From f7cadbc2a10a7a59975fdadf8ffa2abd985d9c4e Mon Sep 17 00:00:00 2001
From: Saisri Vegesna <saisri@uab.edu>
Date: Mon, 30 Mar 2020 11:02:33 -0500
Subject: [PATCH] Upload New File

---
 importSACCTinfo.ipynb | 160 ++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 160 insertions(+)
 create mode 100644 importSACCTinfo.ipynb

diff --git a/importSACCTinfo.ipynb b/importSACCTinfo.ipynb
new file mode 100644
index 0000000..8ec103c
--- /dev/null
+++ b/importSACCTinfo.ipynb
@@ -0,0 +1,160 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2020-03-16T20:57:10.405006Z",
+     "start_time": "2020-03-16T20:56:55.837670Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "import pandas_profiling"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2020-03-16T20:57:11.865980Z",
+     "start_time": "2020-03-16T20:57:10.414986Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "df = pd.read_csv('userusage.txt',delimiter='|')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2020-03-16T20:57:11.932878Z",
+     "start_time": "2020-03-16T20:57:11.905219Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "df.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2020-03-16T20:57:14.154962Z",
+     "start_time": "2020-03-16T20:57:11.967976Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "df[['jid','step']] = df.JobID.str.split(\".\",expand=True) \n",
+    "df.Partition.values"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "ExecuteTime": {
+     "start_time": "2020-03-16T20:56:57.392Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "batchDF=df.dropna(subset=[\"MaxRSS\"])\n",
+    "userDF=df.dropna(subset=[\"User\"])\n",
+    "for jid in df.jid.unique():\n",
+    "    userDF['MaxRSS'][userDF['jid'] == jid]=batchDF['MaxRSS'][batchDF['jid'] == jid]\n",
+    "    \n",
+    "    #print(userDF[userDF['jid'] == jid])\n",
+    "    \n",
+    "userDF.head()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# add more graphs here\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.5"
+  },
+  "toc": {
+   "base_numbering": 1,
+   "nav_menu": {},
+   "number_sections": true,
+   "sideBar": true,
+   "skip_h1_title": false,
+   "title_cell": "Table of Contents",
+   "title_sidebar": "Contents",
+   "toc_cell": false,
+   "toc_position": {},
+   "toc_section_display": true,
+   "toc_window_display": false
+  },
+  "varInspector": {
+   "cols": {
+    "lenName": 16,
+    "lenType": 16,
+    "lenVar": 40
+   },
+   "kernels_config": {
+    "python": {
+     "delete_cmd_postfix": "",
+     "delete_cmd_prefix": "del ",
+     "library": "var_list.py",
+     "varRefreshCmd": "print(var_dic_list())"
+    },
+    "r": {
+     "delete_cmd_postfix": ") ",
+     "delete_cmd_prefix": "rm(",
+     "library": "var_list.r",
+     "varRefreshCmd": "cat(var_dic_list()) "
+    }
+   },
+   "types_to_exclude": [
+    "module",
+    "function",
+    "builtin_function_or_method",
+    "instance",
+    "_Feature"
+   ],
+   "window_display": false
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
-- 
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