numismatic_distribution.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Numismatic Distribution in Imperial Roman Africa Shown Through Social Network Analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Abstract"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Roman Africa is a large and diverse region that enjoyed quite high productivity and stability, especially in the first two centuries CE. Despite the great tradition of archaeological research on material remains, little attention has been paid to numismatic records. The purpose of this study is to apply SNA methods for the first time in numismatics to investigate the presence of interesting similarities in the distribution of coin types across the four Roman provinces of Africa and to understand the integration and hierarchy of settlements over time. The study, conducted on 32,292 coins found in hoards at 50 African sites between 23 BC and 275 CE, confirms trends already known to scholars. However, it also brought to light that the economy was not very integrated and hierarchical, but rather quite distributed in its centrality and with steady hubs over time, which allows for further research."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "What follows is the Network Analysis workflow."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data Analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Importing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Catalogue</th>\n",
       "      <th>Region</th>\n",
       "      <th>Findspot</th>\n",
       "      <th>Province</th>\n",
       "      <th>Type</th>\n",
       "      <th>Denomination</th>\n",
       "      <th>Weight</th>\n",
       "      <th>Year_min</th>\n",
       "      <th>Year_max</th>\n",
       "      <th>Mint_Year</th>\n",
       "      <th>Circulation</th>\n",
       "      <th>Terminal_date</th>\n",
       "      <th>Mint</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Gafsa</td>\n",
       "      <td>Proconsularis</td>\n",
       "      <td>hoard</td>\n",
       "      <td>sestertius</td>\n",
       "      <td>21.07</td>\n",
       "      <td>104</td>\n",
       "      <td>111</td>\n",
       "      <td>108.0</td>\n",
       "      <td>152.0</td>\n",
       "      <td>259</td>\n",
       "      <td>Rome</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Gafsa</td>\n",
       "      <td>Proconsularis</td>\n",
       "      <td>hoard</td>\n",
       "      <td>sestertius</td>\n",
       "      <td>21.11</td>\n",
       "      <td>116</td>\n",
       "      <td>117</td>\n",
       "      <td>117.0</td>\n",
       "      <td>143.0</td>\n",
       "      <td>259</td>\n",
       "      <td>Rome</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Gafsa</td>\n",
       "      <td>Proconsularis</td>\n",
       "      <td>hoard</td>\n",
       "      <td>sestertius</td>\n",
       "      <td>23.27</td>\n",
       "      <td>116</td>\n",
       "      <td>117</td>\n",
       "      <td>117.0</td>\n",
       "      <td>143.0</td>\n",
       "      <td>259</td>\n",
       "      <td>Rome</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Gafsa</td>\n",
       "      <td>Proconsularis</td>\n",
       "      <td>hoard</td>\n",
       "      <td>sestertius</td>\n",
       "      <td>25.42</td>\n",
       "      <td>119</td>\n",
       "      <td>138</td>\n",
       "      <td>129.0</td>\n",
       "      <td>131.0</td>\n",
       "      <td>259</td>\n",
       "      <td>Rome</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Gafsa</td>\n",
       "      <td>Proconsularis</td>\n",
       "      <td>hoard</td>\n",
       "      <td>sestertius</td>\n",
       "      <td>21.81</td>\n",
       "      <td>119</td>\n",
       "      <td>138</td>\n",
       "      <td>129.0</td>\n",
       "      <td>131.0</td>\n",
       "      <td>259</td>\n",
       "      <td>Rome</td>\n",
       "    </tr>\n",
       "    <tr>\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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50965</th>\n",
       "      <td>50966</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Segermes</td>\n",
       "      <td>Proconsularis</td>\n",
       "      <td>sitefind</td>\n",
       "      <td>antoninianus</td>\n",
       "      <td>1.46</td>\n",
       "      <td>270</td>\n",
       "      <td>270</td>\n",
       "      <td>270.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Rome</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50966</th>\n",
       "      <td>50967</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Segermes</td>\n",
       "      <td>Proconsularis</td>\n",
       "      <td>sitefind</td>\n",
       "      <td>antoninianus</td>\n",
       "      <td>2.09</td>\n",
       "      <td>270</td>\n",
       "      <td>270</td>\n",
       "      <td>270.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Rome</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50967</th>\n",
       "      <td>50968</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Segermes</td>\n",
       "      <td>Proconsularis</td>\n",
       "      <td>sitefind</td>\n",
       "      <td>antoninianus</td>\n",
       "      <td>2.57</td>\n",
       "      <td>270</td>\n",
       "      <td>275</td>\n",
       "      <td>272.5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Tripoli</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50968</th>\n",
       "      <td>50969</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Segermes</td>\n",
       "      <td>Proconsularis</td>\n",
       "      <td>sitefind</td>\n",
       "      <td>antoninianus</td>\n",
       "      <td>1.46</td>\n",
       "      <td>260</td>\n",
       "      <td>268</td>\n",
       "      <td>264.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Rome</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50969</th>\n",
       "      <td>50970</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Segermes</td>\n",
       "      <td>Proconsularis</td>\n",
       "      <td>sitefind</td>\n",
       "      <td>antoninianus</td>\n",
       "      <td>2.87</td>\n",
       "      <td>260</td>\n",
       "      <td>268</td>\n",
       "      <td>264.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Rome</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>50970 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Catalogue  Region  Findspot       Province      Type  Denomination  \\\n",
       "0              1  Africa     Gafsa  Proconsularis     hoard    sestertius   \n",
