{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from datetime import datetime\n",
    "import sqlite3\n",
    "import matplotlib.dates as mdates\n",
    "import matplotlib.ticker as ticker\n",
    "plt.rcParams[\"figure.figsize\"] = [9,7]\n",
    "xformatter = mdates.DateFormatter('%H:%M')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "memdata = pd.read_sql(\"select * from memdata\", conn)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "df0['datetime'] = pd.to_datetime(df0['datetime'].values, format='%Y-%m-%dT%H:%M:%S')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['id', 'datetime', 'memtotal', 'memfree', 'memavailable', 'cached',\n",
       "       'shmem', 'slab', 'slabreclaim', 'slabunreclaim'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df0.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "df0.set_index('datetime', inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "df0 = df0*1024"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
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      "text/plain": [
       "                              id    memtotal    memfree  memavailable  \\\n",
       "datetime                                                                \n",
       "2019-05-19 10:44:15.844731  1024  3973554176  130129920     986411008   \n",
       "2019-05-19 10:50:01.192920  2048  3973554176  144433152     895578112   \n",
       "2019-05-19 11:00:01.567269  3072  3973554176  130367488     795430912   \n",
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       "2019-05-19 11:20:01.925553  5120  3973554176  110137344     571715584   \n",
       "\n",
       "                               cached      shmem       slab  slabreclaim  \\\n",
       "datetime                                                                   \n",
       "2019-05-19 10:44:15.844731  978976768  180330496  230416384    118751232   \n",
       "2019-05-19 10:50:01.192920  927420416  190787584  228651008    115900416   \n",
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       "2019-05-19 11:20:01.925553  758460416  210411520  225923072    109891584   \n",
       "\n",
       "                            slabunreclaim  \n",
       "datetime                                   \n",
       "2019-05-19 10:44:15.844731      111665152  \n",
       "2019-05-19 10:50:01.192920      112750592  \n",
       "2019-05-19 11:00:01.567269      113610752  \n",
       "2019-05-19 11:10:02.194191      115175424  \n",
       "2019-05-19 11:20:01.925553      116031488  "
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df0.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
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       "                                     id       memtotal       memfree  \\\n",
       "datetime                                                               \n",
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       "\n",
       "                             memavailable         cached         shmem  \\\n",
       "datetime                                                                 \n",
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       "\n",
       "                                    slab   slabreclaim  slabunreclaim  \n",
       "datetime                                                               \n",
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     },
     "execution_count": 9,
     "metadata": {},
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   "source": [
    "df0*1024"
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  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
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       "      <td>3973558272</td>\n",
       "      <td>269463552</td>\n",
       "      <td>753762304</td>\n",
       "      <td>1280094208</td>\n",
       "      <td>662769664</td>\n",
       "      <td>181096448</td>\n",
       "      <td>73850880</td>\n",
       "      <td>107245568</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-08 15:50:01.916257</th>\n",
       "      <td>10825728</td>\n",
       "      <td>3973558272</td>\n",
       "      <td>201850880</td>\n",
       "      <td>699731968</td>\n",
       "      <td>1286873088</td>\n",
       "      <td>657145856</td>\n",
       "      <td>181952512</td>\n",
       "      <td>73850880</td>\n",
       "      <td>108101632</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-08 16:00:01.266988</th>\n",
       "      <td>10826752</td>\n",
       "      <td>3973558272</td>\n",
       "      <td>140877824</td>\n",
       "      <td>640536576</td>\n",
       "      <td>1287700480</td>\n",
       "      <td>657092608</td>\n",
       "      <td>182956032</td>\n",
       "      <td>73850880</td>\n",
       "      <td>109105152</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-08 16:10:01.679254</th>\n",
       "      <td>10827776</td>\n",
       "      <td>3973558272</td>\n",
       "      <td>169533440</td>\n",
       "      <td>581693440</td>\n",
       "      <td>1199665152</td>\n",
       "      <td>655917056</td>\n",
       "      <td>183824384</td>\n",
       "      <td>73699328</td>\n",
       "      <td>110125056</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                  id    memtotal    memfree  memavailable  \\\n",
       "datetime                                                                    \n",
