add py

Author: rayxtr

exportingfile.py

@@ -0,0 +1,113 @@
+# %% [markdown]
+# ##NUMPY
+# 
+# numpy aims to provide  an array  object that is upto 50 x faster than traditional lists.
+# Numpy arrays are stored at one continous place in memory unlike lists so processes can access and manipulate them very efficiently.
+
+# %%
+import numpy as np;
+a = np.array([1,2,22,3])
+
+# %%
+for i in range (len(a)):
+    print(i*7)
+
+# %%
+import numpy as np;
+# Create a 2D array
+matrix = np.array([[1, 2], [3, 4]])
+print("2D Array:\n", matrix)
+
+# Accessing elements
+print("Element at row 0, column 1:", matrix[0, 1])  # Output: 2
+a = np.array([10, 20, 30])
+b = np.array([1, 2, 3])
+
+print("Addition:", a + b)        # [11 22 33]
+print("Multiplication:", a * b)  # [10 40 90]
+print("Mean of a:", np.mean(a))  # 20.0
+
+
+
+# %%
+import numpy as np;
+# Create a 3x3 matrix with random values
+rand_matrix = np.random.rand(3, 3)
+print("Random Matrix:\n", rand_matrix)
+
+# Reshape a flat array to 2D
+flat = np.arange(9)
+reshaped = flat.reshape(3, 3)
+print("Reshaped Array:\n", reshaped)
+
+
+# %%
+import numpy as np;
+arr = np.array([5, 10, 15, 20, 25])
+filtered = arr[arr > 15]
+print("Filtered (greater than 15):", filtered)  # [20 25]
+
+
+# %%
+import numpy as ss;
+arr1 = ss.array([2,3,4,5,5]);
+for i in range (len(arr1)):
+    if i==1 :
+        print(arr1[i])
+
+
+# %%
+import numpy as np
+
+# Step 1: Define two arrays
+array1 = [1, 3, 5, 7, 9]
+array2 = [2, 3, 5, 8, 10]
+
+# Step 2: Get the union (remove duplicates)
+union_array = list(set(array1 + array2))
+union_array.sort()
+
+# Step 3: Calculate mean and median
+mean_val = np.mean(union_array)
+median_val = np.median(union_array)
+
+# Step 4: Print results
+print("Array 1:", array1)
+print("Array 2:", array2)
+print("Union:", union_array)
+print("Mean:", mean_val)
+print("Median:", median_val)
+
+
+# %%
+from math import isqrt
+import numpy as np;
+
+# Arrays
+array1 = [2, 3, 4]
+array2 = [1, 2, 3]
+
+# Union and sort
+union_array = sorted(set(array1 + array2))
+
+print("Star Patterns:\n")
+
+# Function to print a star block of given rows and cols
+def print_block(rows, cols):
+    for _ in range(rows):
+        print("*" * cols)
+    print()
+
+# Generate all rectangle patterns for each number
+for num in union_array:
+    print(f"Patterns for {num} stars:")
+    for rows in range(1, num + 1):
+        if num % rows == 0:
+            cols = num // rows
+            print_block(rows, cols)
+
+
+# %%
+
+
+