       "1              2  Africa     Gafsa  Proconsularis     hoard    sestertius   \n",
       "2              3  Africa     Gafsa  Proconsularis     hoard    sestertius   \n",
       "3              4  Africa     Gafsa  Proconsularis     hoard    sestertius   \n",
       "4              5  Africa     Gafsa  Proconsularis     hoard    sestertius   \n",
       "...          ...     ...       ...            ...       ...           ...   \n",
       "50965      50966  Africa  Segermes  Proconsularis  sitefind  antoninianus   \n",
       "50966      50967  Africa  Segermes  Proconsularis  sitefind  antoninianus   \n",
       "50967      50968  Africa  Segermes  Proconsularis  sitefind  antoninianus   \n",
       "50968      50969  Africa  Segermes  Proconsularis  sitefind  antoninianus   \n",
       "50969      50970  Africa  Segermes  Proconsularis  sitefind  antoninianus   \n",
       "\n",
       "      Weight  Year_min  Year_max  Mint_Year  Circulation Terminal_date  \\\n",
       "0      21.07       104       111      108.0        152.0           259   \n",
       "1      21.11       116       117      117.0        143.0           259   \n",
       "2      23.27       116       117      117.0        143.0           259   \n",
       "3      25.42       119       138      129.0        131.0           259   \n",
       "4      21.81       119       138      129.0        131.0           259   \n",
       "...      ...       ...       ...        ...          ...           ...   \n",
       "50965   1.46       270       270      270.0          NaN           NaN   \n",
       "50966   2.09       270       270      270.0          NaN           NaN   \n",
       "50967   2.57       270       275      272.5          NaN           NaN   \n",
       "50968   1.46       260       268      264.0          NaN           NaN   \n",
       "50969   2.87       260       268      264.0          NaN           NaN   \n",
       "\n",
       "          Mint  \n",
       "0         Rome  \n",
       "1         Rome  \n",
       "2         Rome  \n",
       "3         Rome  \n",
       "4         Rome  \n",
       "...        ...  \n",
       "50965     Rome  \n",
       "50966     Rome  \n",
       "50967  Tripoli  \n",
       "50968     Rome  \n",
       "50969     Rome  \n",
       "\n",
       "[50970 rows x 13 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "from collections import Counter\n",
    "\n",
    "data_frame = pd.read_csv('isaw-papers-13-data.csv')\n",
    "data_frame"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Exploring and Cleaning: an iterative process"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To some extent, I already know what type of data can be found in the dataset and what I want to focus my attention on. For this reason, before analyzing any further, I can exclude some columns and type of data from the dataset, so that I can work on a restricted and on point set.\n",
    "\n",
    "For example, I will check the Region, the findspot and the denomination to see if there are any empty/NAN/unknown spots and then retain only **Region=Africa**, **Findspot=hoard** and **exclude** any denomination of **imitation coins**. Moreover, the timespan the I want to consider is **23 BCE-275 CE**."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Counter({'Africa': 35559, 'Gaul': 13587, 'Spain': 1207, 'Britain': 617})"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Counter(data_frame['Region'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Counter({'hoard': 49759, 'sitefind': 1211})"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Counter(data_frame['Type'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "What I can immediately do is retrieve only the data that has as **Region=Africa** and **findspot=hoard**."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Catalogue</th>\n",
       "      <th>Region</th>\n",
       "      <th>Findspot</th>\n",
       "      <th>Province</th>\n",
       "      <th>Type</th>\n",
       "      <th>Denomination</th>\n",
       "      <th>Weight</th>\n",
       "      <th>Year_min</th>\n",
       "      <th>Year_max</th>\n",
       "      <th>Mint_Year</th>\n",
       "      <th>Circulation</th>\n",
       "      <th>Terminal_date</th>\n",
       "      <th>Mint</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Gafsa</td>\n",
       "      <td>Proconsularis</td>\n",
       "      <td>hoard</td>\n",
       "      <td>sestertius</td>\n",
       "      <td>21.07</td>\n",
       "      <td>104</td>\n",
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       "      <td>152.0</td>\n",
       "      <td>259</td>\n",
       "      <td>Rome</td>\n",
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       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Gafsa</td>\n",
       "      <td>Proconsularis</td>\n",
       "      <td>hoard</td>\n",
       "      <td>sestertius</td>\n",
       "      <td>21.11</td>\n",
       "      <td>116</td>\n",
       "      <td>117</td>\n",
       "      <td>117.0</td>\n",
       "      <td>143.0</td>\n",
       "      <td>259</td>\n",
       "      <td>Rome</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Gafsa</td>\n",
       "      <td>Proconsularis</td>\n",
       "      <td>hoard</td>\n",
       "      <td>sestertius</td>\n",
       "      <td>23.27</td>\n",
       "      <td>116</td>\n",
       "      <td>117</td>\n",
       "      <td>117.0</td>\n",
       "      <td>143.0</td>\n",
       "      <td>259</td>\n",
       "      <td>Rome</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Gafsa</td>\n",
       "      <td>Proconsularis</td>\n",
       "      <td>hoard</td>\n",
       "      <td>sestertius</td>\n",
       "      <td>25.42</td>\n",
       "      <td>119</td>\n",
       "      <td>138</td>\n",
       "      <td>129.0</td>\n",
       "      <td>131.0</td>\n",
       "      <td>259</td>\n",
       "      <td>Rome</td>\n",
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       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Gafsa</td>\n",
       "      <td>Proconsularis</td>\n",
       "      <td>hoard</td>\n",
       "      <td>sestertius</td>\n",
       "      <td>21.81</td>\n",
       "      <td>119</td>\n",
       "      <td>138</td>\n",
       "      <td>129.0</td>\n",
       "      <td>131.0</td>\n",
       "      <td>259</td>\n",
       "      <td>Rome</td>\n",
       "    </tr>\n",