       "2020-01-08 15:30:02.052835  10823680  3973558272  273547264     705220608   \n",
       "2020-01-08 15:40:01.541794  10824704  3973558272  269463552     753762304   \n",
       "2020-01-08 15:50:01.916257  10825728  3973558272  201850880     699731968   \n",
       "2020-01-08 16:00:01.266988  10826752  3973558272  140877824     640536576   \n",
       "2020-01-08 16:10:01.679254  10827776  3973558272  169533440     581693440   \n",
       "\n",
       "                                cached      shmem       slab  slabreclaim  \\\n",
       "datetime                                                                    \n",
       "2020-01-08 15:30:02.052835  1235865600  667635712  179814400     73654272   \n",
       "2020-01-08 15:40:01.541794  1280094208  662769664  181096448     73850880   \n",
       "2020-01-08 15:50:01.916257  1286873088  657145856  181952512     73850880   \n",
       "2020-01-08 16:00:01.266988  1287700480  657092608  182956032     73850880   \n",
       "2020-01-08 16:10:01.679254  1199665152  655917056  183824384     73699328   \n",
       "\n",
       "                            slabunreclaim  \n",
       "datetime                                   \n",
       "2020-01-08 15:30:02.052835      106160128  \n",
       "2020-01-08 15:40:01.541794      107245568  \n",
       "2020-01-08 15:50:01.916257      108101632  \n",
       "2020-01-08 16:00:01.266988      109105152  \n",
       "2020-01-08 16:10:01.679254      110125056  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df0.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['id', 'memtotal', 'memfree', 'memavailable', 'cached', 'shmem', 'slab',\n",
       "       'slabreclaim', 'slabunreclaim'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df0.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axis.YAxis at 0x7f2f3360c710>"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = df0.plot(y=['memavailable', 'cached', 'shmem'], kind='line')\n",
    "ax.yaxis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>memtotal</th>\n",
       "      <th>memfree</th>\n",
       "      <th>memavailable</th>\n",
       "      <th>cached</th>\n",
       "      <th>shmem</th>\n",
       "      <th>slab</th>\n",
       "      <th>slabreclaim</th>\n",
       "      <th>slabunreclaim</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1.057400e+04</td>\n",
       "      <td>1.057400e+04</td>\n",
       "      <td>1.057400e+04</td>\n",
       "      <td>1.057400e+04</td>\n",
       "      <td>1.057400e+04</td>\n",
       "      <td>1.057400e+04</td>\n",
       "      <td>1.057400e+04</td>\n",
       "      <td>1.057400e+04</td>\n",
       "      <td>1.057400e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>5.414400e+06</td>\n",
       "      <td>3.973555e+09</td>\n",
       "      <td>2.894226e+08</td>\n",
       "      <td>9.428321e+08</td>\n",
       "      <td>8.590187e+08</td>\n",
       "      <td>1.946622e+08</td>\n",
       "      <td>2.158030e+08</td>\n",
       "      <td>1.015835e+08</td>\n",
       "      <td>1.142196e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>3.125857e+06</td>\n",
       "      <td>3.151707e+03</td>\n",
       "      <td>4.871790e+08</td>\n",
       "      <td>7.467063e+08</td>\n",
       "      <td>3.734221e+08</td>\n",
       "      <td>9.115859e+07</td>\n",
       "      <td>6.333862e+07</td>\n",
       "      <td>7.043661e+07</td>\n",
       "      <td>1.788355e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.024000e+03</td>\n",
       "      <td>3.973550e+09</td>\n",
       "      <td>8.382874e+07</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>2.852045e+07</td>\n",
       "      <td>1.015808e+06</td>\n",
       "      <td>9.179546e+07</td>\n",
       "      <td>3.971482e+07</td>\n",
       "      <td>5.174067e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>2.707712e+06</td>\n",
       "      <td>3.973554e+09</td>\n",
       "      <td>1.221110e+08</td>\n",
       "      <td>3.344435e+08</td>\n",
       "      <td>5.366364e+08</td>\n",
       "      <td>1.374751e+08</td>\n",
       "      <td>1.886259e+08</td>\n",
       "      <td>6.299341e+07</td>\n",
       "      <td>1.035756e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>5.414400e+06</td>\n",
       "      <td>3.973554e+09</td>\n",
       "      <td>1.400709e+08</td>\n",
       "      <td>7.513477e+08</td>\n",
       "      <td>8.163185e+08</td>\n",
       "      <td>1.834988e+08</td>\n",
       "      <td>1.991762e+08</td>\n",
       "      <td>8.169062e+07</td>\n",
       "      <td>1.145569e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>8.121088e+06</td>\n",
       "      <td>3.973558e+09</td>\n",
       "      <td>2.050130e+08</td>\n",
       "      <td>1.349637e+09</td>\n",
       "      <td>1.150944e+09</td>\n",
       "      <td>2.311137e+08</td>\n",
       "      <td>2.223186e+08</td>\n",
       "      <td>1.092055e+08</td>\n",
       "      <td>1.267988e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1.082778e+07</td>\n",
       "      <td>3.973562e+09</td>\n",
       "      <td>3.418722e+09</td>\n",
       "      <td>3.550028e+09</td>\n",
       "      <td>2.160902e+09</td>\n",
       "      <td>1.022800e+09</td>\n",
       "      <td>6.632284e+08</td>\n",
       "      <td>6.010675e+08</td>\n",
       "      <td>1.569792e+08</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 id      memtotal       memfree  memavailable        cached  \\\n",
