{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Tutorial"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Import modules"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Import generic modules\n",
    "import matplotlib\n",
    "import networkx as nx\n",
    "import pandas as pd\n",
    "import seaborn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Import the platform_analysis libraries\n",
    "import platform_analysis.github_analysis as github\n",
    "import platform_analysis.sna as sna"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Render our plots inline\n",
    "%matplotlib inline "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Clear font cache for matplotlib\n",
    "font_cache_path = matplotlib.get_cachedir() + '/fontList.cache'\n",
    "%rm $font_cache_path\n",
    "# Set the font\n",
    "matplotlib.rcParams.update({'font.family': 'Hack'})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Get and save the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Configuration\n",
    "repository=\"fablabs\"\n",
    "username=\"fablabbcn\"\n",
    "userlogin = \"xxxx\"\n",
    "password = \"xxxx\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Get the data from GitHub\n",
    "repo = github.github_analysis(\n",
    "    repository=repository,\n",
    "    username=username,\n",
    "    userlogin=userlogin,\n",
    "    password=password,\n",
    "    path=\"/Users/xxxx/Documents\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Load the data, in case we already have it\n",
    "# repo = nx.read_graphml(\"fablabs.graphml\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Save data without self-loops\n",
    "sna.save_graph(repo, \"fablabs.graphml\", self_loops=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Remove self-loops (a user interacting with herself/himself)\n",
    "self_loops_edges = repo.selfloop_edges(keys=True, data=True)\n",
    "repo.remove_edges_from(self_loops_edges)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Transform the graph data into pandas time series\n",
    "data = sna.graph_to_pandas_time_series(repo)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
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       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>fablabbcn</td>\n",
       "      <td>&lt;github.NamedUser.NamedUser object at 0x110282...</td>\n",
       "      <td>92929804</td>\n",
       "      <td>[API] fix travis ruby 2.2.2</td>\n",
       "      <td>pull request assignee</td>\n",
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       "      <td>1</td>\n",
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       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>fablabbcn</td>\n",
       "      <td>fablabbcn/fablabs</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>repository creation</td>\n",
       "      <td>2016-01-01</td>\n",
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       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Lomascolo</td>\n",
       "      <td>fablabbcn</td>\n",
       "      <td>5</td>\n",
       "      <td>Lomascolo/fablabs</td>\n",
       "      <td>fork</td>\n",
       "      <td>2016-01-01</td>\n",
       "      <td>2016-05-20 13:00:58</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>annawb</td>\n",
       "      <td>fablabbcn</td>\n",
       "      <td>1</td>\n",
       "      <td>annawb/fablabs</td>\n",
       "      <td>fork</td>\n",
       "      <td>2016-01-01</td>\n",
       "      <td>2016-12-19 04:20:44</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           0                                                  1      node  \\\n",
       "0  fablabbcn  <github.NamedUser.NamedUser object at 0x110282...  92929804   \n",
       "1  fablabbcn  <github.NamedUser.NamedUser object at 0x1109ce...  92931798   \n",
       "2  fablabbcn                                  fablabbcn/fablabs      None   \n",
       "3  Lomascolo                                          fablabbcn         5   \n",
       "4     annawb                                          fablabbcn         1   \n",
       "\n",
       "                           msg                   type    endopen  \\\n",
       "0  [API] fix travis ruby 2.2.2  pull request assignee 2016-01-01   \n",
       "1     [API] fix travis rake db  pull request assignee 2016-01-01   \n",
       "2                         None    repository creation 2016-01-01   \n",
       "3            Lomascolo/fablabs                   fork 2016-01-01   \n",
       "4               annawb/fablabs                   fork 2016-01-01   \n",
       "\n",
       "                start value  \n",
       "0 2016-11-09 09:34:51     1  \n",
       "1 2016-11-09 09:48:24     1  \n",
       "2 2013-10-16 20:04:34     1  \n",
       "3 2016-05-20 13:00:58     1  \n",
       "4 2016-12-19 04:20:44     1  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Do a first time series analysis\n",
    "time_data = sna.time_analysis(data=data, focus=\"global\", interaction=\"0\", structure=\"separated\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>commit</th>\n",
       "      <th>issue comment</th>\n",
       "      <th>issue assignation</th>\n",
       "      <th>fork</th>\n",
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       "      <th>2016-12-03 16:07:20</th>\n",
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      "text/plain": [
       "                    commit issue comment issue assignation fork  \\\n",
       "2016-12-03 16:07:20      0             1                 0    0   \n",
       "2016-11-09 09:34:51      0             0                 0    0   \n",
       "2016-11-09 09:48:24      0             0                 0    0   \n",
       "2013-10-16 20:04:34      0             0                 0    0   \n",
       "2016-05-20 13:00:58      0             0                 0    1   \n",
       "\n",
       "                    merged pull request pull request assignee  \\\n",
       "2016-12-03 16:07:20                   0                     0   \n",
       "2016-11-09 09:34:51                   0                     1   \n",
       "2016-11-09 09:48:24                   0                     1   \n",
       "2013-10-16 20:04:34                   0                     0   \n",
       "2016-05-20 13:00:58                   0                     0   \n",
       "\n",
       "                    repository creation  \n",
       "2016-12-03 16:07:20                   0  \n",
       "2016-11-09 09:34:51                   0  \n",
       "2016-11-09 09:48:24                   0  \n",
       "2013-10-16 20:04:34                   1  \n",
       "2016-05-20 13:00:58                   0  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "time_data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## All users - Graph visualization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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N6VqfPn0oNzeXbGxsVDzy+Ph4sre3V2r/22+/0eXLl8nDw6PIAn3s2DGqV68e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\nRUQyTEVeRCTD/gfC5RMA8mtAHgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10d10f090>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the global graph, for all users\n",