       "    <tr>\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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50955</th>\n",
       "      <td>50956</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Banasa - oven</td>\n",
       "      <td>Mauretania Tingitana</td>\n",
       "      <td>hoard</td>\n",
       "      <td>antoninianus</td>\n",
       "      <td>NaN</td>\n",
       "      <td>270</td>\n",
       "      <td>275</td>\n",
       "      <td>272.5</td>\n",
       "      <td>2.5</td>\n",
       "      <td>275</td>\n",
       "      <td>Gaul/Italy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50956</th>\n",
       "      <td>50957</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Banasa - oven</td>\n",
       "      <td>Mauretania Tingitana</td>\n",
       "      <td>hoard</td>\n",
       "      <td>antoninianus</td>\n",
       "      <td>NaN</td>\n",
       "      <td>270</td>\n",
       "      <td>275</td>\n",
       "      <td>272.5</td>\n",
       "      <td>2.5</td>\n",
       "      <td>275</td>\n",
       "      <td>Gaul/Italy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50957</th>\n",
       "      <td>50958</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Banasa - oven</td>\n",
       "      <td>Mauretania Tingitana</td>\n",
       "      <td>hoard</td>\n",
       "      <td>antoninianus</td>\n",
       "      <td>NaN</td>\n",
       "      <td>270</td>\n",
       "      <td>275</td>\n",
       "      <td>272.5</td>\n",
       "      <td>2.5</td>\n",
       "      <td>275</td>\n",
       "      <td>Gaul/Italy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50958</th>\n",
       "      <td>50959</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Banasa - oven</td>\n",
       "      <td>Mauretania Tingitana</td>\n",
       "      <td>hoard</td>\n",
       "      <td>antoninianus</td>\n",
       "      <td>NaN</td>\n",
       "      <td>270</td>\n",
       "      <td>275</td>\n",
       "      <td>272.5</td>\n",
       "      <td>2.5</td>\n",
       "      <td>275</td>\n",
       "      <td>Gaul/Italy</td>\n",
       "    </tr>\n",
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       "      <th>50959</th>\n",
       "      <td>50960</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Banasa - oven</td>\n",
       "      <td>Mauretania Tingitana</td>\n",
       "      <td>hoard</td>\n",
       "      <td>antoninianus</td>\n",
       "      <td>NaN</td>\n",
       "      <td>270</td>\n",
       "      <td>275</td>\n",
       "      <td>272.5</td>\n",
       "      <td>2.5</td>\n",
       "      <td>275</td>\n",
       "      <td>Gaul/Italy</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>34384 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Catalogue  Region       Findspot              Province   Type  \\\n",
       "0              1  Africa          Gafsa         Proconsularis  hoard   \n",
       "1              2  Africa          Gafsa         Proconsularis  hoard   \n",
       "2              3  Africa          Gafsa         Proconsularis  hoard   \n",
       "3              4  Africa          Gafsa         Proconsularis  hoard   \n",
       "4              5  Africa          Gafsa         Proconsularis  hoard   \n",
       "...          ...     ...            ...                   ...    ...   \n",
       "50955      50956  Africa  Banasa - oven  Mauretania Tingitana  hoard   \n",
       "50956      50957  Africa  Banasa - oven  Mauretania Tingitana  hoard   \n",
       "50957      50958  Africa  Banasa - oven  Mauretania Tingitana  hoard   \n",
       "50958      50959  Africa  Banasa - oven  Mauretania Tingitana  hoard   \n",
       "50959      50960  Africa  Banasa - oven  Mauretania Tingitana  hoard   \n",
       "\n",
       "       Denomination Weight  Year_min  Year_max  Mint_Year  Circulation  \\\n",
       "0        sestertius  21.07       104       111      108.0        152.0   \n",
       "1        sestertius  21.11       116       117      117.0        143.0   \n",
       "2        sestertius  23.27       116       117      117.0        143.0   \n",
       "3        sestertius  25.42       119       138      129.0        131.0   \n",
       "4        sestertius  21.81       119       138      129.0        131.0   \n",
       "...             ...    ...       ...       ...        ...          ...   \n",
       "50955  antoninianus    NaN       270       275      272.5          2.5   \n",
       "50956  antoninianus    NaN       270       275      272.5          2.5   \n",
       "50957  antoninianus    NaN       270       275      272.5          2.5   \n",
       "50958  antoninianus    NaN       270       275      272.5          2.5   \n",
       "50959  antoninianus    NaN       270       275      272.5          2.5   \n",
       "\n",
       "      Terminal_date        Mint  \n",
       "0               259        Rome  \n",
       "1               259        Rome  \n",
       "2               259        Rome  \n",
       "3               259        Rome  \n",
       "4               259        Rome  \n",
       "...             ...         ...  \n",
       "50955           275  Gaul/Italy  \n",
       "50956           275  Gaul/Italy  \n",
       "50957           275  Gaul/Italy  \n",
       "50958           275  Gaul/Italy  \n",
       "50959           275  Gaul/Italy  \n",
       "\n",
       "[34384 rows x 13 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_africa = data_frame[(data_frame['Region'] == 'Africa') & (data_frame['Type'] == 'hoard')]\n",
    "df_africa"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For more clarity, I can delete all the columns that will not be useful for my research."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>Catalogue</th>\n",
       "      <th>Findspot</th>\n",
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       "      <th>1</th>\n",
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       "      <td>sestertius</td>\n",
       "      <td>129.0</td>\n",
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       "      <td>50956</td>\n",
       "      <td>Banasa - oven</td>\n",
       "      <td>Mauretania Tingitana</td>\n",
       "      <td>antoninianus</td>\n",
       "      <td>272.5</td>\n",
       "      <td>Gaul/Italy</td>\n",
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       "      <th>50957</th>\n",
       "      <td>50958</td>\n",
       "      <td>Banasa - oven</td>\n",
       "      <td>Mauretania Tingitana</td>\n",
       "      <td>antoninianus</td>\n",
       "      <td>272.5</td>\n",