       "count  1.057400e+04  1.057400e+04  1.057400e+04  1.057400e+04  1.057400e+04   \n",
       "mean   5.414400e+06  3.973555e+09  2.894226e+08  9.428321e+08  8.590187e+08   \n",
       "std    3.125857e+06  3.151707e+03  4.871790e+08  7.467063e+08  3.734221e+08   \n",
       "min    1.024000e+03  3.973550e+09  8.382874e+07  0.000000e+00  2.852045e+07   \n",
       "25%    2.707712e+06  3.973554e+09  1.221110e+08  3.344435e+08  5.366364e+08   \n",
       "50%    5.414400e+06  3.973554e+09  1.400709e+08  7.513477e+08  8.163185e+08   \n",
       "75%    8.121088e+06  3.973558e+09  2.050130e+08  1.349637e+09  1.150944e+09   \n",
       "max    1.082778e+07  3.973562e+09  3.418722e+09  3.550028e+09  2.160902e+09   \n",
       "\n",
       "              shmem          slab   slabreclaim  slabunreclaim  \n",
       "count  1.057400e+04  1.057400e+04  1.057400e+04   1.057400e+04  \n",
       "mean   1.946622e+08  2.158030e+08  1.015835e+08   1.142196e+08  \n",
       "std    9.115859e+07  6.333862e+07  7.043661e+07   1.788355e+07  \n",
       "min    1.015808e+06  9.179546e+07  3.971482e+07   5.174067e+07  \n",
       "25%    1.374751e+08  1.886259e+08  6.299341e+07   1.035756e+08  \n",
       "50%    1.834988e+08  1.991762e+08  8.169062e+07   1.145569e+08  \n",
       "75%    2.311137e+08  2.223186e+08  1.092055e+08   1.267988e+08  \n",
       "max    1.022800e+09  6.632284e+08  6.010675e+08   1.569792e+08  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df0.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['id', 'memtotal', 'memfree', 'memavailable', 'cached', 'shmem', 'slab',\n",
       "       'slabreclaim', 'slabunreclaim'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df0.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2019-05-19 10:44:15.844731', '2019-05-19 10:50:01.192920',\n",
       "               '2019-05-19 11:00:01.567269', '2019-05-19 11:10:02.194191',\n",
       "               '2019-05-19 11:20:01.925553', '2019-05-19 11:30:01.634160',\n",
       "               '2019-05-19 11:40:01.441733', '2019-05-19 11:50:01.930397',\n",
       "               '2019-05-19 12:00:02.001585', '2019-05-19 12:10:01.668564',\n",
       "               ...\n",
       "               '2020-01-08 14:40:01.419043', '2020-01-08 14:50:01.817787',\n",
       "               '2020-01-08 15:00:01.224782', '2020-01-08 15:10:01.888192',\n",
       "               '2020-01-08 15:20:01.343294', '2020-01-08 15:30:02.052835',\n",
       "               '2020-01-08 15:40:01.541794', '2020-01-08 15:50:01.916257',\n",
       "               '2020-01-08 16:00:01.266988', '2020-01-08 16:10:01.679254'],\n",
       "              dtype='datetime64[ns]', name='datetime', length=10574, freq=None)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df0.index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>memtotal</th>\n",
       "      <th>memfree</th>\n",
       "      <th>memavailable</th>\n",
       "      <th>cached</th>\n",
       "      <th>shmem</th>\n",
       "      <th>slab</th>\n",
       "      <th>slabreclaim</th>\n",
       "      <th>slabunreclaim</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>datetime</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2019-09-24 20:10:56.884529</th>\n",
       "      <td>5439488</td>\n",
       "      <td>3973558272</td>\n",
       "      <td>83931136</td>\n",
       "      <td>0</td>\n",
       "      <td>55906304</td>\n",
       "      <td>24227840</td>\n",
       "      <td>200019968</td>\n",
       "      <td>49909760</td>\n",
       "      <td>150110208</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                 id    memtotal   memfree  memavailable  \\\n",
       "datetime                                                                  \n",
       "2019-09-24 20:10:56.884529  5439488  3973558272  83931136             0   \n",
       "\n",
       "                              cached     shmem       slab  slabreclaim  \\\n",
       "datetime                                                                 \n",
       "2019-09-24 20:10:56.884529  55906304  24227840  200019968     49909760   \n",
       "\n",
       "                            slabunreclaim  \n",
       "datetime                                   \n",
       "2019-09-24 20:10:56.884529      150110208  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df0[df0['memavailable']<10000]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = df0[datetime(2019,9,24):datetime(2019,9,25)].plot(title=\"Memory usage on September 24th 2019\", y=['memavailable', 'slab'], kind='line')\n",
    "ax.xaxis.set_major_formatter(xformatter)\n",
    "ax.yaxis.set_major_formatter(ticker.FormatStrFormatter(\"%d\"))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<sqlite3.Connection at 0x7f2f4525a570>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "conn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "df1 = pd.read_sql(\"select datetime, cmdline, sum(resident) as resident, sum(shared) as shared from processdata where datetime > '2019-09-24' and datetime < '2019-09-25' group by datetime, cmdline ;\", conn)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "df1['datetime'] = pd.to_datetime(df1['datetime'].values, format='%Y-%m-%dT%H:%M:%S')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "df1.set_index('datetime', inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Multiply on numeric columns by pagesize\n",
