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Assignment-2 #48

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6d6e7b6
Lists Assignment Solved
dnc2k Sep 27, 2018
5117d98
Lists Assignment solved
dnc2k Sep 27, 2018
b640138
Numpy Exercise solved
dnc2k Sep 27, 2018
07486f9
Numpy Examples
dnc2k Sep 28, 2018
432ffe6
Numpy Examples
dnc2k Sep 28, 2018
6efe34e
Pandas Examples
dnc2k Sep 29, 2018
640a118
Get to know your Data in Pandas
dnc2k Sep 29, 2018
101c8f4
Delete Basic_Pandas.ipynb
dnc2k Jan 22, 2019
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371 changes: 371 additions & 0 deletions Copy_of_Numpy_Exercises.ipynb
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{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
"name": "Copy of Numpy_Exercises.ipynb",
"version": "0.3.2",
"provenance": [],
"include_colab_link": true
},
"kernelspec": {
"name": "python3",
"display_name": "Python 3"
}
},
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "view-in-github",
"colab_type": "text"
},
"source": [
"[View in Colaboratory](https://colab.research.google.com/github/dnc2k/Assignment-2/blob/dnc2k/Copy_of_Numpy_Exercises.ipynb)"
]
},
{
"metadata": {
"id": "a_4UupTr9fbX",
"colab_type": "text"
},
"cell_type": "markdown",
"source": [
"# Numpy Exercises\n",
"\n",
"1) Create a uniform subdivision of the interval -1.3 to 2.5 with 64 subdivisions"
]
},
{
"metadata": {
"id": "LIP5u4zi0Nmg",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 311
},
"outputId": "23b1a117-1e5b-4256-d322-3b95cec3d1c5"
},
"cell_type": "code",
"source": [
"import numpy as np #import numpy\n",
"a=np.linspace(-1.3,2.5,64).reshape(8,8)\n",
"print (a)"
],
"execution_count": 2,
"outputs": [
{
"output_type": "stream",
"text": [
"[[-1.3 -1.23968254 -1.17936508 -1.11904762 -1.05873016 -0.9984127\n",
" -0.93809524 -0.87777778]\n",
" [-0.81746032 -0.75714286 -0.6968254 -0.63650794 -0.57619048 -0.51587302\n",
" -0.45555556 -0.3952381 ]\n",
" [-0.33492063 -0.27460317 -0.21428571 -0.15396825 -0.09365079 -0.03333333\n",
" 0.02698413 0.08730159]\n",
" [ 0.14761905 0.20793651 0.26825397 0.32857143 0.38888889 0.44920635\n",
" 0.50952381 0.56984127]\n",
" [ 0.63015873 0.69047619 0.75079365 0.81111111 0.87142857 0.93174603\n",
" 0.99206349 1.05238095]\n",
" [ 1.11269841 1.17301587 1.23333333 1.29365079 1.35396825 1.41428571\n",
" 1.47460317 1.53492063]\n",
" [ 1.5952381 1.65555556 1.71587302 1.77619048 1.83650794 1.8968254\n",
" 1.95714286 2.01746032]\n",
" [ 2.07777778 2.13809524 2.1984127 2.25873016 2.31904762 2.37936508\n",
" 2.43968254 2.5 ]]\n"
],
"name": "stdout"
}
]
},
{
"metadata": {
"id": "dBoH_A7M9jjL",
"colab_type": "text"
},
"cell_type": "markdown",
"source": [
"2) Generate an array of length 3n filled with the cyclic pattern 1, 2, 3"
]
},
{
"metadata": {
"id": "4TxT66309n1o",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 35
},
"outputId": "13ce8763-8b0e-4de1-ad88-7f870e808022"
},
"cell_type": "code",
"source": [
"a1=np.array([1,2,3])\n",
"a2=np.resize(a1,3)\n",
"print (a2)"
],
"execution_count": 11,
"outputs": [
{
"output_type": "stream",
"text": [
"[1 2 3]\n"
],
"name": "stdout"
}
]
},
{
"metadata": {
"id": "Vh-UKizx9oTp",
"colab_type": "text"
},
"cell_type": "markdown",
"source": [
"3) Create an array of the first 10 odd integers."
