user_code, 'lowest_price'),
            "The `lowest_price` variable is declared.",
            "Expected `lowest_price` to be declared."
        )

    def test_lowest_price_is_correct(self):
        import user_code
        expected_value = min([12500, 16500, 16800, 17300, 16500])

        try:
            actual_value = user_code.lowest_price
            condition = actual_value == expected_value
            failure_message = f"Expected `lowest_price` to be `{expected_value}`, but got `{actual_value}`."
        except AttributeError:
            condition = False
            failure_message = "The `lowest_price` variable is not declared."

        _dynamic_test(
            self,
            condition,
            f"`lowest_price` has correct value.",
            failure_message
        )


if __name__ == '__main__':
    unittest.main()

test_main.py

Focus on the core skills for wrangling tabular data with pandas in Python. Learn to build efficient data pipelines, manipulate DataFrames, filter and select records, handle missing values, perform aggregations, and merge datasets for data science workflows. Each chapter is action-oriented and ends with practical challenges.

max() and min()

Solution