Transposition and mean calculation.ipynb

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   "source": [
    "import numpy as np"
   ]
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       "array([[70, 39, 98],\n",
       "       [38, 58, 32],\n",
       "       [88, 11, 59],\n",
       "       [95, 30, 53],\n",
       "       [32, 43, 48]])"
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    "arr = np.random.randint(10,100,size=(5,3))\n",
    "arr"
   ]
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      "text/plain": [
       "array([[70, 38, 88, 95, 32],\n",
       "       [39, 58, 11, 30, 43],\n",
       "       [98, 32, 59, 53, 48]])"
      ]
     },
     "execution_count": 3,
     "metadata": {},
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   "source": [
    "arr_transposed = arr.T\n",
    "arr_transposed"
   ]
  },
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   "cell_type": "code",
   "execution_count": 7,
   "id": "7a16f96a-5675-4648-851e-252a14f70093",
   "metadata": {},
   "outputs": [],
   "source": [
    "mean_original = np.mean(arr)\n",
    "mean_transposed = np.mean(arr_transposed)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
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   "id": "7191ae81-bd56-460b-8cfc-0d33445bc51d",
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       "52.93333333333333"
      ]
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     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
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   "source": [
    "mean_original"
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   "cell_type": "code",
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    {
     "data": {
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       "52.93333333333333"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "mean_transposed"
   ]
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