{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"This notebook shows you step by step how you can transform text data from `vmstat` output file into a pandas DataFrame."
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"%less ../datasets/vmstat_loadtest.log"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Data Input\n",
"In this version, I'll guide you through data parsing step by step."
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"data": {
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" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>r b swpd free buff cache si so bi bo in cs us sy id wa st UTC</th>\n",
" </tr>\n",
" </thead>\n",
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" <tr>\n",
" <th>0</th>\n",
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" <td>0 0 6144 2718404 42276 ...</td>\n",
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" <tr>\n",
" <th>3</th>\n",
" <td>0 0 6144 2717652 42276 ...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>0 0 6144 2717652 42276 ...</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" r b swpd free buff cache si so bi bo in cs us sy id wa st UTC\n",
"0 0 0 6144 2720868 41924 ... \n",
"1 0 0 6144 2718404 42276 ... \n",
"2 0 0 6144 2718404 42276 ... \n",
"3 0 0 6144 2717652 42276 ... \n",
"4 0 0 6144 2717652 42276 ... "
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import pandas as pd\n",
"\n",
"raw = pd.read_csv(\"../datasets/vmstat_loadtest.log\", skiprows=1)\n",
"raw.head()"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"['r', 'b', 'swpd', 'free', 'buff', 'cache', 'si', 'so', 'bi', 'bo', 'in', 'cs', 'us', 'sy', 'id', 'wa', 'st', 'UTC']\n"
]
}
],
"source": [
"columns = raw.columns.str.split().values[0]\n",
"print(columns)"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
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" <th>17</th>\n",
" </tr>\n",
" </thead>\n",
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" <td>0</td>\n",
" <td>2019-01-13 16:09:33</td>\n",
" </tr>\n",
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" <th>1</th>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>6144</td>\n",
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" <td>42276</td>\n",
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" <td>0</td>\n",
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" <td>7724</td>\n",
" <td>1</td>\n",
" <td>6</td>\n",
" <td>92</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>2019-01-13 16:09:34</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>6144</td>\n",
" <td>2718404</td>\n",
" <td>42276</td>\n",
" <td>347912</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>44</td>\n",
" <td>1853</td>\n",
" <td>7724</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>94</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>2019-01-13 16:09:35</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>6144</td>\n",
" <td>2717652</td>\n",
" <td>42276</td>\n",
" <td>347912</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>24</td>\n",
" <td>1778</td>\n",
" <td>7022</td>\n",
" <td>1</td>\n",
" <td>3</td>\n",
" <td>95</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>2019-01-13 16:09:36</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>6144</td>\n",
" <td>2717652</td>\n",
" <td>42276</td>\n",
" <td>347912</td>\n",
" <td>0</td>\n",
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" <td>7033</td>\n",
" <td>1</td>\n",
" <td>4</td>\n",
" <td>96</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>2019-01-13 16:09:37</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 \\\n",
"0 0 0 6144 2720868 41924 345548 0 0 29 691 588 541 2 4 93 \n",
"1 0 0 6144 2718404 42276 347908 0 0 1421 116 1789 7724 1 6 92 \n",
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"3 0 0 6144 2717652 42276 347912 0 0 0 24 1778 7022 1 3 95 \n",
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"\n",
" 15 16 17 \n",
"0 1 0 2019-01-13 16:09:33 \n",
"1 1 0 2019-01-13 16:09:34 \n",
"2 0 0 2019-01-13 16:09:35 \n",
"3 0 0 2019-01-13 16:09:36 \n",
"4 0 0 2019-01-13 16:09:37 "
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data = raw.iloc[:,0].str.split(n=len(columns)-1).apply(pd.Series)\n",
"data.head()"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
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" <th>us</th>\n",
" <th>sy</th>\n",
" <th>id</th>\n",
" <th>wa</th>\n",
" <th>st</th>\n",
" <th>UTC</th>\n",
" </tr>\n",
" </thead>\n",
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" <td>0</td>\n",
" <td>0</td>\n",
" <td>2019-01-13 16:09:36</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>6144</td>\n",
" <td>2717652</td>\n",
" <td>42276</td>\n",
