Numpy

Numpy.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "68ea2f2a",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np \n",
    "\"\"\"can use from numpy import *, but its not preferable\"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "02e79e00",
   "metadata": {},
   "outputs": [],
   "source": [
    "arr = np.arange(1000000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "720e4376",
   "metadata": {},
   "outputs": [],
   "source": [
    "pythlist = list(range(1000000))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "6d7979a5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wall time: 746 ms\n"
     ]
    }
   ],
   "source": [
    "%time for _ in range(10): [item*3 for item in pythlist]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "a64976fb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wall time: 29 ms\n"
     ]
    }
   ],
   "source": [
    "%time for _ in range(10): arr = arr*3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "63a0177a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1, 2, 3, 4, 5, 6])"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.array([1,2,3,4,5,6])"
   ]
  }
 ],
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