    "pos=nx.spring_layout(repo,iterations=100)\n",
    "nx.draw_networkx(repo,pos,node_size=50,with_labels=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## All users - Time visualization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Group interactions by type\n",
    "global_stats = sna.type_stats(data=time_data, focus=\"global\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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frKpfnqOevfrs0L6/+u3Eeqrq9qr6hWH97xza9OdOC9if/qyqtlfVX1fVz+5D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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10d09edd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot generic stats of interaction types\n",
    "plot = global_stats.plot(kind=\"bar\", figsize=(20,6), title=\"Interactions over time in \"+username+\" / \"+repository)\n",
    "plot.set_xlabel(\"Interactions\")\n",
    "plot.set_ylabel(\"Amount\")\n",
    "plot.set_xticklabels(global_stats.index, rotation=0)\n",
    "matplotlib.pyplot.savefig(\"results-01.pdf\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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zZ85k5cqVNDQ0dBvHt771LRobG5k2bRqrVq3i7rvvpqysrE/xdNWvpKQknnnm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JHCkRBCCCHEMXrvhZfJ2+rBqmzsDm7mdkcO7bbMZKclxCFhnARJ4WnjyxS7YrT7KvDYM9hw+8KE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\nRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10de8c4d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot interactions over time, by type (monthly resample)\n",
    "plot = time_data.resample('M').sum().plot(kind=\"area\", figsize=(20,6), title=\"Interactions over time in \"+username+\" / \"+repository)\n",
    "# Axes\n",
    "plot.set_xlabel(\"Time\")\n",
    "plot.set_ylabel(\"Interactions\")\n",
    "# Time format for x axis\n",
    "xticks = pd.date_range(start=time_data.index.min(), end=time_data.index.max(), freq='4M')\n",
    "plot.set_xticklabels([x.strftime('%h\\n%Y') for x in xticks]);\n",
    "plot.set_xticks(xticks)\n",
    "plot.grid('on', which='major', axis='x')\n",
    "matplotlib.pyplot.savefig(\"results-02.pdf\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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Dh7scDiLcbr70D+BhLy+tg/7dSLwDa+2vrLV3WGsTgU3Ay9barcBnQDKQA5wE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5BtepR2FaXXiRK3o6TcEP60jjep45zpxM2boOHgwcLAfvFPAxuPsvCc+N7QnyYebPxk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\niIiIiKTu/wFCBq9qgssncgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1093233d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot interactions over time, by type (quarterly resample)\n",
    "plot = time_data.resample('Q').sum().plot(kind=\"area\", figsize=(20,6), title=\"Interactions over time in \"+username+\" / \"+repository)\n",
    "# Axes\n",
    "plot.set_xlabel(\"Time\")\n",
    "plot.set_ylabel(\"Interactions\")\n",
    "# Time format for x axis\n",
    "xticks = pd.date_range(start=time_data.index.min(), end=time_data.index.max(), freq='4M')\n",
    "plot.set_xticklabels([x.strftime('%h\\n%Y') for x in xticks]);\n",
    "plot.set_xticks(xticks)\n",
    "plot.grid('on', which='major', axis='x')\n",
    "# Plot interactions over time, by type (yearly resample)\n",
    "matplotlib.pyplot.savefig(\"results-03.pdf\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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vvqkuZUJN9nE99NBD/OhHP6KoqOiKrquUUkoppZRS6tqRONZC+/Ya7KP9RFMx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Dp+7nxJsUlEROQIOdB33NuAy4Ba4EM+ik4h4D8ncF4iIiIichxKhGKsXbycynAhU301tA+30Tn0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\njAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x109d678d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot interactions over time, by type (yearly resample)\n",
    "plot = time_data.resample('A').sum().plot(kind=\"area\", figsize=(20,6), title=\"Interactions over time in \"+username+\" / \"+repository)\n",
    "# Axes\n",
    "plot.set_xlabel(\"Time\")\n",
    "plot.set_ylabel(\"Interactions\")\n",
    "# Time format for x axis\n",
    "xticks = pd.date_range(start=time_data.index.min(), end=time_data.index.max(), freq='12M')\n",
    "plot.set_xticklabels([x.strftime('%Y') for x in xticks]);\n",
    "plot.set_xticks(xticks)\n",
    "plot.grid('on', which='major', axis='x')\n",
    "matplotlib.pyplot.savefig(\"results-04.pdf\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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ZpGlbTDWdUotWb+S0Kx/gJ/e9XNHvDMrq+iqltFsX1r0GODmltCYi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\n8N73vpczzzyTm266iTPPPJMlS5Yc8vjh6jnppJP4+te/zgUXXMCXvvQ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      "text/plain": [
       "<matplotlib.figure.Figure at 0x10a38c510>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot interactions over time, split by type (monthly resample)\n",
    "plot = time_data.resample('M').sum().plot(label=(\"X\", \"Y\"), subplots=True, legend=True, kind=\"area\", sharex=True, sharey=True, ylim=(0, 150), figsize=(40,20))\n",
    "\n",
    "ax = plot.flatten()\n",
    "# Time format for x axis\n",
    "xticks = pd.date_range(start=time_data.index.min(), end=time_data.index.max(), freq='4M')\n",
    "\n",
    "for i in plot:\n",
    "    i.set_ylabel(\"Interactions\")\n",
    "    i.set_xlabel(\"Time\")\n",
    "    ax[0].set_xticklabels([x.strftime('%h\\n%Y') for x in xticks]);\n",
    "    ax[0].set_xticks(xticks)\n",
    "    ax[0].grid('on', which='major', axis='x')\n",
    "    i.set_ylim(0,45)\n",
    "\n",
    "matplotlib.pyplot.suptitle(\"Activity over time in \"+username+\" / \"+repository, size=26, y=0.925)\n",
    "matplotlib.pyplot.savefig(\"results-05.pdf\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Combine all the interactions together\n",
    "time_data_combined = sna.time_analysis(data=data, focus=\"global\", interaction=\"0\", structure=\"combined\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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ijqlrJZIkSZIkSS1sYrrE7rEpejO1xintr9bh2MuAuyPiu8DozIUppY/XpSpJ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\nEKcAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1095a54d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot interactions over time (monthly resample)\n",
    "plot = time_data_combined.resample('M').sum().plot(kind=\"area\", figsize=(20,6), title=\"Interactions over time in \"+username+\" / \"+repository)\n",
    "# Axes\n",
    "plot.set_xlabel(\"Time\")\n",
    "plot.set_ylabel(\"Interactions\")\n",
    "# Time format for x axis\n",
    "xticks = pd.date_range(start=time_data.index.min(), end=time_data.index.max(), freq='4M')\n",
