Speed comparison of Python for loop vs. list comprehension

loop-list-speed.ipynb

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   "cell_type": "code",
   "execution_count": 22,
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   "source": [
    "import random\n",
    "randomlist = []\n",
    "for i in range(0, 100000):\n",
    "    n = random.randint(0, 2)\n",
    "    randomlist.append(n)\n",
    "#print(randomlist)"
   ]
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   "cell_type": "code",
   "execution_count": 23,
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   "metadata": {},
   "outputs": [],
   "source": [
    "def split_data_loop(data):\n",
    "    a = []\n",
    "    b = []\n",
    "    c = []\n",
    "    for d in data:\n",
    "        if d == 0 : a.append(d)\n",
    "        if d == 1: b.append(d)\n",
    "        if d == 2 : c.append(d)\n",
    "\n",
    "    return a, b, c"
   ]
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  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "a607ad8a",
   "metadata": {},
   "outputs": [],
   "source": [
    "def split_data_list(data):\n",
    "    a = [d for d in data if d == 0]\n",
    "    b = [d for d in data if d == 1]\n",
    "    c = [d for d in data if d == 2]\n",
    "\n",
    "    return a, b, c"
   ]
  },
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   "cell_type": "code",
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     "name": "stdout",
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     "text": [
      "11 ms ± 25.6 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n"
     ]
    }
   ],
   "source": [
    "%timeit split_data_list(randomlist)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "0d60b611",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "11 ms ± 117 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n"
     ]
    }
   ],
   "source": [
    "%timeit split_data_loop(randomlist)"
   ]
  }
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