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   "source": [
    "# `unique` und andere Mengenlogik\n",
    "\n",
    "NumPy hat einige grundlegende Mengenoperationen für eindimensionale `ndarray`. Eine häufig verwendete ist [numpy.unique](https://numpy.org/doc/stable/reference/generated/numpy.unique.html), die die sortierten eindeutigen Werte in einem Array zurückgibt:"
   ]
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   "source": [
    "import numpy as np\n",
    "\n",
    "\n",
    "names = np.array(\n",
    "    [\n",
    "        \"Andrea\",\n",
    "        \"Tim\",\n",
    "        \"Veit\",\n",
    "        \"Tim\",\n",
    "    ],\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "254fa327",
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    "execution": {
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     "shell.execute_reply.started": "2026-05-21T17:16:37.802495Z"
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Andrea', 'Tim', 'Veit'], dtype='<U6')"
      ]
     },
     "execution_count": 2,
     "metadata": {},
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    }
   ],
   "source": [
    "np.unique(names)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cfa62a8b",
   "metadata": {},
   "source": [
    "Mit [numpy.in1d](https://numpy.org/doc/stable/reference/generated/numpy.in1d.html) lässt sich die Zugehörigkeit der Werte in einem eindimensionalen Array zu einem anderen Array überprüfen wobei ein boolesches Array zurückgegeben wird:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "0453a0d0",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-05-21T17:16:37.806428Z",
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     "shell.execute_reply.started": "2026-05-21T17:16:37.806418Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([False,  True, False,  True])"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.isin(names, [\"Tim\", \"Tom\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f6a96506",
   "metadata": {},
   "source": [
    "Array-Mengenoperationen:\n",
    "    \n",
    "Methode | Beschreibung\n",
    ":------ | :-----------\n",
    "`unique(x)` | berechnet die sortierten, eindeutigen Elemente in `x`\n",
    "`intersect1d(x, y)` | berechnet die sortierten, gemeinsamen Elemente in `x` und `y`\n",
    "`union1d(x, y)` | berechnet die sortierte Vereinigung von Elementen\n",
    "`in1d(x, y)` | berechnet ein boolesches Array, das angibt, ob jedes Element von `x` in `y` enthalten ist\n",
    "`setdiff1d(x, y)` | setzt die Differenz der Elemente in `x`, die nicht in `y` enthalten sind\n",
    "`setxor1d(x, y)` | setzt symmetrische Differenzen; Elemente, die in einem der Arrays enthalten sind, aber nicht in beiden"
   ]
  }
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