" <td>347912</td>\n",
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" <td>0</td>\n",
" <td>0</td>\n",
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" <td>1753</td>\n",
" <td>7033</td>\n",
" <td>1</td>\n",
" <td>4</td>\n",
" <td>96</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>2019-01-13 16:09:37</td>\n",
" </tr>\n",
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"</table>\n",
"</div>"
],
"text/plain": [
" r b swpd free buff cache si so bi bo in cs us sy id \\\n",
"0 0 0 6144 2720868 41924 345548 0 0 29 691 588 541 2 4 93 \n",
"1 0 0 6144 2718404 42276 347908 0 0 1421 116 1789 7724 1 6 92 \n",
"2 0 0 6144 2718404 42276 347912 0 0 0 44 1853 7724 3 3 94 \n",
"3 0 0 6144 2717652 42276 347912 0 0 0 24 1778 7022 1 3 95 \n",
"4 0 0 6144 2717652 42276 347912 0 0 0 20 1753 7033 1 4 96 \n",
"\n",
" wa st UTC \n",
"0 1 0 2019-01-13 16:09:33 \n",
"1 1 0 2019-01-13 16:09:34 \n",
"2 0 0 2019-01-13 16:09:35 \n",
"3 0 0 2019-01-13 16:09:36 \n",
"4 0 0 2019-01-13 16:09:37 "
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data.columns = columns\n",
"data.head()"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
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" <th>us</th>\n",
" <th>sy</th>\n",
" <th>id</th>\n",
" <th>wa</th>\n",
" <th>st</th>\n",
" <th>UTC</th>\n",
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" </thead>\n",
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" <th>1</th>\n",
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" <td>42276</td>\n",
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" <td>0</td>\n",
" <td>1421</td>\n",
" <td>116</td>\n",
" <td>1789</td>\n",
" <td>7724</td>\n",
" <td>1</td>\n",
" <td>6</td>\n",
" <td>92</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>2019-01-13 16:09:34</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>6144</td>\n",
" <td>2718404</td>\n",
" <td>42276</td>\n",
" <td>347912</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>44</td>\n",
" <td>1853</td>\n",
" <td>7724</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>94</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>2019-01-13 16:09:35</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>6144</td>\n",
" <td>2717652</td>\n",
" <td>42276</td>\n",
" <td>347912</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>24</td>\n",
" <td>1778</td>\n",
" <td>7022</td>\n",
" <td>1</td>\n",
" <td>3</td>\n",
" <td>95</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>2019-01-13 16:09:36</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>6144</td>\n",
" <td>2717652</td>\n",
" <td>42276</td>\n",
" <td>347912</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>20</td>\n",
" <td>1753</td>\n",
" <td>7033</td>\n",
" <td>1</td>\n",
" <td>4</td>\n",
" <td>96</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>2019-01-13 16:09:37</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" r b swpd free buff cache si so bi bo in cs us sy \\\n",
"0 0 0 6144 2720868 41924 345548 0 0 29 691 588 541 2 4 \n",
"1 0 0 6144 2718404 42276 347908 0 0 1421 116 1789 7724 1 6 \n",
"2 0 0 6144 2718404 42276 347912 0 0 0 44 1853 7724 3 3 \n",
"3 0 0 6144 2717652 42276 347912 0 0 0 24 1778 7022 1 3 \n",
"4 0 0 6144 2717652 42276 347912 0 0 0 20 1753 7033 1 4 \n",
"\n",
" id wa st UTC \n",
"0 93 1 0 2019-01-13 16:09:33 \n",
"1 92 1 0 2019-01-13 16:09:34 \n",
"2 94 0 0 2019-01-13 16:09:35 \n",
"3 95 0 0 2019-01-13 16:09:36 \n",
"4 96 0 0 2019-01-13 16:09:37 "
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"vmstat = data.iloc[:,:-1].apply(pd.to_numeric)\n",
"vmstat['UTC'] = pd.to_datetime(data['UTC'])\n",
"vmstat.head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Data Selection"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
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" <td>92</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>94</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>1</td>\n",
" <td>3</td>\n",
" <td>95</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>1</td>\n",
" <td>4</td>\n",
" <td>96</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" us sy id wa st\n",
"0 2 4 93 1 0\n",
"1 1 6 92 1 0\n",
"2 3 3 94 0 0\n",
"3 1 3 95 0 0\n",
"4 1 4 96 0 0"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"cpu = vmstat[['us','sy','id','wa', 'st']]\n",
"cpu.head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Visualization"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"image/png": {
"height": 250,
"width": 377
},
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"%matplotlib inline\n",
"cpu.plot.area();"
]
}
],
"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": "3.6.4"
}
},
"nbformat": 4,
"nbformat_minor": 2
}