diff --git a/how-to-drop-null-values-in-pandas/README.md b/how-to-drop-null-values-in-pandas/README.md
new file mode 100644
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@@ -0,0 +1,16 @@
+The materials contained in this download are designed to complement the RealPython tutorial [How to Drop Null Values in pandas](https://realpython.com/how-to-drop-null-values-in-pandas/).
+
+You should create a new folder named pandas_nulls on your computer and place each file inside it. You may also consider creating a [Python virtual environment](https://realpython.com/python-virtual-environments-a-primer/) within this folder.
+
+Your download bundle contains the following four files. The first three files contain the code from different tutorial sections, while the fourth contains the solutions to the exercise.
+
+`drop_null_rows.py`        
+`drop_null_columns.py`   
+`drop_a_subset.py`         
+`exercise_solutions.py` 
+
+There are also two data files containing the data used throughout the tutorial:
+
+`sales_data_with_missing_values.csv`
+`grades.csv`
+
diff --git a/how-to-drop-null-values-in-pandas/drop_a_subset.py b/how-to-drop-null-values-in-pandas/drop_a_subset.py
new file mode 100644
index 0000000000..c6d7094877
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+++ b/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")
+
+
+sales_data.dropna(axis=0, subset=(["discount", "sale_price"]))
+
+sales_data.dropna(how="all")
+
+sales_data.dropna(thresh=5)
+
+sales_data.dropna(thresh=5, ignore_index=True)
diff --git a/how-to-drop-null-values-in-pandas/drop_null_columns.py b/how-to-drop-null-values-in-pandas/drop_null_columns.py
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+++ b/how-to-drop-null-values-in-pandas/drop_null_columns.py
@@ -0,0 +1,9 @@
+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")
+
+sales_data.dropna(axis="columns")
diff --git a/how-to-drop-null-values-in-pandas/drop_null_rows.py b/how-to-drop-null-values-in-pandas/drop_null_rows.py
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+++ b/how-to-drop-null-values-in-pandas/drop_null_rows.py
@@ -0,0 +1,19 @@
+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")
+
+sales_data
+
+sales_data.isna().sum()
+
+sales_data.dropna()
+
+clean_sales_data = sales_data.dropna()
+
+clean_sales_data = sales_data.dropna(inplace=True)
diff --git a/how-to-drop-null-values-in-pandas/exercise_solutions.py b/how-to-drop-null-values-in-pandas/exercise_solutions.py
new file mode 100644
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--- /dev/null
+++ b/how-to-drop-null-values-in-pandas/exercise_solutions.py
@@ -0,0 +1,25 @@
+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)
diff --git a/how-to-drop-null-values-in-pandas/grades.csv b/how-to-drop-null-values-in-pandas/grades.csv
new file mode 100644
index 0000000000..b716989147
--- /dev/null
+++ b/how-to-drop-null-values-in-pandas/grades.csv
@@ -0,0 +1,8 @@
+Subject,S1,S2,S3,S4,S5,S6
+math,18,,15,20,17,18
+science,26,35,19,,33,
+art,15,,9,17,18,14
+music,14,20,12,20,13,18
+history,18,19,,17,,18
+sport,20,17,20,17,18
+,,,,,
\ No newline at end of file
diff --git a/how-to-drop-null-values-in-pandas/sales_data_with_missing_values.csv b/how-to-drop-null-values-in-pandas/sales_data_with_missing_values.csv
new file mode 100644
index 0000000000..04036fafc2
--- /dev/null
+++ b/how-to-drop-null-values-in-pandas/sales_data_with_missing_values.csv
@@ -0,0 +1,12 @@
+order_number,order_date,customer_name,product_purchased,discount,sale_price
+,09/02/2025,Skipton Fealty,Chili Extra Virgin Olive Oil,TRUE,135.00
+70041,,Carmine Priestnall,,,150.00
+70042,09/02/2025,,Rosemary Olive Oil Candle,FALSE,78.00
+70043,10/02/2025,Lanni D'Ambrogi,,TRUE,19.50
+70044,10/02/2025,Tann Angear,Vanilla and Olive Oil Candle,,13.98
+70045,10/02/2025,Skipton Fealty,Basil Extra Virgin Olive Oil,TRUE,
+70046,11/02/2025,Far Pow,Chili Extra Virgin Olive Oil,FALSE,150.00
+70047,11/02/2025,Hill Group,Chili Extra Virgin Olive Oil,TRUE,135.00
+70048,11/02/2025,Devlin Nock,Lavender and Olive Oil Lotion,FALSE,39.96
+,,,,,
+70049,12/02/2025,Swift Inc,Garlic Extra Virgin Olive Oil,TRUE,936.00