Exploratory Data Analysis.ipynb

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      "djhsdbj\n"
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   "source": [
    "import pandas as pd\n",
    "\n",
    "#reading data\n",
    "dfg = pd.read_excel(\"galena1 (4) (1).xlsx\")\n",
    "dfo= pd.read_excel(\"olivine  (1).xlsx\")\n",
    "print(dfg.shape,dfo.shape)\n",
    "print(dfg.columns)\n",
    "print(dfo.columns)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [
    "dfo.describe\n",
    "\n",
    "ppm_columnsg = [col for col in dfg.columns if col.endswith('ppm')]\n",
    "ppm_datag = dfg[ppm_columnsg]\n",
    "import seaborn as sns\n",
    "sns.heatmap(ppm_datag.corr())\n",
    "sns.heatmap;\n"
   ],
   "metadata": {
    "collapsed": false
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   "source": [
    "\n",
    "ppm_columns = [col for col in dfo.columns if col.endswith('ppm')]\n",
    "\n",
    "ppm_data = dfo[ppm_columns]\n",
    "import seaborn as sns\n",
    "sns.heatmap(ppm_data.corr())\n",
    "sns.heatmap;\n"
   ],
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   },
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  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "plt.figure(figsize=(8, 6))\n",
    "sns.histplot(dfg['U_corrected_ppm'], bins=20, kde=True)\n",
    "plt.title('Uranium Distribution')\n",
    "plt.xlabel('U_corrected_ppm')\n",
    "plt.ylabel('analyses')\n",
    "plt.show()\n"
   ],
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   "source": [
    "fig, (ax1, ax2) = plt.subplots(nrows=1, ncols=2\n",
    "                               , figsize=(18, 4))\n",
    "ax1.plot(dfg['Start time'], dfg['Th_corrected_ppm'])\n",
    "ax1.set_xlabel('time')\n",
    "ax1.set_ylabel('Th')\n",
    "ax1.set_title('Time Series Analysis of Thorium Galena')\n",
    "\n",
    "ax2.plot(dfg['Start time'], dfg['U_corrected_ppm'])\n",
    "ax2.set_xlabel('time')\n",
    "ax2.set_ylabel('U')\n",
    "ax2.set_title('Time Series Analysis of Uranium Galena')\n"
   ],
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   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [
    "\n",
    "correlation_matrix = data.corr()\n",
    "plt.figure(figsize=(10, 8))\n",
    "sns.heatmap(correlation_matrix, annot=True, cmap='coolwarm')\n",
    "plt.title('Correlation Heatmap')\n",
    "plt.show()\n",
    "correlation_matrix = dfg.corr()\n",
    "plt.figure(figsize=(10, 8))\n",
    "sns.heatmap(correlation_matrix, annot=True, cmap='coolwarm')\n",
    "plt.title('Correlation Matrix')\n",
    "plt.show()"
   ],
   "metadata": {
    "collapsed": false
   },
   "id": "b22bc4ea376b74a"
  }
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