    "pagesize = 4096\n",
    "df1[df1.select_dtypes(include=['number']).columns]*=pagesize"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>cmdline</th>\n",
       "      <th>resident</th>\n",
       "      <th>shared</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>datetime</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2019-09-24 09:00:03.609425</th>\n",
       "      <td>ModemManager</td>\n",
       "      <td>9170944</td>\n",
       "      <td>7782400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-09-24 09:00:03.609425</th>\n",
       "      <td>NetworkManager</td>\n",
       "      <td>15425536</td>\n",
       "      <td>12066816</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-09-24 09:00:03.609425</th>\n",
       "      <td>WebKitNetworkPr</td>\n",
       "      <td>34312192</td>\n",
       "      <td>28729344</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-09-24 09:00:03.609425</th>\n",
       "      <td>WebKitWebProces</td>\n",
       "      <td>74088448</td>\n",
       "      <td>62222336</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-09-24 09:00:03.609425</th>\n",
       "      <td>Xorg</td>\n",
       "      <td>57270272</td>\n",
       "      <td>32378880</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                    cmdline  resident    shared\n",
       "datetime                                                       \n",
       "2019-09-24 09:00:03.609425     ModemManager   9170944   7782400\n",
       "2019-09-24 09:00:03.609425   NetworkManager  15425536  12066816\n",
       "2019-09-24 09:00:03.609425  WebKitNetworkPr  34312192  28729344\n",
       "2019-09-24 09:00:03.609425  WebKitWebProces  74088448  62222336\n",
       "2019-09-24 09:00:03.609425             Xorg  57270272  32378880"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>cmdline</th>\n",
       "      <th>resident</th>\n",
       "      <th>shared</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>datetime</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2019-09-24 09:10:01.533692</th>\n",
       "      <td>chrome</td>\n",
       "      <td>1748746240</td>\n",
       "      <td>1132208128</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-09-24 09:20:01.545650</th>\n",
       "      <td>chrome</td>\n",
       "      <td>1511886848</td>\n",
       "      <td>959361024</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-09-24 09:00:03.609425</th>\n",
       "      <td>chrome</td>\n",
       "      <td>1422888960</td>\n",
       "      <td>1015562240</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-09-24 09:00:03.609425</th>\n",
       "      <td>update-apt-xapi</td>\n",
       "      <td>245092352</td>\n",
       "      <td>23502848</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-09-24 09:00:03.609425</th>\n",
       "      <td>akonadi_imap_re</td>\n",
       "      <td>241811456</td>\n",
       "      <td>190644224</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                    cmdline    resident      shared\n",
       "datetime                                                           \n",
       "2019-09-24 09:10:01.533692           chrome  1748746240  1132208128\n",
       "2019-09-24 09:20:01.545650           chrome  1511886848   959361024\n",
       "2019-09-24 09:00:03.609425           chrome  1422888960  1015562240\n",
       "2019-09-24 09:00:03.609425  update-apt-xapi   245092352    23502848\n",
       "2019-09-24 09:00:03.609425  akonadi_imap_re   241811456   190644224"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.sort_values(by=['resident'], ascending=False).head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "cmdline\n",
       "chrome             1748746240\n",
       "update-apt-xapi     245092352\n",
       "akonadi_imap_re     241811456\n",
       "kded5               240803840\n",
       "mysqld              213643264\n",
       "plasmashell         182763520\n",
       "evolution           156078080\n",
       "dolphin             140320768\n",
       "evolution-calen     129433600\n",
       "apache2             123138048\n",
       "Name: resident, dtype: int64"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.groupby('cmdline')['resident'].max().sort_values(ascending=False).head(n=10)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['chrome', 'update-apt-xapi', 'akonadi_imap_re', 'kded5', 'mysqld'],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "worst = df1.groupby('cmdline')['resident'].max().sort_values(ascending=False).head(n=5).index.values ; worst\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "cmdline\n",
       "chrome             1132208128\n",
       "akonadi_imap_re     190644224\n",
       "kded5               164483072\n",
       "dolphin             111726592\n",
       "plasmashell          90689536\n",
       "Name: shared, dtype: int64"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.groupby('cmdline')['shared'].max().sort_values(ascending=False).head(n=5)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>cmdline</th>\n",
       "      <th>resident</th>\n",
       "      <th>shared</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>datetime</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2019-09-24 09:00:03.609425</th>\n",
       "      <td>akonadi_imap_re</td>\n",