    "plot.set_xticklabels([x.strftime('%h\\n%Y') for x in xticks]);\n",
    "plot.set_xticks(xticks)\n",
    "plot.grid('on', which='major', axis='x')\n",
    "matplotlib.pyplot.savefig(\"results-06.pdf\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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1ducAKBTbc2gdHGT1ugo3Aj+OiDVAAKcC/7NmVUmSJEmSJDWxrp4cHZkgb+h0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\nAa3MOXJqTzzyAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10a10ba10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot interactions over time (quarterly resample)\n",
    "plot = time_data_combined.resample('Q').sum().plot(kind=\"area\", figsize=(20,6), title=\"Interactions over time in \"+username+\" / \"+repository)\n",
    "# Axes\n",
    "plot.set_xlabel(\"Time\")\n",
    "plot.set_ylabel(\"Interactions\")\n",
    "# Time format for x axis\n",
    "xticks = pd.date_range(start=time_data.index.min(), end=time_data.index.max(), freq='4M')\n",
    "plot.set_xticklabels([x.strftime('%h\\n%Y') for x in xticks]);\n",
    "plot.set_xticks(xticks)\n",
    "plot.grid('on', which='major', axis='x')\n",
    "matplotlib.pyplot.savefig(\"results-07.pdf\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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/bAIom4AHZX+mptVMkjQnDJ0kSZIkLWp7Do+xrnaI/vogm7Yfplm0qZS75VjV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\nIjNfOzdLkiRJ0lJ0YmKKWzf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qo+uQJKmVdfeV+dHTq7l1znL2dPfTFhAB/ZVmVyZJkiSN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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1095ad0d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot interactions over time (yearly resample)\n",
    "plot = time_data_combined.resample('A').sum().plot(kind=\"area\", figsize=(20,6), title=\"Interactions over time in \"+username+\" / \"+repository)\n",
    "# Axes\n",
    "plot.set_xlabel(\"Time\")\n",
    "plot.set_ylabel(\"Interactions\")\n",
    "# Time format for x axis\n",
    "xticks = pd.date_range(start=time_data.index.min(), end=time_data.index.max(), freq='4M')\n",
    "plot.set_xticklabels([x.strftime('%h\\n%Y') for x in xticks]);\n",
    "plot.set_xticks(xticks)\n",
    "plot.grid('on', which='major', axis='x')\n",
    "matplotlib.pyplot.savefig(\"results-08.pdf\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Single users - Data visualisation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Get data of single users\n",
    "user_data = sna.time_analysis(data=data, focus=\"user\", interaction=\"0\", structure=\"separated\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>commit</th>\n",
       "      <th>issue comment</th>\n",
       "      <th>issue assignation</th>\n",
       "      <th>fork</th>\n",
       "      <th>merged pull request</th>\n",
       "      <th>pull request assignee</th>\n",
       "      <th>repository creation</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>nnnnicholas</th>\n",
       "      <th>2016-12-03 16:07:20</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">fablabbcn</th>\n",
       "      <th>2016-11-09 09:34:51</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-11-09 09:48:24</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-10-16 20:04:34</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lomascolo</th>\n",
       "      <th>2016-05-20 13:00:58</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                commit issue comment issue assignation fork  \\\n",
       "nnnnicholas 2016-12-03 16:07:20      0             1                 0    0   \n",
       "fablabbcn   2016-11-09 09:34:51      0             0                 0    0   \n",
       "            2016-11-09 09:48:24      0             0                 0    0   \n",
       "            2013-10-16 20:04:34      0             0                 0    0   \n",
       "Lomascolo   2016-05-20 13:00:58      0             0                 0    1   \n",
       "\n",
       "                                merged pull request pull request assignee  \\\n",
       "nnnnicholas 2016-12-03 16:07:20                   0                     0   \n",
       "fablabbcn   2016-11-09 09:34:51                   0                     1   \n",
       "            2016-11-09 09:48:24                   0                     1   \n",
       "            2013-10-16 20:04:34                   0                     0   \n",
       "Lomascolo   2016-05-20 13:00:58                   0                     0   \n",
       "\n",
       "                                repository creation  \n",
       "nnnnicholas 2016-12-03 16:07:20                   0  \n",
       "fablabbcn   2016-11-09 09:34:51                   0  \n",
       "            2016-11-09 09:48:24                   0  \n",
       "            2013-10-16 20:04:34                   1  \n",
       "Lomascolo   2016-05-20 13:00:58                   0  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "user_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python2.7/site-packages/ipykernel/__main__.py:2: DeprecationWarning: \n",
      ".ix is deprecated. Please use\n",
      ".loc for label based indexing or\n",
      ".iloc for positional indexing\n",
      "\n",
      "See the documentation here:\n",
      "http://pandas.pydata.org/pandas-docs/stable/indexing.html#ix-indexer-is-deprecated\n",
      "  from ipykernel import kernelapp as app\n"
     ]
    },
    {
     "data": {
      "image/png": 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Ehoayb9++Luelq3gun/Pp06c73KrmbtypU6fygx/8gPr6epqbm9m9ezevvvpq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\nSHAEAAAAwKD/D0PfLHUnl356AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x108ca0490>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot interactions of @ceritium user over time, by type (monthly resample)\n",
    "plot = user_data.ix[\"ceritium\"].resample('M').sum().plot(kind=\"area\", figsize=(20,6), ylim=(0,40), title=\"Interactions over time of @ceritium in \"+username+\" / \"+repository)\n",
    "# Axes\n",
    "plot.set_xlabel(\"Time\")\n",
    "plot.set_ylabel(\"Interactions\")\n",
    "# Time format for x axis\n",
    "xticks = pd.date_range(start=time_data.index.min(), end=time_data.index.max(), freq='4M')\n",
    "plot.set_xticklabels([x.strftime('%h\\n%Y') for x in xticks]);\n",
    "plot.set_xticks(xticks)\n",
    "plot.grid('on', which='major', axis='x')\n",
