Get difference between two lists

performace_list_set_diff.ipynb

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   "source": [
    "import numpy as np\n",
    "import pandas as pd"
   ]
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     "text": [
      "Wall time: 12 ms\n"
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   "source": [
    "%%time\n",
    "maxsize=int(1e5)\n",
    "l1=list(range(1,maxsize,3))+list(range(1,maxsize,5))\n",
    "l2=list(range(0,maxsize,7))+list(range(1,maxsize,11))\n",
    "\n",
    "l11=np.array(l1)\n",
    "l12=pd.Index(l11).astype('int32')\n",
    "l21=np.array(l2)\n",
    "l22=pd.Index(l21).astype('int32')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wall time: 21.5 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "comp1={_ for _ in l2 if _ not in l1}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wall time: 26.9 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "comp2=[_ for _ in l2 if _ not in l1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wall time: 30.8 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "comp3={_ for _ in l1 if _ not in l2}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wall time: 30.7 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "comp4=[_ for _ in l1 if _ not in l2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wall time: 8 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "numpy_diff1=np.setdiff1d(l11,l21)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wall time: 6 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "numpy_diff2=np.setdiff1d(l21,l11)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wall time: 11 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "pd_diff1=l12.difference(l22)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wall time: 6.5 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "pd_diff2=l22.difference(l12)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(11776, 12467, 36363, 41557)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(comp1), len(comp2), len(comp3), len(comp4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "scrolled": true
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     "data": {
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       "(36363, 11776)"
      ]
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     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "numpy_diff1.size, numpy_diff2.size"
   ]
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   "cell_type": "code",
   "execution_count": 13,
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     "execution_count": 13,
     "metadata": {},
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   "source": [
    "pd_diff1.size, pd_diff2.size"
   ]
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   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wall time: 1.01 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "maxsize=int(1e7)\n",
    "l1=list(range(1,maxsize,3))+list(range(1,maxsize,5))\n",
    "l2=list(range(0,maxsize,7))+list(range(1,maxsize,11))\n",
    "\n",
    "l11=np.array(l1)\n",
    "l12=pd.Index(l11).astype('int32')\n",
    "l21=np.array(l2)\n",
    "l22=pd.Index(l21).astype('int32')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
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   "outputs": [
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     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wall time: 693 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "numpy_diff1=np.setdiff1d(l11,l21)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wall time: 707 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "numpy_diff2=np.setdiff1d(l21,l11)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wall time: 1.71 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "pd_diff1=l12.difference(l22)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "scrolled": false
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wall time: 1.27 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "pd_diff2=l22.difference(l12)"
   ]
  },
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   "cell_type": "code",
   "execution_count": 19,
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      "text/plain": [
       "(3636362, 1177489)"
      ]
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     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
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   "source": [
    "numpy_diff1.size, numpy_diff2.size"
   ]
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   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "scrolled": true
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     "data": {
      "text/plain": [
       "(3636362, 1177489)"
      ]
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     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
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   "source": [
    "pd_diff1.size, pd_diff2.size"
   ]
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   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(dtype('int32'), dtype('int64'))"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "numpy_diff1.dtype, pd_diff1.dtype"
   ]
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   "cell_type": "code",
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Based on http://stackoverflow.com/a/31881491/2230844