       "      <td>Gaul/Italy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50958</th>\n",
       "      <td>50959</td>\n",
       "      <td>Banasa - oven</td>\n",
       "      <td>Mauretania Tingitana</td>\n",
       "      <td>antoninianus</td>\n",
       "      <td>272.5</td>\n",
       "      <td>Gaul/Italy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50959</th>\n",
       "      <td>50960</td>\n",
       "      <td>Banasa - oven</td>\n",
       "      <td>Mauretania Tingitana</td>\n",
       "      <td>antoninianus</td>\n",
       "      <td>272.5</td>\n",
       "      <td>Gaul/Italy</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>34384 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Catalogue       Findspot              Province  Denomination  \\\n",
       "0              1          Gafsa         Proconsularis    sestertius   \n",
       "1              2          Gafsa         Proconsularis    sestertius   \n",
       "2              3          Gafsa         Proconsularis    sestertius   \n",
       "3              4          Gafsa         Proconsularis    sestertius   \n",
       "4              5          Gafsa         Proconsularis    sestertius   \n",
       "...          ...            ...                   ...           ...   \n",
       "50955      50956  Banasa - oven  Mauretania Tingitana  antoninianus   \n",
       "50956      50957  Banasa - oven  Mauretania Tingitana  antoninianus   \n",
       "50957      50958  Banasa - oven  Mauretania Tingitana  antoninianus   \n",
       "50958      50959  Banasa - oven  Mauretania Tingitana  antoninianus   \n",
       "50959      50960  Banasa - oven  Mauretania Tingitana  antoninianus   \n",
       "\n",
       "       Mint_Year        Mint  \n",
       "0          108.0        Rome  \n",
       "1          117.0        Rome  \n",
       "2          117.0        Rome  \n",
       "3          129.0        Rome  \n",
       "4          129.0        Rome  \n",
       "...          ...         ...  \n",
       "50955      272.5  Gaul/Italy  \n",
       "50956      272.5  Gaul/Italy  \n",
       "50957      272.5  Gaul/Italy  \n",
       "50958      272.5  Gaul/Italy  \n",
       "50959      272.5  Gaul/Italy  \n",
       "\n",
       "[34384 rows x 6 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_africa = df_africa.drop(['Region','Type', 'Weight', 'Year_min', 'Year_max', 'Circulation', 'Terminal_date'], axis=1)\n",
    "df_africa"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Checking Denominations, I notice that there are “imitation antoninianus” that I need to exclude."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Counter({'sestertius': 8045,\n",
       "         'dupondius': 1,\n",
       "         'denarius': 4603,\n",
       "         'aureus': 38,\n",
       "         'as': 4,\n",
       "         'dupondius/as': 1,\n",
       "         'antoninianus': 19680,\n",
       "         'imitation antoninianus': 2012})"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Counter(df_africa['Denomination'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>Mauretania Tingitana</td>\n",
       "      <td>antoninianus</td>\n",
       "      <td>272.5</td>\n",
       "      <td>Gaul/Italy</td>\n",
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       "    <tr>\n",
       "      <th>50958</th>\n",
       "      <td>50959</td>\n",
       "      <td>Banasa - oven</td>\n",
       "      <td>Mauretania Tingitana</td>\n",
       "      <td>antoninianus</td>\n",
       "      <td>272.5</td>\n",
       "      <td>Gaul/Italy</td>\n",
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       "    <tr>\n",
       "      <th>50959</th>\n",
       "      <td>50960</td>\n",
       "      <td>Banasa - oven</td>\n",
       "      <td>Mauretania Tingitana</td>\n",
       "      <td>antoninianus</td>\n",
       "      <td>272.5</td>\n",
       "      <td>Gaul/Italy</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>32372 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Catalogue       Findspot              Province  Denomination  \\\n",
       "0              1          Gafsa         Proconsularis    sestertius   \n",
       "1              2          Gafsa         Proconsularis    sestertius   \n",
       "2              3          Gafsa         Proconsularis    sestertius   \n",
       "3              4          Gafsa         Proconsularis    sestertius   \n",
       "4              5          Gafsa         Proconsularis    sestertius   \n",
       "...          ...            ...                   ...           ...   \n",
       "50955      50956  Banasa - oven  Mauretania Tingitana  antoninianus   \n",
       "50956      50957  Banasa - oven  Mauretania Tingitana  antoninianus   \n",
       "50957      50958  Banasa - oven  Mauretania Tingitana  antoninianus   \n",
       "50958      50959  Banasa - oven  Mauretania Tingitana  antoninianus   \n",
       "50959      50960  Banasa - oven  Mauretania Tingitana  antoninianus   \n",
       "\n",
       "       Mint_Year        Mint  \n",
       "0          108.0        Rome  \n",
       "1          117.0        Rome  \n",
       "2          117.0        Rome  \n",
       "3          129.0        Rome  \n",
       "4          129.0        Rome  \n",
       "...          ...         ...  \n",
       "50955      272.5  Gaul/Italy  \n",
       "50956      272.5  Gaul/Italy  \n",
       "50957      272.5  Gaul/Italy  \n",
       "50958      272.5  Gaul/Italy  \n",
       "50959      272.5  Gaul/Italy  \n",
       "\n",
       "[32372 rows x 6 columns]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_africa = df_africa[df_africa['Denomination'] != 'imitation antoninianus']\n",
    "df_africa"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For sure, I can also exclude some coins minted before or after the time span of interest."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "    <tr>\n",
       "      <th>32289</th>\n",
       "      <td>50958</td>\n",
       "      <td>Banasa</td>\n",
       "      <td>Mauretania Tingitana</td>\n",
       "      <td>antoninianus</td>\n",
       "      <td>272.5</td>\n",
       "      <td>Gaul/Italy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32290</th>\n",
       "      <td>50959</td>\n",
       "      <td>Banasa</td>\n",
       "      <td>Mauretania Tingitana</td>\n",
       "      <td>antoninianus</td>\n",
       "      <td>272.5</td>\n",
       "      <td>Gaul/Italy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32291</th>\n",
