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00945ec
Created using Colaboratory
Sounak97 Sep 25, 2018
ee9926e
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Sounak97 Sep 25, 2018
a579efc
Created using Colaboratory
Sounak97 Sep 25, 2018
fecb5b0
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Sounak97 Sep 26, 2018
e65d59c
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Sounak97 Sep 28, 2018
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394 changes: 364 additions & 30 deletions Sounak97.ipynb
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Original file line number Diff line number Diff line change
@@ -1,32 +1,366 @@
{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
"name": "Sounak97.ipynb",
"version": "0.3.2",
"provenance": []
},
"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": "3.5.2"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
"cells": [
{
"metadata": {
"id": "ahm2qZERkD2t",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 168
},
"outputId": "c840c130-e0b3-422d-dab3-a9515a47bcdf"
},
"cell_type": "code",
"source": [
"#1) Create any random list and assign it to a variable dummy_list\n",
"dummy_list=[100,300,200,500,400]\n",
"print(dummy_list)#2) print dummy_list\n",
"dummy_list.reverse()\n",
"print(dummy_list)#3) Reverse dummy_list and print\n",
"dummy_list_2 = [2, 200, 16, 4, 1, 0, 9.45, 45.67, 90, 12.01, 12.02]\n",
"dummy_list=dummy_list + dummy_list_2#4) Add the list dummy_list_2 to the previous dummy_list and now print dummy_list\n",
"print(dummy_list)\n",
"dummy_dict={100:1,300:1,200:2,500:1,400:1,2:1,16:1,4:1,1:1,0:1,9.45:1,45.67:1,90:1,12.01:1,12.02:1}\n",
"\n",
"print(dummy_dict) #5) Create a dictionary named dummy_dict which contains all the elements of dummy_list as keys and frequency as values.6) print dummy_dict\n",
"dummy_list.sort()#7) Sort dummy_list in ascending order as well as descending order and print the changed lists\n",
"print(dummy_list)\n",
"dummy_list.sort(reverse=True)\n",
"print(dummy_list)\n",
"x=200#8) Remove the first item from the list whose value is equal to x. It raises a ValueError if there is no such item.\n",
"p=0\n",
"j=0\n",
"for j in dummy_list:\n",
" if j==x :\n",
" dummy_list.remove(j)\n",
" break\n",
" else:\n",
" j=j+1\n",
" p=p+1\n",
" \n",
"if p==len(dummy_list):\n",
" print(\"ValueError\")\n",
"else:\n",
" print(dummy_list)\n",
" \n",
"x=14#9) Remove the item at position x. x is any random integer\n",
"if(x>len(dummy_list)):\n",
" print(\"Out of Range\")\n",
"else:\n",
" del dummy_list[x]\n",
"print(dummy_list)\n",
"del dummy_list[:]#10) Let's clean everything clear the list and then print\n",
"print(dummy_list)\n",
"\n",
"\n",
" \n",
" \n",
"\n"
],
"execution_count": 2,
"outputs": [
{
"output_type": "stream",
"text": [
"[100, 300, 200, 500, 400]\n",
"[400, 500, 200, 300, 100]\n",
"[400, 500, 200, 300, 100, 2, 200, 16, 4, 1, 0, 9.45, 45.67, 90, 12.01, 12.02]\n",
"{100: 1, 300: 1, 200: 2, 500: 1, 400: 1, 2: 1, 16: 1, 4: 1, 1: 1, 0: 1, 9.45: 1, 45.67: 1, 90: 1, 12.01: 1, 12.02: 1}\n",
"[0, 1, 2, 4, 9.45, 12.01, 12.02, 16, 45.67, 90, 100, 200, 200, 300, 400, 500]\n",
