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num.py
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num.py
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"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Array Indexing"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"# Question: Get third and fourth elements from the following array and add them.\n",
"arr = np.array([1, 2, 3, 4, 8,12, 9])\n"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"# Extract the last column from the array arr.\n",
"\n",
"arr = np.array([[1, 2, 3],\n",
" [4, 5, 6],\n",
" [7, 8, 9]])"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"# Question: Create a new array new_arr containing elements from the second and third rows of arr.\n",
"arr = np.array([[1, 2, 3],\n",
" [4, 5, 6],\n",
" [7, 8, 9]])"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"# Question: Use negative indexing to access 2nd last array from the end.\n",
"arr = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17])\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Array Slicing"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"# Question: Given a 1D NumPy array arr, extract elements from index 2 to index 5.\n",
"arr = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9])\n"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"# Question: Extract every alternate element from the array arr.\n",
"arr = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9])\n"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"# Question: Given a 2D NumPy array arr, extract the subarray consisting of rows from index 1 to index 3 and columns from index 2 to index 4.\n",
"arr = np.array([[1, 2, 3, 4, 5],\n",
" [6, 7, 8, 9, 10],\n",
" [11, 12, 13, 14, 15],\n",
" [16, 17, 18, 19, 20]])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# HAPPY CODING!!"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "main_env",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.12"
}
},
"nbformat": 4,
"nbformat_minor": 2