    "matplotlib.pyplot.savefig(\"results-09.pdf\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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5L2SJI+fcD4EfeoNZCJzCszl2EVCIZ3Psq4A3QxWDiIiIiIiIiIi0XyhXHF3AOVdjZg8C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OeygzJfHe1k8Vx0Dv8ZvQIfMWbYtqMLSefbdvzmelyrdfO+WjgSEREREUlje2lgOhCLRBhRUMa+\nlkp+mdOL8yJE0lTUn8V3hl569PKclo18MlxPoW8YxZlljAtOxe/8tPxyG5XtSzkU3U/meYXM//zf\nkpmV5WHlA98b/3If5wQvYOPhtyjOeZXAAFrJiDmjwpXHF4qi03nHTSRCBrm0M9f3Hp/0L6HNZbI2\nNpHHYpcTiZ2++Ch+NjKOjbH4kZ8FNDPXKii0Vva64dwV+QQ/51MU0sx83wYu863nUv8GSq2uX/bR\nk6fbzD4G3J64eLNz7lUv6hARERERSXevZA/lWmBk1jgCviwORffzbtZMr8sSGfRW5E1hRaeYo1vq\nX2S05VLkH0FJdhmluWNgF+z81qvUtFVzOPMgU66/komzFbLd2dI7/z+T8mZQ1boLc8aswpVel0SN\nG8KS2DSWRKezNDaNOgoAmGqVfNb/EoXWxpZoGctj5/FabFavx2skyFvuvERgu2Mc1Yy1/ZgZq2KT\neS42FyIwyfawwLe+T0K2O0v6wpGZZQJ3AXOALGCxmU10zsWSXYuIiIiISLpblT2Z5o4GRuSMIhLr\noChQ4nVJIinpjqJjRyOVdhziq/VvU2hDGJ5Zyui8cs72TSb2ZCvr/vg4teFqOsocC75yI8HCAg+r\n9taBrZsZtncUIWvD7wvxkdIfelJHyGWwJjaJNxKnnx0JtR5GI/N9G5joq6I2VsAqN4UHotcC/XnU\nprGDMna4MnCQSZgLbDPDrZE6l8/D0Q9zf/QvyCJ8XMj2BNvX45BtL444mgOsB+YCh4E9wExgjQe1\niIiIiIikvYZwPcFAIbXt1SyL7gdGeV2SSEqrDgzjX4suOXr5+oY3udA5hvhKKM4q45yCmdAMB374\nNhsSIdslH5rMRZ/4mIdVJ9/Wu5YyNm8iGxuXcNGQe09/hz7iHOw8IdS6jWwCnUKtfebYEC3nldgF\nPBObl7TaThQmkzVucuJoJBjJISb59iZCtsv4YeTv+CHxkO1L/RtY4FvPfF/FGYVse7FwNBI4AEwn\nvnB05J1JC0ciIiIiIh5oiNQxinJqw/u4d8gFXpcjknb+VDibPyV+9kdDfLf+OYosEbKdXcqYjHGw\nEiqWLqIuVEOMbn0Z1qCWYZmUByexuXE9T2bns9q3EPrmzKtT2rKnhG+Hf87eTqHWH/ctpcxXx+5Y\ncZeh1gPJfoaxPzYMOBayPcpXRxuZPB+dzaPRDx0N2Xbc0q3HNOd6nsDdE2b2V8CHgV1AKzAb+KNz\n7plO23wB+ELi4nTiRyglWyHQoDH7zVnA7iSPmU7PrxfjetFTSJ++6rWaemN6NW669NSTcf0FxdP8\nOQUZLsn/gxVtOujz5w9P6mn/LtRqlpWb1P30YkyvxvWip2XhkL8gK49NLpLUT6Tp9Luk12rqjZuM\nngZd2Irx+bL8OQA0tjdTkB3szyG75MW4je3N5GRmku3fk7Qx9zZEOavQR5gMGl0eTeTS4jJjztGv\nv1vJ+P3NsJgFLeQroIV8a2P7oQ4aQ+70J7A555L6D5gP/Bm4DrgaeB244BTb1ya7xsS492nMfh03\n6X1Ns+fXi33VazXFxvSqr2n2/KbFazXNnl+9VlNsTA/3NS166uHzq9dqio3p4b6mRU89fH7ToqcD\n/fn14lS1lcC5wFvEw7HHAGtPsf3hZBTVhWc1Zr/yoq/p9Px6Ma5eq6k3Jui1morjpktPvRpXr9XU\nG9OrcdOlp16Nq9dq6o3p1bjp0lOvxk2XnsIAfn6TfqoagJl9GjgSh36zc+4DizWz1c65C5NTmSSL\n+pp61NPUpL6mHvU0NamvqUc9TU3qa+pRT1OPenoyL444wjn3KPBoNze/rz9rEc+or6lHPU1N6mvq\nUU9Tk/qaetTT1KS+ph71NPWopyfw5IgjEREREREREREZ+HxeFyAicipmNs3M1pnZbjP75Sm2y09s\nV2dmn0pmjSIiqUjzr4iIdzQHy0AyIBaOzOxjZvaumW0wsy92Y/vfm9nQZNQmPWNmlYl+rkv8++gp\ntm1OZm3Sc919A+tLzrkNzrkZwHdPs11TYrtnklFXqtD8m3o0/6Ymzb+pSXNw6tEcnHq8mH9Bc3B/\n0/x7ZjzJOOrMzILAL4FZQAh418wWOef2n+Ju8xkgi15ySh9yzh30ugjpO865DcAMM/sc4FlgnJk1\nO+eCiZ9fB25xzq32qp7BSvNvStP8m2I0/6YezcEpTXNwChko8y9oDu4rmn/P3EDY8TnAWudcrXOu\nEVgMLDCzuWa20swqzGwxgJldZWbrgDJgcWLlt8zD2uUMmNlCM1tlZu+Y2c+Ov8l+k+h10lbxpW90\n/muZmb1uZhcmfq42s38zs41m9hvvKpRT0PybJjT/pibNv4Oe5uA0oTk49Wj+HfQ0/56hgbBwNBI4\n0OlyTeK6PwL/2zl3HvB5AOfcq4nD8KqIr+TPcM5VJbtg6bYjL6x1ZlZC/DDLy5xzs4BhZrYgsV0u\n8BgwHTi/0/UyuI0kfsjsDODqdJxgBwHNv6lL82960/w7OGgOTl2ag9OX5t/BQfPvGRoIC0ddMWBv\n4rBAnHM7Pa5HeubIC2sG8VXds4HliRXbucC4xHZR4DXnXAx4FbjAk2qlr4Wdc2855zqAncQn497I\nIH4oKUDnr4PMPGE7fVVk72j+TQ2af9Ob5t/BS3NwatAcnL76ev4FzcHJovn3FDzPOAL2AyM6XS4B\n2jyqRfqPAS855/6mG9tq0hv4uvMG1tHpZ0cPFqrN7HJgg3PuEPG/xm1J3NRoZmOBdmDaCXc7BIw6\n07HSlObf9KD5N7Vo/k0dmoPTg+bg1JGU+Rc0ByeB5t8zNBCOOFoBzDSzYjPLBy4HHgRGmdk0ADMb\nc8J9Gok3VwaPt4mfNzoawMzOMrPSxG1+4Eoz8wFXAas8qlFOwcwuN7NhiYvTif8VBRJvYGY2gpPf\nwHqrCHjTzDYAU4FHEtf/O7AcuA84MRDw18D/SRwe7mmA4SCg+Tc9aP4d5DT/pizNwelBc/Ag5tH8\nC5qD+5vm3zPk+RFHzrlmM/sy8BrxFfl/d87tMrNPA/eZWQ5wmHgzj/gV8KyZNQHXpuM5hoONc67G\nzL4APG1m2cRXya8HqoHaxM+/IP4XmWXeVSqncOQNLEr8nODvJK4/8ga2mpPfwHrFOfcU8FQX198N\n3P0B99lG/7yBpxzNv+lB829K0PybgjQHpwfNwYNe0udf0Bzc3zT/njlzTkdEioiIiIiIiIjIyQbC\nqWoiIiIiIiIiIjIAaeFIRERERERERES6pIUjERERERERERHpkicLR2Y20czWmNmmROr7VYnrP2Zm\n6xP/ruq0/R1mdsDMKjpdN8TMVprZO4nH6M5XXEo/6Yuedrot38yqzOyWZO6DnEx9TT3qaWrqq76a\nWTRx/3Vm9otk74cco56mJvU19fRhT6cn7v++mT2e7P2Q46mvqUc97R1PwrHN7Cwg1zm3ycymEk8z\nHwtsAeYAWcBiYKJzLmZmlwBh4EHn3HmJx8gAshOJ6EOBzUCpcy6S9B2SPulpp8f6CfGvnXzDOXdH\nMvdDjqe+ph71NDX1VV/NrNk5F0z+HsiJ1NPUpL6mnj76XOMj/lnmRufcUjMb6pyr82J/JE59TT3q\nae94csSRc263c25T4uImoBCYC6xP/HccsAeYmdh+OXDwhMeIOOeaExcLgRCgr4jzSF/0FMDMJgHF\nwJoklC2nob6mHvU0NfVVX2XgUE9Tk/qaevqopxcDtc65pYlt0uKD6ECmvqYe9bR3BkLG0aeA14ES\n4AAwPfFvPzDqVHe0+GkSG4CNwJedc9H+LVW6qcc9BX4CfL8/i5MeU19Tj3qamnrT16zEYdxLzexD\n/VqlnAn1NDWpr6mnpz0dCxwws+cSp8B8ub8LlTOivqYe9fQMZXg5uJmdDfwAuJr44WEAMbpZl3Ou\nCZiW+Mv382b2aqejkMQDvempmS0EtjjndplZ/xUpZ0x9TT3qaWrq7fsqUOacqzWzC4FFZjbBOdfe\nD6VKN6mnqUl9TT297GkMuBKYBhwGVpvZC8657f1Rq3Sf+pp61NOe8eyIIzPLBx4Hvuic2wVUAaVA\nBfEjiEYC+7rzWM65LcBu4lkb4pE+6Okc4JNmtgn4MvAvptBzz6mvqUc9TU198b7qnKtN/Hc1UA2U\n92PJchrqaWpSX1NPH/T0APCec26Xc64BWA1M7t+q5XTU19SjnvacJ0ccJYKtHwX+n3Pu9cTVK4Fz\ngbeIB1ONAdae4jFGA63OuTozG0m8YTv6s275YH3RU+fct4FvJx7vNqDZOfeH/qtaTkd9TT3qaWrq\no/fVoUCbc67NzMqBMuLn+osH1NPUpL6mnr7oKfA2MNLMhgFNxI9m2NZfNcvpqa+pRz3tHa9OVbsa\nuBwoM7NvJq77CPANYGni8k3OuRiAmd0DfAIYbmZ7gX8kvtr3OzOLAgZ83Tmn8EDv9Lqnzrlnkluy\ndIP6mnrU09TUF++rh4CHzKwNiAJfcM61JG8X5ATqaWpSX1NPn7yvmtktwKtAAPjPxBkV4h31NfWo\np71gzumLyERERERERERE5GQD4VvVRERERERERERkANLCkYiIiIiIiIiIdEkLRyIiIiIiIiIi0iUt\nHImIiIiIiIiISJe0cCQiIiIiIiIiIl3SwpGIiIjIBzCzh81snZntN7N9iZ9/nbjtu2Z2rdc1ioiI\niPQnc855XYOIiIjIgGZmtwHNzrk7vK5FREREJJl0xJGIiIjIGTKze8ys1sw+1+m628zsNTPbbma/\nSvx3auK2hWa2yszeMbOfeVa4iIiIyBnK8LoAERERkcHGOfclM+vqsO1FwFigBvg5cJWZHQS+C1zm\nnGs1s4fMbIFzbkkSSxYRERHpES0ciYiIiPSdJqCZ+MIRwBhgDnA2sNzMAHKBxYAWjkRERGTA08KR\niIiISM90JyjSDxjwknPub/q5HhEREZE+p4wjERERkZ6pIX5E0em8DSwws9EAZnaWmZX2a2UiIiIi\nfUQLRyIiIiI98zvgE2b2rpld+kEbOedqgC8AT5vZRuApID9JNYqIiIj0ijnXnaOsRUREREREREQk\n3eiIIxERERERERER6ZIWjkREREREREREpEtaOBIRERERERERkS5p4UhERERERERERLqkhSMRERER\nEREREemSFo5ERERERERERKRLWjgSEREREREREZEuaeFIRERERERERES69D+eQhSkCx8wOgAAAABJ\nRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10a8d5450>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot interactions of @hiromipaw user over time, by type (monthly resample)\n",
    "plot = user_data.ix[\"hiromipaw\"].resample('M').sum().plot(kind=\"area\", ylim=(0,40), figsize=(20,6), title=\"Interactions over time of @hiromipaw in \"+username+\" / \"+repository)\n",
    "# Axes\n",
    "plot.set_xlabel(\"Time\")\n",
    "plot.set_ylabel(\"Interactions\")\n",
    "# Time format for x axis\n",
    "xticks = pd.date_range(start=time_data.index.min(), end=time_data.index.max(), freq='4M')\n",
    "plot.set_xticklabels([x.strftime('%h\\n%Y') for x in xticks]);\n",
    "plot.set_xticks(xticks)\n",
    "plot.grid('on', which='major', axis='x')\n",
    "matplotlib.pyplot.savefig(\"results-10.pdf\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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vVfsXPE/mOOdKPEufM71/yoAvhDgGERERERERERHpgohQdWxmM4FPnXPFZtbc7P1vU3tj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\nexx9Fzi9mYFIkiRJkiR1gr4NUKmWWdDXwwl7Sqw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      "text/plain": [
       "<matplotlib.figure.Figure at 0x10b49f810>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot interactions of @openp2pdesign user over time, by type (monthly resample)\n",
    "plot = user_data.ix[\"openp2pdesign\"].resample('M').sum().plot(kind=\"area\", ylim=(0,40), figsize=(20,6), title=\"Interactions over time of @openp2pdesign in \"+username+\" / \"+repository)\n",
    "# Axes\n",
    "plot.set_xlabel(\"Time\")\n",
    "plot.set_ylabel(\"Interactions\")\n",
    "# Time format for x axis\n",
    "xticks = pd.date_range(start=time_data.index.min(), end=time_data.index.max(), freq='4M')\n",
    "plot.set_xticklabels([x.strftime('%h\\n%Y') for x in xticks]);\n",