       "      <td>50960</td>\n",
       "      <td>Banasa</td>\n",
       "      <td>Mauretania Tingitana</td>\n",
       "      <td>antoninianus</td>\n",
       "      <td>272.5</td>\n",
       "      <td>Gaul/Italy</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>32292 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Catalogue Findspot              Province  Denomination  Mint_Year  \\\n",
       "0              1    Gafsa         Proconsularis    sestertius      108.0   \n",
       "1              2    Gafsa         Proconsularis    sestertius      117.0   \n",
       "2              3    Gafsa         Proconsularis    sestertius      117.0   \n",
       "3              4    Gafsa         Proconsularis    sestertius      129.0   \n",
       "4              5    Gafsa         Proconsularis    sestertius      129.0   \n",
       "...          ...      ...                   ...           ...        ...   \n",
       "32287      50956   Banasa  Mauretania Tingitana  antoninianus      272.5   \n",
       "32288      50957   Banasa  Mauretania Tingitana  antoninianus      272.5   \n",
       "32289      50958   Banasa  Mauretania Tingitana  antoninianus      272.5   \n",
       "32290      50959   Banasa  Mauretania Tingitana  antoninianus      272.5   \n",
       "32291      50960   Banasa  Mauretania Tingitana  antoninianus      272.5   \n",
       "\n",
       "             Mint  \n",
       "0            Rome  \n",
       "1            Rome  \n",
       "2            Rome  \n",
       "3            Rome  \n",
       "4            Rome  \n",
       "...           ...  \n",
       "32287  Gaul/Italy  \n",
       "32288  Gaul/Italy  \n",
       "32289  Gaul/Italy  \n",
       "32290  Gaul/Italy  \n",
       "32291  Gaul/Italy  \n",
       "\n",
       "[32292 rows x 6 columns]"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_africa = df_africa[(df_africa['Mint_Year'] >= -23) & (df_africa['Mint_Year'] <= 275)]\n",
    "df_africa"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 32292 entries, 0 to 32291\n",
      "Data columns (total 6 columns):\n",
      " #   Column        Non-Null Count  Dtype  \n",
      "---  ------        --------------  -----  \n",
      " 0   Catalogue     32292 non-null  int64  \n",
      " 1   Findspot      32292 non-null  object \n",
      " 2   Province      32292 non-null  object \n",
      " 3   Denomination  32292 non-null  object \n",
      " 4   Mint_Year     32292 non-null  float64\n",
      " 5   Mint          32292 non-null  object \n",
      "dtypes: float64(1), int64(1), object(4)\n",
      "memory usage: 1.7+ MB\n"
     ]
    }
   ],
   "source": [
    "df_africa.info() # Index, Datatype and Memory information"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Each column has the correct type, no need for fixes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Catalogue       32292\n",
       "Findspot        32292\n",
       "Province        32292\n",
       "Denomination    32292\n",
       "Mint_Year       32292\n",
       "Mint            32292\n",
       "dtype: int64"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_africa.count() # Returns the number of non-null values in each DataFrame: rows should be 32372"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_africa.to_csv('refined_dataset.csv', index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Since the detail of the single archaeological excavation in a Findspot is not of my interest, I proceed to clean the data with the OpenRefine software in order to unify similar Findposts."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The result is a new dataset, which I transform back into a dataframe, and which contains this number of Findspots:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_africa = pd.read_csv('cleaned_dataset.csv', encoding='utf-8 ')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Split data\n",
    "\n",
    "Now it is time to spit data into 3 historical periods: \n",
    "1. 23 BCE- 96 CE\n",
    "2. 97-192 CE\n",
    "3. 193-275 CE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_africa1 = df_africa[df_africa['Mint_Year'] < 97]\n",
    "df_africa2 = df_africa[(df_africa['Mint_Year'] > 96) & (df_africa['Mint_Year'] < 193)]\n",
    "df_africa3 = df_africa[df_africa['Mint_Year'] > 192]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In order to prepare tables that will be needed to callculate the BR coefficient, I develop the necessary functions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def new_csv(data_frame, file_name):\n",
    "    '''\n",
    "    drop csv file\n",
    "    '''\n",
    "    return data_frame.to_csv(file_name, index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def den_per_prov_count(data_frame):\n",
    "    '''\n",
    "    how many coins of each denomination per findspot, return new df\n",
    "    '''\n",
    "    find = data_frame['Findspot'].unique()\n",
    "    den = data_frame['Denomination'].unique()\n",
    "    new_d = {'Site': find.tolist()}\n",
    "    for d in den.tolist():\n",
    "        new_d[d] = 0\n",
    "    new_df = pd.DataFrame(data=new_d)\n",
    "    for f in find:\n",
    "        for idn in data_frame.index:\n",
    "            if data_frame['Findspot'][idn] == f:\n",
    "                denomination = data_frame['Denomination'][idn]\n",
    "                idx = new_df.index[new_df['Site'] == f].values[0]\n",
    "                new_df.at[idx, denomination] = new_df.at[idx, denomination] +1\n",
    "    return new_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "def remove_few_coins(df):\n",
    "    '''\n",
    "    remove site with less than 10 coins\n",
    "    '''\n",
    "    data_frame = den_per_prov_count(df)\n",
    "    s = data_frame.sum(axis=1, numeric_only=True)\n",
    "    for ind in data_frame.index:\n",
    "        if s[ind] < 10:\n",
    "            data_frame.drop(labels=ind, axis=0, inplace=True)\n",
    "    return data_frame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_africa1 = remove_few_coins(df_africa1)\n",
    "df_africa2 = remove_few_coins(df_africa2)\n",
    "df_africa3 = remove_few_coins(df_africa3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 290,
   "metadata": {},
   "outputs": [],
   "source": [
    "# drop new csv files\n",
    "new_csv(df_africa1, 'df_africa1.csv')\n",
    "new_csv(df_africa2, 'df_africa2.csv')\n",
