TestingJupyter.ipynb

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   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "a=np.random.randn(5,10)\n",
    "df=pd.DataFrame(a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
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       "array([[ 0.25667056, -0.54613993, -0.53358287,  1.6901468 ,  1.71452835,\n",
       "         1.06650029,  0.42516294,  0.01132299, -0.8453335 , -0.1417125 ],\n",
       "       [ 0.26840916,  0.63369548,  1.58034111, -2.68132071, -0.34309488,\n",
       "         1.17044296, -1.37417243,  2.03242369, -1.23752365, -0.81402051],\n",
       "       [ 1.67947016, -0.81944661, -2.36651522,  0.24932272, -0.39210187,\n",
       "        -0.24161567, -0.21745463,  0.20701174,  0.03480106, -1.25807151],\n",
       "       [-1.57912305, -0.58028377, -1.74454584, -0.61049945,  0.53314022,\n",
       "         1.51806752,  0.66769863, -0.25394667, -0.67776064, -0.9001706 ],\n",
       "       [ 1.51912649, -0.93449435, -2.01671768,  0.41377538, -1.80908068,\n",
       "        -0.76608966, -2.35199004, -0.27889756, -0.32385296, -1.20976817]])"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a"
   ]
  },
  {
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   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td> 0.256671</td>\n",
       "      <td>-0.546140</td>\n",
       "      <td>-0.533583</td>\n",
       "      <td> 1.690147</td>\n",
       "      <td> 1.714528</td>\n",
       "      <td> 1.066500</td>\n",
       "      <td> 0.425163</td>\n",
       "      <td> 0.011323</td>\n",
       "      <td>-0.845334</td>\n",
       "      <td>-0.141712</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td> 0.268409</td>\n",
       "      <td> 0.633695</td>\n",
       "      <td> 1.580341</td>\n",
       "      <td>-2.681321</td>\n",
       "      <td>-0.343095</td>\n",
       "      <td> 1.170443</td>\n",
       "      <td>-1.374172</td>\n",
       "      <td> 2.032424</td>\n",
       "      <td>-1.237524</td>\n",
       "      <td>-0.814021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td> 1.679470</td>\n",
       "      <td>-0.819447</td>\n",
       "      <td>-2.366515</td>\n",
       "      <td> 0.249323</td>\n",
       "      <td>-0.392102</td>\n",
       "      <td>-0.241616</td>\n",
       "      <td>-0.217455</td>\n",
       "      <td> 0.207012</td>\n",
       "      <td> 0.034801</td>\n",
       "      <td>-1.258072</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-1.579123</td>\n",
       "      <td>-0.580284</td>\n",
       "      <td>-1.744546</td>\n",
       "      <td>-0.610499</td>\n",
       "      <td> 0.533140</td>\n",
       "      <td> 1.518068</td>\n",
       "      <td> 0.667699</td>\n",
       "      <td>-0.253947</td>\n",
       "      <td>-0.677761</td>\n",
       "      <td>-0.900171</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td> 1.519126</td>\n",
       "      <td>-0.934494</td>\n",
       "      <td>-2.016718</td>\n",
       "      <td> 0.413775</td>\n",
       "      <td>-1.809081</td>\n",
       "      <td>-0.766090</td>\n",
       "      <td>-2.351990</td>\n",
       "      <td>-0.278898</td>\n",
       "      <td>-0.323853</td>\n",
       "      <td>-1.209768</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          0         1         2         3         4         5         6  \\\n",
       "0  0.256671 -0.546140 -0.533583  1.690147  1.714528  1.066500  0.425163   \n",
       "1  0.268409  0.633695  1.580341 -2.681321 -0.343095  1.170443 -1.374172   \n",
       "2  1.679470 -0.819447 -2.366515  0.249323 -0.392102 -0.241616 -0.217455   \n",
       "3 -1.579123 -0.580284 -1.744546 -0.610499  0.533140  1.518068  0.667699   \n",
       "4  1.519126 -0.934494 -2.016718  0.413775 -1.809081 -0.766090 -2.351990   \n",
       "\n",
       "          7         8         9  \n",
       "0  0.011323 -0.845334 -0.141712  \n",
       "1  2.032424 -1.237524 -0.814021  \n",
       "2  0.207012  0.034801 -1.258072  \n",
       "3 -0.253947 -0.677761 -0.900171  \n",
       "4 -0.278898 -0.323853 -1.209768  \n",
       "\n",
       "[5 rows x 10 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  }
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