    "plot.set_xticks(xticks)\n",
    "plot.grid('on', which='major', axis='x')\n",
    "matplotlib.pyplot.savefig(\"results-11.pdf\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>commit</th>\n",
       "      <th>issue comment</th>\n",
       "      <th>issue assignation</th>\n",
       "      <th>fork</th>\n",
       "      <th>merged pull request</th>\n",
       "      <th>pull request assignee</th>\n",
       "      <th>repository creation</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2016-12-06 17:50:49</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-14 17:22:06</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-11-04 16:44:09</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-21 17:19:21</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-11-26 16:48:51</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    commit issue comment issue assignation fork  \\\n",
       "2016-12-06 17:50:49      1             0                 0    0   \n",
       "2016-12-14 17:22:06      0             0                 1    0   \n",
       "2016-11-04 16:44:09      0             0                 1    0   \n",
       "2016-12-21 17:19:21      0             1                 0    0   \n",
       "2016-11-26 16:48:51      0             1                 0    0   \n",
       "\n",
       "                    merged pull request pull request assignee  \\\n",
       "2016-12-06 17:50:49                   0                     0   \n",
       "2016-12-14 17:22:06                   0                     0   \n",
       "2016-11-04 16:44:09                   0                     0   \n",
       "2016-12-21 17:19:21                   0                     0   \n",
       "2016-11-26 16:48:51                   0                     0   \n",
       "\n",
       "                    repository creation  \n",
       "2016-12-06 17:50:49                   0  \n",
       "2016-12-14 17:22:06                   0  \n",
       "2016-11-04 16:44:09                   0  \n",
       "2016-12-21 17:19:21                   0  \n",
       "2016-11-26 16:48:51                   0  "
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check @openp2pdesign data table (only first rows)\n",
    "user_data.ix[\"openp2pdesign\"].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>commit</th>\n",
       "      <th>issue comment</th>\n",
       "      <th>issue assignation</th>\n",
       "      <th>fork</th>\n",
       "      <th>merged pull request</th>\n",
       "      <th>pull request assignee</th>\n",
       "      <th>repository creation</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>67</td>\n",
       "      <td>67</td>\n",
       "      <td>67</td>\n",
       "      <td>67</td>\n",
       "      <td>67</td>\n",
       "      <td>67</td>\n",
       "      <td>67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>unique</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>top</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>freq</th>\n",
       "      <td>49</td>\n",
       "      <td>45</td>\n",
       "      <td>64</td>\n",
       "      <td>67</td>\n",
       "      <td>66</td>\n",
       "      <td>67</td>\n",
       "      <td>67</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        commit  issue comment  issue assignation  fork  merged pull request  \\\n",
       "count       67             67                 67    67                   67   \n",
       "unique       2              2                  2     1                    2   \n",
       "top          0              1                  0     0                    0   \n",
       "freq        49             45                 64    67                   66   \n",
       "\n",
       "        pull request assignee  repository creation  \n",
       "count                      67                   67  \n",
       "unique                      1                    1  \n",
       "top                         0                    0  \n",
       "freq                       67                   67  "
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check @openp2pdesign stats data table\n",
    "user_data.ix[\"openp2pdesign\"].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>commit</th>\n",
       "      <th>issue comment</th>\n",
       "      <th>issue assignation</th>\n",
       "      <th>fork</th>\n",
       "      <th>merged pull request</th>\n",
       "      <th>pull request assignee</th>\n",
       "      <th>repository creation</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>332</td>\n",
       "      <td>332</td>\n",
       "      <td>332</td>\n",
       "      <td>332</td>\n",
       "      <td>332</td>\n",
       "      <td>332</td>\n",
       "      <td>332</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>unique</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>top</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>freq</th>\n",
       "      <td>218</td>\n",
       "      <td>240</td>\n",
       "      <td>323</td>\n",
       "      <td>326</td>\n",
       "      <td>327</td>\n",
       "      <td>330</td>\n",
       "      <td>331</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        commit  issue comment  issue assignation  fork  merged pull request  \\\n",
       "count      332            332                332   332                  332   \n",
       "unique       2              2                  2     2                    2   \n",
       "top          1              0                  0     0                    0   \n",
       "freq       218            240                323   326                  327   \n",
       "\n",
       "        pull request assignee  repository creation  \n",
       "count                     332                  332  \n",
       "unique                      2                    2  \n",
       "top                         0                    0  \n",
       "freq                      330                  331  "
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# All users stats\n",
    "user_data.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>commit</th>\n",
       "      <th>issue comment</th>\n",
       "      <th>issue assignation</th>\n",
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       "      <th>repository creation</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>nnnnicholas</th>\n",
       "      <th>2016-12-03 16:07:20</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">fablabbcn</th>\n",
       "      <th>2016-11-09 09:34:51</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-11-09 09:48:24</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-10-16 20:04:34</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lomascolo</th>\n",
       "      <th>2016-05-20 13:00:58</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fablab-catania</th>\n",
       "      <th>2016-12-19 13:48:57</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Aldo23</th>\n",
