diff --git a/Leon_Submissions/Homework1.py b/Leon_Submissions/Homework1.py
index e69de29..9384b12 100644
--- a/Leon_Submissions/Homework1.py
+++ b/Leon_Submissions/Homework1.py
@@ -0,0 +1,28 @@
+# Question 1: 
+# The international standard for floating-point representation is 
+# called the "IEEE 754 Standard for Floating-Point Arithmetic."
+
+# Question 2: 
+# 32-bit and 64-bit formats are the most widely used ones in practice.
+
+# Question 3: 
+# My computer supports all these formats
+import numpy as np
+
+supported_formats = np.finfo(np.float32).bits, np.finfo(np.float64).bits
+print(f"Your computer supports the following floating-point formats: {supported_formats}")
+
+
+# Question 4:
+# Using the Pandas multiplication operator (df['Number1'] * df['Number2'])
+# , the result is automatically converted to a floating-point data type. 
+# On the other hand, when I multiply the numbers using the normal Python
+# multiplication operator (num1 * num2), the result remains an integer 
+# data type.
+
+# Question 5:
+# The size of a floating-point number in memory is primarily determined 
+# by the data type and not the actual value it represents. So the size 
+# of a Python floating-point number does not change as it gets larger.
+import sys
+print(sys.getsizeof(70))
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