]
},
{
"metadata": {
"id": "ebhEUZq29r32",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 35
},
"outputId": "0efbd9b4-7bc8-4978-e6f6-0fe847326a45"
},
"cell_type": "code",
"source": [
"a2=np.arange(1,20,2)\n",
"print (a2)"
],
"execution_count": 0,
"outputs": [
{
"output_type": "stream",
"text": [
"[ 1 3 5 7 9 11 13 15 17 19]\n"
],
"name": "stdout"
}
]
},
{
"metadata": {
"id": "QfJRdMat90f4",
"colab_type": "text"
},
"cell_type": "markdown",
"source": [
"4) Find intersection of a and b"
]
},
{
"metadata": {
"id": "gOlfuJCo-JwF",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 35
},
"outputId": "766a60e1-d170-41e5-8526-8e13d55546a3"
},
"cell_type": "code",
"source": [
"#expected output array([2, 4])\n",
"a = np.array([1,2,3,2,3,4,3,4,5,6])\n",
"b = np.array([7,2,10,2,7,4,9,4,9,8])\n",
"I = np.intersect1d(a,b)\n",
"print ('I',I)\n"
],
"execution_count": 0,
"outputs": [
{
"output_type": "stream",
"text": [
"I [2 4]\n"
],
"name": "stdout"
}
]
},
{
"metadata": {
"id": "RtVCf0UoCeB8",
"colab_type": "text"
},
"cell_type": "markdown",
"source": [
"5) Reshape 1d array a to 2d array of 2X5"
]
},
{
"metadata": {
"id": "2E8b55_2Cjx5",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 72
},
"outputId": "0321e16b-580e-4f68-e128-ef07b70086f1"
},
"cell_type": "code",
"source": [
"a = np.arange(10)\n",
"a1= a.reshape(2,5)\n",
"print ('After reshape \\n',a1)"
],
"execution_count": 0,
"outputs": [
{
"output_type": "stream",
"text": [
"After reshape \n",
" [[0 1 2 3 4]\n",
" [5 6 7 8 9]]\n"
],
"name": "stdout"
}
]
},
{
"metadata": {
"id": "dVrSBW1zEjp2",
"colab_type": "text"
},
"cell_type": "markdown",
"source": [
"6) Create a numpy array to list and vice versa"
]
},
{
"metadata": {
"id": "tcBCyhXPEp9C",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 90
},
"outputId": "b11709dd-14c1-441f-ea05-42815cc546d8"
},
"cell_type": "code",
"source": [
"a = [1, 2, 3, 4, 5, 6, 7, 8, 9]\n",
"a1=np.array(a)\n",
"print (\"1-D array:\\n\" , a1)\n",
"l1=a1.tolist()\n",
"print (\"Array to List:\\n\", l1)"
],
"execution_count": 15,
"outputs": [
{
"output_type": "stream",
"text": [
"1-D array:\n",
" [1 2 3 4 5 6 7 8 9]\n",
"Array to List:\n",
" [1, 2, 3, 4, 5, 6, 7, 8, 9]\n"
],
"name": "stdout"
}
]
},
{
"metadata": {
"id": "JNqX8wnz9sQJ",
"colab_type": "text"
},
"cell_type": "markdown",
"source": [
"7) Create a 10 x 10 arrays of zeros and then \"frame\" it with a border of ones."
]
},
{
"metadata": {
"id": "4bjP3JAc9vRD",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 201
},
"outputId": "2618d44e-9f7a-423c-f4f4-ba5b2cc4b2b9"
},
"cell_type": "code",
"source": [
"a=np.zeros(shape=(10,10),dtype=int)\n",
"a[0,:]=1\n",
"a[:,0]=1\n",
"a[9,:]=1\n",
"a[:,9]=1\n",
"print (a)"
],
"execution_count": 4,
"outputs": [
{
"output_type": "stream",
"text": [
"[[1 1 1 1 1 1 1 1 1 1]\n",
" [1 0 0 0 0 0 0 0 0 1]\n",
" [1 0 0 0 0 0 0 0 0 1]\n",
" [1 0 0 0 0 0 0 0 0 1]\n",
" [1 0 0 0 0 0 0 0 0 1]\n",
" [1 0 0 0 0 0 0 0 0 1]\n",
" [1 0 0 0 0 0 0 0 0 1]\n",
" [1 0 0 0 0 0 0 0 0 1]\n",
" [1 0 0 0 0 0 0 0 0 1]\n",
" [1 1 1 1 1 1 1 1 1 1]]\n"
],
"name": "stdout"
}
]
},
{
"metadata": {
"id": "xaQgf8tT9v-n",
"colab_type": "text"
},
"cell_type": "markdown",
"source": [
"8) Create an 8 x 8 array with a checkerboard pattern of zeros and ones using a slicing+striding approach."
]
},
{
"metadata": {
"id": "No7fx0Xy9zEh",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 182
},
"outputId": "0e8bcd3c-2881-467b-ffdb-6c57153a46c0"
},
"cell_type": "code",
"source": [
"import numpy as np\n",
"x=np.zeros(shape=(8,8),dtype=int)\n",
"x[1::2,::2]=1\n",
"x[::2,1::2]=1\n",
"print (\"Checkerboard Pattern:\\n\",x)"
],
"execution_count": 3,
"outputs": [
{
"output_type": "stream",
"text": [
"Checkerboard Pattern:\n",
" [[0 1 0 1 0 1 0 1]\n",
" [1 0 1 0 1 0 1 0]\n",
" [0 1 0 1 0 1 0 1]\n",
" [1 0 1 0 1 0 1 0]\n",
" [0 1 0 1 0 1 0 1]\n",
" [1 0 1 0 1 0 1 0]\n",
" [0 1 0 1 0 1 0 1]\n",
" [1 0 1 0 1 0 1 0]]\n"
],
"name": "stdout"
}
]
}
]
}
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