       "      <th>2016-12-21 11:37:34</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">Fablabimpact</th>\n",
       "      <th>2016-06-01 19:35:17</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-07-26 13:26:07</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">pral2a</th>\n",
       "      <th>2015-09-28 16:18:35</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-09-28 18:17:29</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-14 14:30:34</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>lespacedunmatin</th>\n",
       "      <th>2016-05-31 09:57:03</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>annawb</th>\n",
       "      <th>2016-12-19 04:20:44</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">tomasdiez</th>\n",
       "      <th>2015-10-08 10:15:57</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-10-08 10:46:34</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-10-08 10:13:37</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">Hiromi</th>\n",
       "      <th>2015-09-07 17:03:12</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-06-08 15:48:12</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-06-08 15:41:36</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">wendwarge</th>\n",
       "      <th>2016-12-21 22:56:02</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-22 00:23:25</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-22 00:36:23</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-22 02:30:51</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-25 02:03:03</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>waagsociety</th>\n",
       "      <th>2016-01-15 09:03:53</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">TheBeachLab</th>\n",
       "      <th>2016-12-03 05:40:17</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-03 13:01:23</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-05 05:06:57</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-11-15 11:03:34</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"21\" valign=\"top\">openp2pdesign</th>\n",
       "      <th>2016-12-14 17:14:41</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-11-16 10:53:06</th>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>2016-10-27 15:00:39</th>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>2016-10-26 15:43:20</th>\n",
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       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>2016-10-27 14:37:14</th>\n",
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       "    <tr>\n",
       "      <th>2016-10-25 13:07:22</th>\n",
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       "    <tr>\n",
       "      <th>2016-12-14 16:16:15</th>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>2016-10-28 08:23:59</th>\n",
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       "    <tr>\n",
       "      <th>2016-12-06 18:48:18</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-10-27 17:27:44</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-11-21 19:39:42</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>2016-12-14 11:38:18</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-11-22 09:02:49</th>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>2016-11-21 19:31:22</th>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>2016-12-14 15:47:58</th>\n",
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       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-11-23 16:25:29</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>2016-12-14 15:34:22</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-10-28 08:05:47</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-15 17:56:20</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-15 11:25:45</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-14 18:43:07</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Texs</th>\n",
       "      <th>2016-07-04 04:24:55</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5N44P</th>\n",
       "      <th>2016-07-27 01:42:03</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">waldooo</th>\n",
       "      <th>2016-12-14 19:13:11</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-14 19:01:55</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-14 18:48:02</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-15 16:18:24</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">maujabur</th>\n",
       "      <th>2016-12-14 19:09:21</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-14 18:51:56</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-14 18:41:39</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>332 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                    commit issue comment issue assignation  \\\n",
       "nnnnicholas     2016-12-03 16:07:20      0             1                 0   \n",
       "fablabbcn       2016-11-09 09:34:51      0             0                 0   \n",
       "                2016-11-09 09:48:24      0             0                 0   \n",
       "                2013-10-16 20:04:34      0             0                 0   \n",
       "Lomascolo       2016-05-20 13:00:58      0             0                 0   \n",
       "fablab-catania  2016-12-19 13:48:57      0             0                 0   \n",
       "Aldo23          2016-12-21 11:37:34      0             1                 0   \n",
       "Fablabimpact    2016-06-01 19:35:17      0             0                 0   \n",
       "                2016-07-26 13:26:07      0             1                 0   \n",
       "pral2a          2015-09-28 16:18:35      0             0                 0   \n",
       "                2015-09-28 18:17:29      1             0                 0   \n",
       "                2015-12-14 14:30:34      0             0                 1   \n",
       "lespacedunmatin 2016-05-31 09:57:03      0             1                 0   \n",
       "annawb          2016-12-19 04:20:44      0             0                 0   \n",
       "tomasdiez       2015-10-08 10:15:57      0             1                 0   \n",
       "                2015-10-08 10:46:34      0             1                 0   \n",
       "                2015-10-08 10:13:37      0             1                 0   \n",
       "Hiromi          2015-09-07 17:03:12      1             0                 0   \n",
       "                2015-06-08 15:48:12      1             0                 0   \n",
       "                2015-06-08 15:41:36      1             0                 0   \n",
       "wendwarge       2016-12-21 22:56:02      0             1                 0   \n",
       "                2016-12-22 00:23:25      0             1                 0   \n",
       "                2016-12-22 00:36:23      0             1                 0   \n",
       "                2016-12-22 02:30:51      0             1                 0   \n",
