6.1 What Is NumPy Arrays (Ndarrays).ipynb

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   "source": [
    "<center><em>Copyright! This material is protected, please do not copy or distribute.    by:Taher Assaf</em></center>"
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   "source": [
    "***\n",
    "<h1 align=\"center\">Udemy course : Python Bootcamp for Data Science 2021 Numpy Pandas & Seaborn</h1> \n",
    "\n",
    "***"
   ]
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   "source": [
    "## 6.1 What Is NumPy Arrays (Ndarrays)"
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   "source": [
    "here we create a list using the range() function:"
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   "source": [
    "list1 = list(range(1000000))"
   ]
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   "source": [
    "lets check the type of this variable:"
   ]
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       "list"
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   "source": [
    "type(list1)"
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    "Importing numpy library:"
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   "source": [
    "import numpy as np"
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   "source": [
    "We can create the same above list but this time using function arange() in numpy:"
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   "source": [
    "np_array = np.arange(1000000)"
   ]
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  {
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   "source": [
    "Lets check the tyoe of this data using the type() function:"
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      "text/plain": [
       "numpy.ndarray"
      ]
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     "execution_count": 5,
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   "source": [
    "type(np_array)"
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   "source": [
    "To check the execution time for multiplying the first list by number 3:"
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     "text": [
      "67.8 ms ± 2.83 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
     ]
    }
   ],
   "source": [
    "%timeit list1*3"
   ]
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   "source": [
    "Now we check the execution time for multiplying numpy array: "
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     "text": [
      "4.05 ms ± 193 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n"
     ]
    }
   ],
   "source": [
    "%timeit np_array *3"
   ]
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   "source": [
    "***\n",
    "\n",
    "<h1 align=\"center\">Thank You</h1> \n",
    "\n",
    "***"
   ]
  }
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