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HackerRank --> Python --> Numpy --> COMPLETED
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‎HackerRank/Python/Numpy/Numpy.ipynb‎

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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# [Array Mathematics](https://www.hackerrank.com/challenges/np-array-mathematics/problem?h_r=next-challenge&h_v=zen)\n",
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"<pre>\n",
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"Basic mathematical functions operate element-wise on arrays. They are available both as operator overloads and as functions in the NumPy module.\n",
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"\n",
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"import numpy\n",
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"\n",
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"a = numpy.array([1,2,3,4], float)\n",
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"b = numpy.array([5,6,7,8], float)\n",
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"\n",
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"print a + b #[ 6. 8. 10. 12.]\n",
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"print numpy.add(a, b) #[ 6. 8. 10. 12.]\n",
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"\n",
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"print a - b #[-4. -4. -4. -4.]\n",
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"print numpy.subtract(a, b) #[-4. -4. -4. -4.]\n",
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"\n",
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"print a * b #[ 5. 12. 21. 32.]\n",
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"print numpy.multiply(a, b) #[ 5. 12. 21. 32.]\n",
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"\n",
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"print a / b #[ 0.2 0.33333333 0.42857143 0.5 ]\n",
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"print numpy.divide(a, b) #[ 0.2 0.33333333 0.42857143 0.5 ]\n",
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"\n",
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"print a % b #[ 1. 2. 3. 4.]\n",
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"print numpy.mod(a, b) #[ 1. 2. 3. 4.]\n",
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"\n",
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"print a**b #[ 1.00000000e+00 6.40000000e+01 2.18700000e+03 6.55360000e+04]\n",
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"print numpy.power(a, b) #[ 1.00000000e+00 6.40000000e+01 2.18700000e+03 6.55360000e+04]</pre>"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 23,
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"metadata": {},
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"outputs": [
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{
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"name": "stdin",
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"output_type": "stream",
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"text": [
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" 1 4\n",
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" 1 2 3 4\n",
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" 5 6 7 8\n"
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]
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"[[ 6 8 10 12]]\n",
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"[[-4 -4 -4 -4]]\n",
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"[[ 5 12 21 32]]\n",
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"[[0 0 0 0]]\n",
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"[[1 2 3 4]]\n",
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"[[ 1 64 2187 65536]]\n",
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"\n"
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]
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}
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],
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"source": [
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"import numpy as np\n",
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"n1,n2=map(int,input().split())\n",
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"a1=np.zeros((n1,n2),int)\n",
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"a2=np.zeros((n1,n2),int)\n",
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"\n",
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"for i in range(n1):\n",
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" a1[i]=np.array(input().split(),int)\n",
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"\n",
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"for i in range(n1):\n",
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" a2[i]=np.array(input().split(),int)\n",
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"\n",
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"\n",
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"np.set_printoptions(legacy='1.13')\n",
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" \n",
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"print(f'{(a1+a2).astype(int)}\\n{(a1-a2).astype(int)}\\n{(a1*a2).astype(int)}\\n{(a1//a2).astype(int)}\\n{(a1%a2).astype(int)}\\n{(a1**a2).astype(int)}\\n')"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 31,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"array([0, 0, 0, 0])"
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]
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},
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"execution_count": 31,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"a1=np.zeros((n1,n2),int)\n",
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"# a1[0]=np.array(input().split(),int)\n",
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"a1[0]"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 15,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"array([[0, 0],\n",
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" [0, 0]])"
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]
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},
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"execution_count": 15,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"np.zeros((2,2),int)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# [Floor, Ceil and Rint](https://www.hackerrank.com/challenges/floor-ceil-and-rint/problem?h_r=next-challenge&h_v=zen)\n",
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"\n",
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"<pre>\n",
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"<b>floor</b>\n",
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"The tool floor returns the floor of the input element-wise.\n",
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"The floor of is the largest integer where .\n",
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"\n",
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"import numpy\n",
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"\n",
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"my_array = numpy.array([1.1, 2.2, 3.3, 4.4, 5.5, 6.6, 7.7, 8.8, 9.9])\n",
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"print numpy.floor(my_array) #[ 1. 2. 3. 4. 5. 6. 7. 8. 9.]\n",
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"\n",
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"<b>ceil</b>\n",
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"The tool ceil returns the ceiling of the input element-wise.\n",
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"The ceiling of is the smallest integer where .\n",
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"\n",
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"import numpy\n",
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"\n",
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"my_array = numpy.array([1.1, 2.2, 3.3, 4.4, 5.5, 6.6, 7.7, 8.8, 9.9])\n",
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"print numpy.ceil(my_array) #[ 2. 3. 4. 5. 6. 7. 8. 9. 10.]\n",
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"\n",
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"<b>rint</b>\n",
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"The rint tool rounds to the nearest integer of input element-wise.\n",
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"\n",
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"import numpy\n",
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"\n",
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"my_array = numpy.array([1.1, 2.2, 3.3, 4.4, 5.5, 6.6, 7.7, 8.8, 9.9])\n",
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"print numpy.rint(my_array) #[ 1. 2. 3. 4. 6. 7. 8. 9. 10.]\n",
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"</pre>"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [
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{
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"name": "stdin",
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"output_type": "stream",
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"text": [
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" 1.1 2.2 3.3 4.4 5.5 6.6 7.7 8.8 9.9\n"
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]
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"[ 1. 2. 3. 4. 5. 6. 7. 8. 9.]\n",
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"[ 2. 3. 4. 5. 6. 7. 8. 9. 10.]\n",
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"[ 1. 2. 3. 4. 6. 7. 8. 9. 10.]\n"
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]
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}
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],
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"source": [
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"import numpy as np\n",
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"a=np.array(input().split(),float)\n",
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"np.set_printoptions(legacy='1.13')\n",
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"print(np.floor(a))\n",
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"print(np.ceil(a))\n",
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"print(np.rint(a))"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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},
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{
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"cell_type": "code",
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"execution_count": 19,
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"execution_count": 1,
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"metadata": {},
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"outputs": [
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{
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"source": [
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"import numpy as np\n",
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"n1,n2=map(int,input().split())\n",
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"np.set_printoptions(legacy='1.13')\n",
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"print(np.eye(n1,n2))"
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]
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},

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