       "                2016-05-25 02:03:03      0             1                 0   \n",
       "waagsociety     2016-01-15 09:03:53      0             0                 0   \n",
       "TheBeachLab     2016-12-03 05:40:17      0             0                 1   \n",
       "                2016-12-03 13:01:23      0             1                 0   \n",
       "                2016-12-05 05:06:57      0             1                 0   \n",
       "                2016-11-15 11:03:34      0             1                 0   \n",
       "...                                    ...           ...               ...   \n",
       "openp2pdesign   2016-12-14 17:14:41      1             0                 0   \n",
       "                2016-11-16 10:53:06      1             0                 0   \n",
       "                2016-10-27 15:00:39      0             1                 0   \n",
       "                2016-10-26 15:43:20      0             1                 0   \n",
       "                2016-10-27 14:37:14      0             1                 0   \n",
       "                2016-10-25 13:07:22      0             0                 1   \n",
       "                2016-12-14 16:16:15      0             0                 0   \n",
       "                2016-10-28 08:23:59      0             1                 0   \n",
       "                2016-12-06 18:48:18      1             0                 0   \n",
       "                2016-10-27 17:27:44      1             0                 0   \n",
       "                2016-11-21 19:39:42      1             0                 0   \n",
       "                2016-12-14 11:38:18      1             0                 0   \n",
       "                2016-11-22 09:02:49      1             0                 0   \n",
       "                2016-11-21 19:31:22      1             0                 0   \n",
       "                2016-12-14 15:47:58      0             1                 0   \n",
       "                2016-11-23 16:25:29      0             1                 0   \n",
       "                2016-12-14 15:34:22      0             1                 0   \n",
       "                2016-10-28 08:05:47      0             1                 0   \n",
       "                2016-12-15 17:56:20      0             1                 0   \n",
       "                2016-12-15 11:25:45      0             1                 0   \n",
       "                2016-12-14 18:43:07      0             1                 0   \n",
       "Texs            2016-07-04 04:24:55      0             0                 0   \n",
       "5N44P           2016-07-27 01:42:03      0             1                 0   \n",
       "waldooo         2016-12-14 19:13:11      0             1                 0   \n",
       "                2016-12-14 19:01:55      0             1                 0   \n",
       "                2016-12-14 18:48:02      0             1                 0   \n",
       "                2016-12-15 16:18:24      0             1                 0   \n",
       "maujabur        2016-12-14 19:09:21      0             1                 0   \n",
       "                2016-12-14 18:51:56      0             1                 0   \n",
       "                2016-12-14 18:41:39      0             1                 0   \n",
       "\n",
       "                                    fork merged pull request  \\\n",
       "nnnnicholas     2016-12-03 16:07:20    0                   0   \n",
       "fablabbcn       2016-11-09 09:34:51    0                   0   \n",
       "                2016-11-09 09:48:24    0                   0   \n",
       "                2013-10-16 20:04:34    0                   0   \n",
       "Lomascolo       2016-05-20 13:00:58    1                   0   \n",
       "fablab-catania  2016-12-19 13:48:57    1                   0   \n",
       "Aldo23          2016-12-21 11:37:34    0                   0   \n",
       "Fablabimpact    2016-06-01 19:35:17    1                   0   \n",
       "                2016-07-26 13:26:07    0                   0   \n",
       "pral2a          2015-09-28 16:18:35    0                   1   \n",
       "                2015-09-28 18:17:29    0                   0   \n",
       "                2015-12-14 14:30:34    0                   0   \n",
       "lespacedunmatin 2016-05-31 09:57:03    0                   0   \n",
       "annawb          2016-12-19 04:20:44    1                   0   \n",
       "tomasdiez       2015-10-08 10:15:57    0                   0   \n",
       "                2015-10-08 10:46:34    0                   0   \n",
       "                2015-10-08 10:13:37    0                   0   \n",
       "Hiromi          2015-09-07 17:03:12    0                   0   \n",
       "                2015-06-08 15:48:12    0                   0   \n",
       "                2015-06-08 15:41:36    0                   0   \n",
       "wendwarge       2016-12-21 22:56:02    0                   0   \n",
       "                2016-12-22 00:23:25    0                   0   \n",
       "                2016-12-22 00:36:23    0                   0   \n",
       "                2016-12-22 02:30:51    0                   0   \n",
       "                2016-05-25 02:03:03    0                   0   \n",
       "waagsociety     2016-01-15 09:03:53    1                   0   \n",
       "TheBeachLab     2016-12-03 05:40:17    0                   0   \n",
       "                2016-12-03 13:01:23    0                   0   \n",
       "                2016-12-05 05:06:57    0                   0   \n",
       "                2016-11-15 11:03:34    0                   0   \n",
       "...                                  ...                 ...   \n",
       "openp2pdesign   2016-12-14 17:14:41    0                   0   \n",
       "                2016-11-16 10:53:06    0                   0   \n",
       "                2016-10-27 15:00:39    0                   0   \n",
       "                2016-10-26 15:43:20    0                   0   \n",
       "                2016-10-27 14:37:14    0                   0   \n",
       "                2016-10-25 13:07:22    0                   0   \n",
       "                2016-12-14 16:16:15    0                   1   \n",
       "                2016-10-28 08:23:59    0                   0   \n",
       "                2016-12-06 18:48:18    0                   0   \n",
       "                2016-10-27 17:27:44    0                   0   \n",
       "                2016-11-21 19:39:42    0                   0   \n",
       "                2016-12-14 11:38:18    0                   0   \n",
       "                2016-11-22 09:02:49    0                   0   \n",
       "                2016-11-21 19:31:22    0                   0   \n",
       "                2016-12-14 15:47:58    0                   0   \n",
       "                2016-11-23 16:25:29    0                   0   \n",