"[500, 400, 300, 200, 200, 100, 90, 45.67, 16, 12.02, 12.01, 9.45, 4, 2, 1, 0]\n",
"[500, 400, 300, 200, 100, 90, 45.67, 16, 12.02, 12.01, 9.45, 4, 2, 1, 0]\n",
"[500, 400, 300, 200, 100, 90, 45.67, 16, 12.02, 12.01, 9.45, 4, 2, 1]\n",
"[]\n"
],
"name": "stdout"
}
]
},
{
"metadata": {
"id": "VwSRD8sVvAFC",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 857
},
"outputId": "371e4abd-fa21-42eb-9804-cb9be93e584e"
},
"cell_type": "code",
"source": [
"import numpy as np#Import numpy\n",
"a=np.array([100,200,300])\n",
"print(a)\n",
"print(type(a))\n",
"\n",
"b=np.array([[10,20,30],[40,50,60]]) #Create numpy arrays\n",
"print(b.shape)\n",
"print(b[0,0],b[0,1],b[1,0])\n",
"a=np.zeros(shape=(2,2))#Some basic functions for creating arrays\n",
"b=np.ones(shape=(3,3))\n",
"c=np.eye(2)\n",
"d=np.full(shape=(3,3),fill_value=5)\n",
"e=np.random.random((2,2))\n",
"print('a',a)\n",
"print('b',b)\n",
"print('c',c)\n",
"print('d',d)\n",
"print('e',e)\n",
"a==np.arange(10) #execute and understand\n",
"b==np.linspace(0,10,num=6)\n",
"print(a)\n",
"print(b)\n",
"a = np.array([[1,2,3,4], [5,6,7,8], [9,10,11,12]])#Array Indexing\n",
"b = a[:2, 1:3]\n",
"print(a[0,1])\n",
"b[0,0]=77\n",
"print(a[0,1])\n",
"a = np.array([[1,2,3,4], [5,6,7,8], [9,10,11,12]])#slicing\n",
"row_r1 = a[1, :] \n",
"row_r2 = a[1:2, :]\n",
"print(row_r1,row_r1.shape)\n",
"print(row_r2,row_r2.shape)\n",
"col_r1=a[:,1]\n",
"col_r2=a[:,1:2]\n",
"print(col_r1, col_r1.shape)\n",
"print(col_r2, col_r2.shape)\n",
"\n",
"\n",
"x=np.array([[1,2],[3,4]])#Arithmetic operations\n",
"print(np.sum(x))\n",
"print(np.sum(x,axis=0))#sum of each column\n",
"print(np.sum(x,axis=1))#sum of each row\n",
"b=np.arange(10)#Boolean Mask use\n",
"print(b)\n",
"mask=b%2!=0\n",
"print(mask)\n",
"print(b[mask])\n",
"mod_b=b\n",
"mod_b[mask]=-1\n",
"print(mod_b)\n",
"a=np.arange(9).reshape(3,3)#swapping 2 colums\n",
"print(a)\n",
"print(a[:,[1,0,2]])\n",
"a=np.arange(9).reshape(3,3)#swapping 2 rows\n",
"print(a)\n",
"print(a[[1,0,2],:])\n",
"\n"
],
"execution_count": 0,
"outputs": [
{
"output_type": "stream",
"text": [
"[100 200 300]\n",
"<class 'numpy.ndarray'>\n",
"(2, 3)\n",
"10 20 40\n",
"a [[0. 0.]\n",
" [0. 0.]]\n",
"b [[1. 1. 1.]\n",
" [1. 1. 1.]\n",
" [1. 1. 1.]]\n",
"c [[1. 0.]\n",
" [0. 1.]]\n",
"d [[5 5 5]\n",
" [5 5 5]\n",
" [5 5 5]]\n",
"e [[0.58957867 0.78449677]\n",
" [0.17984702 0.68954991]]\n",
"[[0. 0.]\n",
" [0. 0.]]\n",
"[[1. 1. 1.]\n",
" [1. 1. 1.]\n",
" [1. 1. 1.]]\n",
"2\n",
"77\n",
"[5 6 7 8] (4,)\n",
"[[5 6 7 8]] (1, 4)\n",
"[ 2 6 10] (3,)\n",
"[[ 2]\n",
" [ 6]\n",
" [10]] (3, 1)\n",
"10\n",
"[4 6]\n",
"[3 7]\n",
"[0 1 2 3 4 5 6 7 8 9]\n",
"[False True False True False True False True False True]\n",
"[1 3 5 7 9]\n",
"[ 0 -1 2 -1 4 -1 6 -1 8 -1]\n",
"[[0 1 2]\n",
" [3 4 5]\n",
" [6 7 8]]\n",
"[[1 0 2]\n",
" [4 3 5]\n",
" [7 6 8]]\n",
"[[0 1 2]\n",
" [3 4 5]\n",
" [6 7 8]]\n",
"[[3 4 5]\n",
" [0 1 2]\n",
" [6 7 8]]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:19: DeprecationWarning: elementwise == comparison failed; this will raise an error in the future.\n",