    "new_csv(df_africa3, 'df_africa3.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### BR coefficient and Mini-Max Model\n",
    "\n",
    "I run the BR.r script on each of the three tables.\n",
    "\n",
    "I need to define a model that decides a threshold under which the similarity between two findspots can be cosidered as too weak. Under the threshold, the network doesn't retain its unity. This threshold is necessary to transform the BR output matrix into a binary one: 1 equal or above threshold, 0 under threshold."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "def remove_isolates(data_frame):\n",
    "    '''\n",
    "    check the presence of isolates and remove from graph\n",
    "    '''\n",
    "    G = nx.from_pandas_adjacency(data_frame)\n",
    "    G.remove_edges_from(nx.selfloop_edges(G))\n",
    "\n",
    "    iso = list(nx.isolates(G))\n",
    "    if len(iso) > 0:\n",
    "        for n in iso:\n",
    "            data_frame.drop(n, axis=1, inplace=True)\n",
    "            data_frame.drop(n, axis=0, inplace=True)\n",
    "        return data_frame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def to_binary_matrix(threshold, df):\n",
    "    '''\n",
    "    change values to 1 or 0 based on threshold number\n",
    "    '''\n",
    "    df.mask(df < threshold, other=0, inplace=True)\n",
    "    df.mask(df >= threshold, other=1, inplace=True)\n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "import networkx as nx\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "def min_max_model(file_name):\n",
    "    '''\n",
    "    find threshold for each matrix and return binary matrix\n",
    "    '''\n",
    "    # read the csv into a dataframe\n",
    "    input_data = pd.read_csv(file_name, index_col=0)\n",
    "    # immediately check if there are isolated nodes in the network: means they have similarity 0 with all others and we need to remove them\n",
    "    remove_isolates(input_data)\n",
    "    \n",
    "    # define starting threshold value as 200 (max BR similarity coefficient) to have most of the nodes separated\n",
    "    threshold = 200\n",
    "    # create a copy of dataframe to not overwrite\n",
    "    df_copy = input_data.copy()\n",
    "    # first transformation into binary dataframe to check connectivity\n",
    "    to_binary_matrix(threshold, df_copy)\n",
    "    binary_G = nx.from_pandas_adjacency(df_copy)\n",
    "    binary_G.remove_edges_from(nx.selfloop_edges(binary_G))  # remove selfloops because unnecessary\n",
    "    connection = nx.is_connected(binary_G)\n",
    "    \n",
    "    # lower threshold value until there are no more separated components in the network\n",
    "    while (connection == False):\n",
    "        threshold -= 1\n",
    "        df_copy = input_data.copy()\n",
    "        to_binary_matrix(threshold, df_copy)\n",
    "        binary_G = nx.from_pandas_adjacency(df_copy)\n",
    "        binary_G.remove_edges_from(nx.selfloop_edges(binary_G))\n",
    "        connection = nx.is_connected(binary_G)\n",
    "    else:\n",
    "        return df_copy"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## The Networks"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now I binarize each matrix using the threshold of each one and visualize the networks:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "matrix_1 = min_max_model('df_africa1_out.csv')\n",
    "G_1 = nx.from_pandas_adjacency(matrix_1)\n",
    "G_1.remove_edges_from(nx.selfloop_edges(G_1))\n",
    "nx.draw(G_1, with_labels='True')"
   ]
  },
  {
   "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": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "matrix_2 = min_max_model('df_africa2_out.csv')\n",
    "G_2 = nx.from_pandas_adjacency(matrix_2)\n",
    "G_2.remove_edges_from(nx.selfloop_edges(G_2))\n",
    "nx.draw(G_2, with_labels='True')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "matrix_3 = min_max_model('df_africa3_out.csv')\n",
    "G_3 = nx.from_pandas_adjacency(matrix_3)\n",
    "G_3.remove_edges_from(nx.selfloop_edges(G_3))\n",
    "nx.draw(G_3, with_labels='True')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "By default, the layout of the nodes and edges is automatically determined by the Fruchterman-Reingold force-directed algorithm (called “spring layout” in NetworkX), which conducts a pseudo-physics simulation of the movements of the nodes, assuming that each edge is a spring with a ﬁxed equilibrium distance. This heuristic algorithm tends to bring groups of well-connected nodes closer to each other, making the result of visualization more meaningful and aesthetically more pleasing."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now I will costumize the networks based on the Province of each findspot (color), and the composition of the hoard (width)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "# colors\n",
    "color_dict = {\n",
    "    'Proconsularis': '#8D38E1', #purple\n",
    "    'Numidia': '#E1E138', #yellow\n",
    "    'Mauretania Caesarea': '#8DE138', #green\n",
    "    'Mauretania Tingitana': '#E13838', #red\n",
    "    'Tripolitania': '#8D38E1'\n",
    "}\n",
    "\n",
    "def color_map(G, starting_colors, dataframe):\n",
    "    '''\n",
    "    create a list of colors for the nodes, based on Province\n",
    "    '''\n",
    "    color_list = []\n",
    "    node_list = list(G.nodes)\n",
    "    for node in node_list:\n",
    "        idx = dataframe.index[dataframe['Findspot']==node].tolist()[0]\n",
    "        province = dataframe['Province'].iloc[idx]\n",
    "        color = starting_colors[province]\n",
    "        color_list.append(color)\n",
    "    return color_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "color_map_1 = color_map(G_1, color_dict, df_africa)\n",
    "color_map_2 = color_map(G_2, color_dict, df_africa)\n",
    "color_map_3 = color_map(G_3, color_dict, df_africa)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "# width\n",
    "width_dict = {\n",
    "    'sestertius': 50,\n",
    "    'denarius': 200,\n",
    "    'antoninianus': 600\n",
    "}\n",
    "\n",
    "\n",
    "def whidth_map(G, shape_dict, file_name):\n",
    "    '''\n",
    "    create a list of shapes for the nodes, based on the most present type of coin in Site\n",
    "    '''\n",
    "    width_list = []\n",
    "    input_data = pd.read_csv(file_name, index_col=0)\n",
    "    coin_types = input_data.idxmax(axis=1)\n",
    "\n",
    "    node_list = list(G.nodes)\n",
    "    for node in node_list:\n",