       "                2016-12-14 15:34:22    0                   0   \n",
       "                2016-10-28 08:05:47    0                   0   \n",
       "                2016-12-15 17:56:20    0                   0   \n",
       "                2016-12-15 11:25:45    0                   0   \n",
       "                2016-12-14 18:43:07    0                   0   \n",
       "Texs            2016-07-04 04:24:55    1                   0   \n",
       "5N44P           2016-07-27 01:42:03    0                   0   \n",
       "waldooo         2016-12-14 19:13:11    0                   0   \n",
       "                2016-12-14 19:01:55    0                   0   \n",
       "                2016-12-14 18:48:02    0                   0   \n",
       "                2016-12-15 16:18:24    0                   0   \n",
       "maujabur        2016-12-14 19:09:21    0                   0   \n",
       "                2016-12-14 18:51:56    0                   0   \n",
       "                2016-12-14 18:41:39    0                   0   \n",
       "\n",
       "                                    pull request assignee repository creation  \n",
       "nnnnicholas     2016-12-03 16:07:20                     0                   0  \n",
       "fablabbcn       2016-11-09 09:34:51                     1                   0  \n",
       "                2016-11-09 09:48:24                     1                   0  \n",
       "                2013-10-16 20:04:34                     0                   1  \n",
       "Lomascolo       2016-05-20 13:00:58                     0                   0  \n",
       "fablab-catania  2016-12-19 13:48:57                     0                   0  \n",
       "Aldo23          2016-12-21 11:37:34                     0                   0  \n",
       "Fablabimpact    2016-06-01 19:35:17                     0                   0  \n",
       "                2016-07-26 13:26:07                     0                   0  \n",
       "pral2a          2015-09-28 16:18:35                     0                   0  \n",
       "                2015-09-28 18:17:29                     0                   0  \n",
       "                2015-12-14 14:30:34                     0                   0  \n",
       "lespacedunmatin 2016-05-31 09:57:03                     0                   0  \n",
       "annawb          2016-12-19 04:20:44                     0                   0  \n",
       "tomasdiez       2015-10-08 10:15:57                     0                   0  \n",
       "                2015-10-08 10:46:34                     0                   0  \n",
       "                2015-10-08 10:13:37                     0                   0  \n",
       "Hiromi          2015-09-07 17:03:12                     0                   0  \n",
       "                2015-06-08 15:48:12                     0                   0  \n",
       "                2015-06-08 15:41:36                     0                   0  \n",
       "wendwarge       2016-12-21 22:56:02                     0                   0  \n",
       "                2016-12-22 00:23:25                     0                   0  \n",
       "                2016-12-22 00:36:23                     0                   0  \n",
       "                2016-12-22 02:30:51                     0                   0  \n",
       "                2016-05-25 02:03:03                     0                   0  \n",
       "waagsociety     2016-01-15 09:03:53                     0                   0  \n",
       "TheBeachLab     2016-12-03 05:40:17                     0                   0  \n",
       "                2016-12-03 13:01:23                     0                   0  \n",
       "                2016-12-05 05:06:57                     0                   0  \n",
       "                2016-11-15 11:03:34                     0                   0  \n",
       "...                                                   ...                 ...  \n",
       "openp2pdesign   2016-12-14 17:14:41                     0                   0  \n",
       "                2016-11-16 10:53:06                     0                   0  \n",
       "                2016-10-27 15:00:39                     0                   0  \n",
       "                2016-10-26 15:43:20                     0                   0  \n",
       "                2016-10-27 14:37:14                     0                   0  \n",
       "                2016-10-25 13:07:22                     0                   0  \n",
       "                2016-12-14 16:16:15                     0                   0  \n",
       "                2016-10-28 08:23:59                     0                   0  \n",
       "                2016-12-06 18:48:18                     0                   0  \n",
       "                2016-10-27 17:27:44                     0                   0  \n",
       "                2016-11-21 19:39:42                     0                   0  \n",
       "                2016-12-14 11:38:18                     0                   0  \n",
       "                2016-11-22 09:02:49                     0                   0  \n",
       "                2016-11-21 19:31:22                     0                   0  \n",
       "                2016-12-14 15:47:58                     0                   0  \n",
       "                2016-11-23 16:25:29                     0                   0  \n",
       "                2016-12-14 15:34:22                     0                   0  \n",
       "                2016-10-28 08:05:47                     0                   0  \n",
       "                2016-12-15 17:56:20                     0                   0  \n",
       "                2016-12-15 11:25:45                     0                   0  \n",
       "                2016-12-14 18:43:07                     0                   0  \n",
       "Texs            2016-07-04 04:24:55                     0                   0  \n",
       "5N44P           2016-07-27 01:42:03                     0                   0  \n",
       "waldooo         2016-12-14 19:13:11                     0                   0  \n",
       "                2016-12-14 19:01:55                     0                   0  \n",
       "                2016-12-14 18:48:02                     0                   0  \n",
       "                2016-12-15 16:18:24                     0                   0  \n",
       "maujabur        2016-12-14 19:09:21                     0                   0  \n",
       "                2016-12-14 18:51:56                     0                   0  \n",
       "                2016-12-14 18:41:39                     0                   0  \n",
       "\n",
       "[332 rows x 7 columns]"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# All users data\n",
    "user_data"
   ]
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