       "      <td>241811456</td>\n",
       "      <td>190644224</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-09-24 09:00:03.609425</th>\n",
       "      <td>chrome</td>\n",
       "      <td>1422888960</td>\n",
       "      <td>1015562240</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-09-24 09:00:03.609425</th>\n",
       "      <td>kded5</td>\n",
       "      <td>240803840</td>\n",
       "      <td>164483072</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-09-24 09:00:03.609425</th>\n",
       "      <td>mysqld</td>\n",
       "      <td>203739136</td>\n",
       "      <td>18927616</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-09-24 09:00:03.609425</th>\n",
       "      <td>update-apt-xapi</td>\n",
       "      <td>245092352</td>\n",
       "      <td>23502848</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                    cmdline    resident      shared\n",
       "datetime                                                           \n",
       "2019-09-24 09:00:03.609425  akonadi_imap_re   241811456   190644224\n",
       "2019-09-24 09:00:03.609425           chrome  1422888960  1015562240\n",
       "2019-09-24 09:00:03.609425            kded5   240803840   164483072\n",
       "2019-09-24 09:00:03.609425           mysqld   203739136    18927616\n",
       "2019-09-24 09:00:03.609425  update-apt-xapi   245092352    23502848"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2 = df1[df1['cmdline'].isin( worst )]\n",
    "df2.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = df2.pivot(columns='cmdline').plot(y=['resident'])\n",
    "ax.xaxis.set_major_formatter(xformatter)\n",
    "ax.yaxis.set_major_formatter(ticker.FormatStrFormatter(\"%d\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = df2.plot(title=\"Ram worst offenders\", y='resident')\n",
    "ax.xaxis.set_major_formatter(xformatter)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f2f4043e780>"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df2.plot(y='shared')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "ename": "IndexError",
     "evalue": "index 6 is out of bounds for axis 0 with size 3",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mIndexError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-31-15d3aff3a4c2>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mdf2\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mloc\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'20190322 08'\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m'20190322 17'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0my\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m6\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/pandas/plotting/_core.py\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m    765\u001b[0m                 \u001b[0mint_y_arg\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mis_integer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0my\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0mint_ylist\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    766\u001b[0m                 \u001b[0;32mif\u001b[0m \u001b[0mint_y_arg\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mholds_integer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 767\u001b[0;31m                     \u001b[0my\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdata_cols\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0my\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    768\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    769\u001b[0m                 \u001b[0mlabel_kw\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mkwargs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"label\"\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0;34m\"label\"\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mkwargs\u001b[0m \u001b[0;32melse\u001b[0m \u001b[0;32mFalse\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m   4289\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   4290\u001b[0m         \u001b[0mkey\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcom\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalues_from_object\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 4291\u001b[0;31m         \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mgetitem\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   4292\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mis_scalar\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mresult\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   4293\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0mpromote\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mresult\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mIndexError\u001b[0m: index 6 is out of bounds for axis 0 with size 3"
     ]
    }
   ],
   "source": [
    "df2.loc['20190322 08':'20190322 17'].plot(y=[1,6])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df2.iloc[:,0:3].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df2['memavailable'] = df0['memavailable']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df2.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df2.loc['20190322 08':'20190322 17'].plot(y=[1,6,10])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "(df2*4).head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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