    "        for index, value in coin_types.items():\n",
    "            if node == index:\n",
    "                width = width_dict[value]\n",
    "                width_list.append(width)\n",
    "    return width_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "color_list = []\n",
    "for v in color_dict.values():\n",
    "    color_list.append(v)\n",
    "\n",
    "prov_list = []\n",
    "for k in color_dict.keys():\n",
    "    prov_list.append(k)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "shape_map_1 = whidth_map(G_1, width_dict, 'df_africa1.csv')\n",
    "shape_map_2 = whidth_map(G_2, width_dict, 'df_africa2.csv')\n",
    "shape_map_3 = whidth_map(G_3, width_dict, 'df_africa3.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.patches as mpatches\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "nx.draw_networkx(G_1, node_color=color_map_1, node_size=shape_map_1, width=0.5, with_labels=False)\n",
    "plt.savefig(\"period1.png\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(15, 10))\n",
    "\n",
    "nx.draw_networkx(G_2, node_color=color_map_2, node_size=shape_map_2, width=0.5, with_labels=False)\n",
    "plt.savefig(\"period2.png\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(15, 10))\n",
    "\n",
    "nx.draw_networkx(G_3, node_color=color_map_3, node_size=shape_map_3, width=0.4, with_labels=False)\n",
    "plt.savefig(\"period3.png\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### The Measures\n",
    "\n",
    "#### Network Density\n",
    "\n",
    "The simplest measure of cohesion is density, i.e., the ratio between the number of ties in the network with respect to the total number of possible ties *n(n-1)/2*."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The networks have density of 1.0, 0.4860215053763441 and 0.47096774193548385.\n"
     ]
    }
   ],
   "source": [
    "d_1 = nx.density(G_1)\n",
    "d_2 = nx.density(G_2)\n",
    "d_3 = nx.density(G_3)\n",
    "print(f'The networks have density of {d_1}, {d_2} and {d_3}.')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Network Size\n",
    "\n",
    "**Diameter**\n",
    "\n",
    "The diameter of a network is the length of the longest among all existing shortest paths between every pair of nodes in the network. The diameter of the network is useful e.g., to understand the connectedness of networks."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The networks have diameter of 1, 3 and 3.\n"
     ]
    }
   ],
   "source": [
    "dm_1 = nx.diameter(G_1)\n",
    "dm_2 = nx.diameter(G_2)\n",
    "dm_3 = nx.diameter(G_3)\n",
    "print(f'The networks have diameter of {dm_1}, {dm_2} and {dm_3}.')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Average Path Length**\n",
    "\n",
    "Paths are walks (a sequence of nodes such that every consecutive pair of nodes in the sequence is connected by an edge) that do not intersect themselves.\n",
    "A shortest path in a network, also sometimes called a geodesic path, is the shortest walk (hence minimal on the number of edges and thus self-avoiding) between a given pair of nodes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The networks have average shortest path length of 1.0, 1.9655913978494624 and 1.6064516129032258.\n"
     ]
    }
   ],
   "source": [
    "p_1 = nx.average_shortest_path_length(G_1)\n",
    "p_2 = nx.average_shortest_path_length(G_2)\n",
    "p_3 = nx.average_shortest_path_length(G_3)\n",
    "print(f'The networks have average shortest path length of {p_1}, {p_2} and {p_3}.')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Centrality Measures\n",
    "\n",
    "**Degree Centrality**\n",
    "\n",
    "One of the simplest centrality measure for a node in a network is just its degree. In an undirected network, the degree of a\n",
    "node is the number of edges connected to it.\n",
    "\n",
    "It can be very illuminating: for example, in a social network those individuals who have many followers might have more influence, more access to information, or more prestige than those who have fewer. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Network 1 have degree centrality of {'Volubilis': 1.0, 'Ain Temouchent': 1.0, 'Albulae': 1.0, 'Thibilis': 1.0, 'Tipasa': 1.0}\n",
      "\n",
      "Network 2 have degree centrality of {'Gafsa': 0.5, 'Rusguniae': 0.5, 'Monastir': 0.4666666666666667, 'Lambaesa': 0.4666666666666667, 'Guelma': 0.5, 'Volubilis': 0.4666666666666667, 'Banasa': 0.5333333333333333, 'Ain Temouchent': 0.4666666666666667, 'Ain Bessem': 0.5, 'Ain el Djenan': 0.4666666666666667, 'Albulae': 0.5, 'Alger-Hammamet': 0.5, 'Alger-Rais Hamidou': 0.5, 'Thibilis': 0.4666666666666667, 'Bouira': 0.4666666666666667, 'Cherchel': 0.5, 'Auzia': 0.4666666666666667, 'Cissi': 0.5, 'Grarem': 0.5, 'Aquae Calidae': 0.5, 'Khemis el Khema': 0.5, 'Gunugu': 0.5, 'Taher': 0.5, 'Tipasa': 0.4666666666666667, 'Garian': 0.5, 'Sabratha': 0.4666666666666667, 'Tripoli ': 0.5, 'Adjim': 0.4666666666666667, 'Carthage': 0.4666666666666667, 'Thaenae': 0.4666666666666667, 'Hadrumetum': 0.4666666666666667}\n",
      "\n",
      " Network 3 have degree centrality of {'Gafsa': 0.2, 'Guelma': 0.2, 'Rusguniae': 0.2, 'Banasa': 0.8, 'Ain Temouchent': 0.23333333333333334, 'Hadrumetum': 0.8, 'El-Hamadi': 0.23333333333333334, 'Albulae': 0.23333333333333334, 'Ain Trab': 0.2, 'Thibilis': 0.23333333333333334, 'Cissi': 0.6, 'Gadiaufala': 0.2, 'Miliana': 0.6, 'Bou Arreridj': 0.6, 'Rusicade': 0.6, 'Rapidum': 0.6, 'Auzia': 0.6, 'Cartennas': 0.6, 'Iomnium': 0.6, 'Lucu': 0.2, 'Tipasa': 0.6, 'Abbiar-Miggi': 0.6, 'Gasr Selim': 0.6, 'Sabratha': 0.8, 'Adjim': 0.23333333333333334, 'Carthage': 0.23333333333333334, 'Thysdrus': 0.6, 'Fadhiline': 0.6, 'Ras Kaboudia': 0.6, 'Utica': 0.6, 'Volubilis': 0.6}.\n"
     ]
    }
   ],
   "source": [
    "dc_1 = nx.degree_centrality(G_1)\n",
    "dc_2 = nx.degree_centrality(G_2)\n",
    "dc_3 = nx.degree_centrality(G_3)\n",
    "print(f'Network 1 have degree centrality of {dc_1}\\n\\nNetwork 2 have degree centrality of {dc_2}\\n\\n Network 3 have degree centrality of {dc_3}.')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.0\n",
      "0.4860215053763441\n",
      "0.47096774193548385\n"
     ]
    }
   ],
   "source": [
    "# mean value\n",
    "\n",
    "import statistics\n",
    "\n",
    "def mean_value(d):\n",
    "    value_set = []\n",
    "    for v in d.values():\n",
    "        value_set.append(v)\n",
    "    return statistics.mean(value_set)\n",
    "\n",
    "print(mean_value(dc_1))\n",