"/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:20: DeprecationWarning: elementwise == comparison failed; this will raise an error in the future.\n"
],
"name": "stderr"
}
]
},
{
"metadata": {
"id": "JTnipVXrvLwo",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 638
},
"outputId": "b7a95e69-ccca-4dd9-cb68-57d7f287dcd7"
},
"cell_type": "code",
"source": [
"\n",
"\n",
"\n",
"import numpy as np#Create a uniform subdivision of the interval -1.3 to 2.5 with 64 subdivisions\n",
"A=np.linspace(-1.3,2.5,64)\n",
"print(A)\n",
"\n",
"\n",
"\n",
"\n",
"\n",
"n=int(input())# Generate an array of length 3n filled with the cyclic pattern 1, 2, 3\n",
"B=np.array([1,2,3])\n",
"B=np.resize(B,3*n)\n",
"print(B)\n",
"\n",
"\n",
"\n",
"\n",
"\n",
"b1=np.arange(1,20,2)#Create an array of the first 10 odd integers.\n",
"print(b1)\n",
"\n",
"\n",
"\n",
"\n",
"\n",
"a=np.array([1,2,3,2,3,4,3,4,5,6])#Find intersection of a and b\n",
"b = np.array([7,2,10,2,7,4,9,4,9,8])\n",
"np.intersect1d(a,b)\n",
"\n",
"\n",
"\n",
"\n",
"\n",
"a1=np.arange(10)# Reshape 1d array a to 2d array of 2X5\n",
"print(a1)\n",
"a1=a1.reshape(2,5)\n",
"print(a1)\n",
"\n",
"\n",
"\n",
"\n",
"\n",
"a2=[1,2,3,4,5,6,7,8,9]#conversion\n",
"a2=np.array(a2)#numpy list to array\n",
"print(a2)\n",
"a2.tolist()#numpy array to list\n",
"print(a2)\n",
"\n",
"\n",
"\n",
"\n",
"\n",
"a3=np.ones(shape=(10,10))# Create a 10 x 10 arrays of zeros and then \"frame\" it with a border of ones.\n",
"a3[1:9,1:9]=0\n",
"print(a3)\n",
"\n",
"\n",
"\n",
"\n",
"\n",
"a4=np.ones(shape=(8,8))#Create an 8 x 8 array with a checkerboard pattern of zeros and ones using a slicing+striding approach.\n",
"a4[::2,1::2]=0\n",
"a4[1::2,::2]=0\n",
"print(a4)"
],
"execution_count": 0,
"outputs": [
{
"output_type": "stream",
"text": [
"[-1.3 -1.23968254 -1.17936508 -1.11904762 -1.05873016 -0.9984127\n",
" -0.93809524 -0.87777778 -0.81746032 -0.75714286 -0.6968254 -0.63650794\n",
" -0.57619048 -0.51587302 -0.45555556 -0.3952381 -0.33492063 -0.27460317\n",
" -0.21428571 -0.15396825 -0.09365079 -0.03333333 0.02698413 0.08730159\n",
" 0.14761905 0.20793651 0.26825397 0.32857143 0.38888889 0.44920635\n",
" 0.50952381 0.56984127 0.63015873 0.69047619 0.75079365 0.81111111\n",
" 0.87142857 0.93174603 0.99206349 1.05238095 1.11269841 1.17301587\n",
" 1.23333333 1.29365079 1.35396825 1.41428571 1.47460317 1.53492063\n",
" 1.5952381 1.65555556 1.71587302 1.77619048 1.83650794 1.8968254\n",
" 1.95714286 2.01746032 2.07777778 2.13809524 2.1984127 2.25873016\n",
" 2.31904762 2.37936508 2.43968254 2.5 ]\n",
"6\n",
"[1 2 3 1 2 3 1 2 3 1 2 3 1 2 3 1 2 3]\n",
"[ 1 3 5 7 9 11 13 15 17 19]\n",
"[0 1 2 3 4 5 6 7 8 9]\n",
"[[0 1 2 3 4]\n",
" [5 6 7 8 9]]\n",
"[1 2 3 4 5 6 7 8 9]\n",
"[1 2 3 4 5 6 7 8 9]\n",
"[[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",
"[[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",
" [0. 1. 0. 1. 0. 1. 0. 1.]]\n"
],
"name": "stdout"
}
]
},
{
"metadata": {
"id": "5mZI6Q3q1cCb",
"colab_type": "text"
},
"cell_type": "markdown",
"source": [
""
]
}
]
}
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