Merge branch 'master' into type-hint-arrow-samples

Author: brendaweles

debug-python-errors/README.md

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+# How to Debug Common Python Errors
+
+This folder provides the code examples for the Real Python tutorial [How to Debug Common Python Errors](https://realpython.com/debug-python-errors/).

debug-python-errors/cat.py

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+cat = "Siamese"
+
+print(cat)

debug-python-errors/fruit.py

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+def capitalize_fruit_names(fruits):
+    capitalized_fruit_names = []
+    cleaned = [fruit if isinstance(fruit, str) else "" for fruit in fruits]
+
+    for fruit in cleaned:
+        capitalized_fruit_names.append(fruit.capitalize())
+
+    return capitalized_fruit_names
+
+
+if __name__ == "__main__":
+    print(capitalize_fruit_names(["apple", "BANANA", "cherry", "maNgo"]))

debug-python-errors/palindromes.py

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+def find_palindromes(text):
+    # Split sentence into words
+    words = text.split()
+
+    # Remove punctuation and convert to lowercase
+    normalized_words = [
+        "".join(filter(str.isalnum, word)).lower() for word in words
+    ]
+
+    # Check for palindromes
+    return [word for word in normalized_words if word == word[::-1]]
+
+
+if __name__ == "__main__":
+    print(
+        find_palindromes("Dad plays many solos at noon, and sees a racecar.")
+    )

debug-python-errors/test_fruit.py

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+import unittest
+
+from fruit import capitalize_fruit_names
+
+
+class TestFruit(unittest.TestCase):
+    def test_empty_list(self):
+        """with empty list"""
+        self.assertEqual(capitalize_fruit_names([]), [])
+
+    def test_lowercase(self):
+        """with lowercase strings"""
+        self.assertEqual(
+            capitalize_fruit_names(["apple", "banana", "cherry"]),
+            ["Apple", "Banana", "Cherry"],
+        )
+
+    def test_uppercase(self):
+        """with uppercase strings"""
+        self.assertEqual(
+            capitalize_fruit_names(["APPLE", "BANANA", "CHERRY"]),
+            ["Apple", "Banana", "Cherry"],
+        )
+
+    def test_mixed_case(self):
+        """with mixed case strings"""
+        self.assertEqual(
+            capitalize_fruit_names(["mAnGo", "grApE"]),
+            ["Mango", "Grape"],
+        )
+
+    def test_non_string_element(self):
+        """with a mix of integer and string elements"""
+        self.assertEqual(
+            capitalize_fruit_names([123, "banana"]),
+            ["", "Banana"],
+        )
+
+
+if __name__ == "__main__":
+    unittest.main()

how-to-drop-null-values-in-pandas/README.md

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+# How to Drop Null Values in pandas
+
+The materials contained in this download are designed to complement the Real Python tutorial [How to Drop Null Values in pandas](https://realpython.com/how-to-drop-null-values-in-pandas/).
+
+Consider creating a [Python virtual environment](https://realpython.com/python-virtual-environments-a-primer/) before installing the dependencies:
+
+```shell
+$ python3 -m venv .venv/ --prompt pandas-nulls
+$ source .venv/bin/activate
+(pandas-nulls) $ python -m pip install -r requirements.txt
+```
+
+Your download bundle contains the following four files:
+
+1. `drop_null_rows.py`
+2. `drop_null_columns.py`
+3. `drop_a_subset.py`
+4. `exercise_solutions.py`
+
+The first three files contain the code from different tutorial sections, while the fourth contains the solutions to the exercise.
+
+There are also two data files containing the data used throughout the tutorial:
+
+1. `sales_data_with_missing_values.csv`
+2. `grades.csv`

how-to-drop-null-values-in-pandas/drop_a_subset.py

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+import pandas as pd
+
+pd.set_option("display.max_columns", None)
+
+sales_data = pd.read_csv(
+    "sales_data_with_missing_values.csv",
+    parse_dates=["order_date"],
+    date_format="%d/%m/%Y",
+).convert_dtypes(dtype_backend="pyarrow")
+
+print(sales_data.dropna(axis=0, subset=(["discount", "sale_price"])))
+print(sales_data.dropna(how="all"))
+print(sales_data.dropna(thresh=5))
+print(sales_data.dropna(thresh=5, ignore_index=True))

how-to-drop-null-values-in-pandas/drop_null_columns.py

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+import pandas as pd
+
+sales_data = pd.read_csv(
+    "sales_data_with_missing_values.csv",
+    parse_dates=["order_date"],
+    date_format="%d/%m/%Y",
+).convert_dtypes(dtype_backend="pyarrow")
+
+print(sales_data.dropna(axis="columns"))

how-to-drop-null-values-in-pandas/drop_null_rows.py

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+import pandas as pd
+
+pd.set_option("display.max_columns", None)
+
+sales_data = pd.read_csv(
+    "sales_data_with_missing_values.csv",
+    parse_dates=["order_date"],
+    date_format="%d/%m/%Y",
+).convert_dtypes(dtype_backend="pyarrow")
+
+print(sales_data)
+print(sales_data.isna().sum())
+print(sales_data.dropna())
+
+clean_sales_data = sales_data.dropna()
+print(clean_sales_data)
+
+sales_data.dropna(inplace=True)
+print(sales_data)

how-to-drop-null-values-in-pandas/exercise_solutions.py

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+import pandas as pd
+
+grades = pd.read_csv(
+    "grades.csv",
+).convert_dtypes(dtype_backend="pyarrow")
+
+# 1. Use `.dropna()` in such a way that it permanently drops the row in the dataframe containing only null values.
+grades.dropna(how="all", inplace=True)
+
+# 2. Display the rows for the exams that all students have completed.
+grades.dropna()
+
+# 3. Display any columns with no missing data.
+grades.dropna(axis=1)
+
+# 4. Display the exams sat by at least five students.
+grades.dropna(axis=0, thresh=6)  # Remember there are seven columns.
+
+# 5. Who else was in in every exam that both S2 and S4 sat?
+grades.dropna(subset=["S2", "S4"]).dropna(axis=1, ignore_index=True)