    "print(mean_value(dc_2))\n",
    "print(mean_value(dc_3))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Eigenvector Centrality**\n",
    "\n",
    "In many circumstances a node’s importance in a network is increased by having connections to other nodes that are themselves important.\n",
    "\n",
    "Eigenvector centrality is an extension of degree centrality that takes this factor into account. Instead of just awarding one point for every network neighbour a node has, eigenvector centrality awards a number of points proportional to the centrality\n",
    "scores of the neighbours.\n",
    "\n",
    "For example, you might have only one friend in the world, but if that friend is the president of the United States then you yourself may be an important person. Thus centrality is not only about how many people you know but also who you know."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Network 1 have eigenvector centrality of {'Volubilis': 0.447213595499958, 'Ain Temouchent': 0.4472135954999579, 'Albulae': 0.44721359549995787, 'Thibilis': 0.44721359549995787, 'Tipasa': 0.4472135954999579}\n",
      "\n",
      "Network 2 have eigenvector centrality of {'Gafsa': 0.2493300581425379, 'Rusguniae': 0.2493300581425378, 'Monastir': 0.015575501086128698, 'Lambaesa': 0.015575501086128688, 'Guelma': 0.24933005814253786, 'Volubilis': 0.015575501086128672, 'Banasa': 0.25128366661580476, 'Ain Temouchent': 0.015575501086128807, 'Ain Bessem': 0.24933005814253784, 'Ain el Djenan': 0.015575501086128735, 'Albulae': 0.03127304293671361, 'Alger-Hammamet': 0.2493300581425379, 'Alger-Rais Hamidou': 0.24933005814253784, 'Thibilis': 0.015575501086128709, 'Bouira': 0.015575501086128709, 'Cherchel': 0.2493300581425379, 'Auzia': 0.015575501086128695, 'Cissi': 0.2493300581425379, 'Grarem': 0.2493300581425378, 'Aquae Calidae': 0.24933005814253786, 'Khemis el Khema': 0.24933005814253778, 'Gunugu': 0.24933005814253786, 'Taher': 0.24933005814253792, 'Tipasa': 0.015575501086128733, 'Garian': 0.24933005814253778, 'Sabratha': 0.015575501086128749, 'Tripoli ': 0.2493300581425378, 'Adjim': 0.015575501086128733, 'Carthage': 0.015575501086128698, 'Thaenae': 0.01557550108612874, 'Hadrumetum': 0.015575501086128705}\n",
      "\n",
      " Network 3 have eigenvector centrality of {'Gafsa': 0.017701075497283187, 'Guelma': 0.01770107549728319, 'Rusguniae': 0.01770107549728317, 'Banasa': 0.2323248763787858, 'Ain Temouchent': 0.036290861607227345, 'Hadrumetum': 0.23815699610661373, 'El-Hamadi': 0.03629086160722733, 'Albulae': 0.03629086160722732, 'Ain Trab': 0.017701075497283135, 'Thibilis': 0.036290861607227304, 'Cissi': 0.22677156925621192, 'Gadiaufala': 0.017701075497283145, 'Miliana': 0.2267715692562118, 'Bou Arreridj': 0.22677156925621186, 'Rusicade': 0.22677156925621184, 'Rapidum': 0.22677156925621178, 'Auzia': 0.22677156925621184, 'Cartennas': 0.22677156925621178, 'Iomnium': 0.2267715692562118, 'Lucu': 0.017701075497283225, 'Tipasa': 0.22677156925621178, 'Abbiar-Miggi': 0.22677156925621184, 'Gasr Selim': 0.22677156925621178, 'Sabratha': 0.23815699610661378, 'Adjim': 0.03629086160722746, 'Carthage': 0.03629086160722737, 'Thysdrus': 0.22677156925621175, 'Fadhiline': 0.2267715692562118, 'Ras Kaboudia': 0.2267715692562118, 'Utica': 0.2267715692562118, 'Volubilis': 0.22677156925621186}.\n"
     ]
    }
   ],
   "source": [
    "ec_1 = nx.eigenvector_centrality_numpy(G_1)\n",
    "ec_2 = nx.eigenvector_centrality_numpy(G_2)\n",
    "ec_3 = nx.eigenvector_centrality_numpy(G_3)\n",
    "print(f'Network 1 have eigenvector centrality of {ec_1}\\n\\nNetwork 2 have eigenvector centrality of {ec_2}\\n\\n Network 3 have eigenvector centrality of {ec_3}.')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.4472135954999579\n",
      "0.1367924063514964\n",
      "0.1503527612683376\n"
     ]
    }
   ],
   "source": [
    "# mean value\n",
    "\n",
    "print(mean_value(ec_1))\n",
    "print(mean_value(ec_2))\n",
    "print(mean_value(ec_3))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Betweenness Centrality**\n",
    "\n",
    "Betweenness centrality, also based on shortest paths, measures the extent to which a node lies on paths between other nodes. The assumption here is that paths lying on “trafficked” shortest paths have a more central role in the network, as gateways favoured by their closeness to (reach) the other nodes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Network 1 have betweenness centrality of {'Volubilis': 0.0, 'Ain Temouchent': 0.0, 'Albulae': 0.0, 'Thibilis': 0.0, 'Tipasa': 0.0}\n",
      "\n",
      "Network 2 have betweenness centrality of {'Gafsa': 0.0, 'Rusguniae': 0.0, 'Monastir': 0.0, 'Lambaesa': 0.0, 'Guelma': 0.0, 'Volubilis': 0.0, 'Banasa': 0.5172413793103449, 'Ain Temouchent': 0.0, 'Ain Bessem': 0.0, 'Ain el Djenan': 0.0, 'Albulae': 0.5149425287356322, 'Alger-Hammamet': 0.0, 'Alger-Rais Hamidou': 0.0, 'Thibilis': 0.0, 'Bouira': 0.0, 'Cherchel': 0.0, 'Auzia': 0.0, 'Cissi': 0.0, 'Grarem': 0.0, 'Aquae Calidae': 0.0, 'Khemis el Khema': 0.0, 'Gunugu': 0.0, 'Taher': 0.0, 'Tipasa': 0.0, 'Garian': 0.0, 'Sabratha': 0.0, 'Tripoli ': 0.0, 'Adjim': 0.0, 'Carthage': 0.0, 'Thaenae': 0.0, 'Hadrumetum': 0.0}\n",
      "\n",
      "Network 3 have betweenness centrality of {'Gafsa': 0.0, 'Guelma': 0.0, 'Rusguniae': 0.0, 'Banasa': 0.3310344827586207, 'Ain Temouchent': 0.0, 'Hadrumetum': 0.1586206896551724, 'El-Hamadi': 0.0, 'Albulae': 0.0, 'Ain Trab': 0.0, 'Thibilis': 0.0, 'Cissi': 0.0, 'Gadiaufala': 0.0, 'Miliana': 0.0, 'Bou Arreridj': 0.0, 'Rusicade': 0.0, 'Rapidum': 0.0, 'Auzia': 0.0, 'Cartennas': 0.0, 'Iomnium': 0.0, 'Lucu': 0.0, 'Tipasa': 0.0, 'Abbiar-Miggi': 0.0, 'Gasr Selim': 0.0, 'Sabratha': 0.1586206896551724, 'Adjim': 0.0, 'Carthage': 0.0, 'Thysdrus': 0.0, 'Fadhiline': 0.0, 'Ras Kaboudia': 0.0, 'Utica': 0.0, 'Volubilis': 0.0}.\n"
     ]
    }
   ],
   "source": [
    "bc_1 = nx.betweenness_centrality(G_1)\n",
    "bc_2 = nx.betweenness_centrality(G_2)\n",
    "bc_3 = nx.betweenness_centrality(G_3)\n",
    "print(f'Network 1 have betweenness centrality of {bc_1}\\n\\nNetwork 2 have betweenness centrality of {bc_2}\\n\\nNetwork 3 have betweenness centrality of {bc_3}.')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.0\n",
      "0.03329625509825732\n",
      "0.020912124582869854\n"
     ]
    }
   ],
   "source": [
    "# mean value\n",
    "\n",
    "print(mean_value(bc_1))\n",
    "print(mean_value(bc_2))\n",
    "print(mean_value(bc_3))"
   ]
  }
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