From 3ad7a854b7a06e1a78dfdd67053a2521d1937a62 Mon Sep 17 00:00:00 2001
From: Shreyas Bhangare <54718732+shreyasbhangare@users.noreply.github.com>
Date: Mon, 24 Aug 2020 21:29:53 +0530
Subject: [PATCH] Add files via upload

---
 .../Assignment1 Numpy Shreyas Bhangare.ipynb  | 349 ++++++++++++++++++
 1 file changed, 349 insertions(+)
 create mode 100644 Assignment/Assignment1 Numpy Shreyas Bhangare.ipynb

diff --git a/Assignment/Assignment1 Numpy Shreyas Bhangare.ipynb b/Assignment/Assignment1 Numpy Shreyas Bhangare.ipynb
new file mode 100644
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@@ -0,0 +1,349 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Assignment"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Import numpy as np"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\n",
+    "import numpy as np"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Make a python list => \\[1,2,3,4,5\\]\n",
+    "\n",
+    "Convert it into numpy array and print it"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[1 2 3 4 5]\n"
+     ]
+    }
+   ],
+   "source": [
+    "a=[1,2,3,4,5]\n",
+    "a_np=np.array(a)\n",
+    "print(a_np)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Make a python matrix (3 x 3) => \\[[1,2,3],[4,5,6],[7,8,9]\\]\n",
+    "\n",
+    "Convert it into numpy array and print it"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[[1 2 3]\n",
+      " [4 5 6]\n",
+      " [7 8 9]]\n"
+     ]
+    }
+   ],
+   "source": [
+    "matrix1=[[1,2,3],[4,5,6],[7,8,9]]\n",
+    "matrix1=np.array(matrix1)\n",
+    "print(matrix1)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Make a matrix (3 x 3) using built-in methods (like arange(), reshape() etc.):\n",
+    "\n",
+    "\\[ [1,3,5],\n",
+    "\n",
+    " [7,9,11],\n",
+    " \n",
+    " [13,15,17] \\]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[ 1,  3,  5],\n",
+       "       [ 7,  9, 11],\n",
+       "       [13, 15, 17]])"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "arr=np.arange(1,18,2)\n",
+    "arr.reshape(3,3)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Create a numpy array with 10 random numbers from 0 to 10 (there should be few numbers greater than 1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[5 8 2 9 0 1 6 1 9 9]\n"
+     ]
+    }
+   ],
+   "source": [
+    "randarr=np.random.randint(0,10,10)\n",
+    "print(randarr)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Create numpy array => \\[1,2,3,4,5\\] and convert it to 2D array with 5 rows"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[1],\n",
+       "       [2],\n",
+       "       [3],\n",
+       "       [4],\n",
+       "       [5]])"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "arr=[1,2,3,4,5]\n",
+    "arr=np.array(arr)\n",
+    "arr.reshape(5,1)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Print the shape of the above created array"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "(5,)\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(arr.shape)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Create a numpy array with 10 elements in it. Access and print its 3rd, 4th and 9th element."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "3 4 9\n"
+     ]
+    }
+   ],
+   "source": [
+    "arr=np.array([1,2,3,4,5,6,7,8,9,10])\n",
+    "print(arr[2],arr[3],arr[8])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Print alternate elements of that array"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[1 3 5 7 9]\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(arr[::2])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Change last 3 elements into 100 using broadcasting and print"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[ 1  2  3  4  5  6  7  8  9 10]\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "array([  1,   2,   3,   4,   5,   6,   7, 100, 100, 100])"
+      ]
+     },
+     "execution_count": 33,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "print(arr)\n",
+    "arr[7:]=100\n",
+    "arr"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Create a 5 x 5 matrix (fill it with any element you like), print it.\n",
+    "\n",
+    "Then print the middle (3 x 3) matrix."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[[ 0  1  2  3  4]\n",
+      " [ 5  6  7  8  9]\n",
+      " [10 11 12 13 14]\n",
+      " [15 16 17 18 19]\n",
+      " [20 21 22 23 24]]\n",
+      "\n",
+      "Reshaped array:\n",
+      "\n",
+      "[[ 6  7  8]\n",
+      " [11 12 13]\n",
+      " [16 17 18]]\n"
+     ]
+    }
+   ],
+   "source": [
+    "arr1=np.arange(0,25).reshape(5,5)\n",
+    "print(arr1)\n",
+    "print(\"\\nReshaped array:\\n\")\n",
+    "print(arr1[1:4,1:4])"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "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": "3.7.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}