diff --git a/.ipynb_checkpoints/Untitled-checkpoint.ipynb b/.ipynb_checkpoints/Untitled-checkpoint.ipynb
new file mode 100644
index 0000000..2fd6442
--- /dev/null
+++ b/.ipynb_checkpoints/Untitled-checkpoint.ipynb
@@ -0,0 +1,6 @@
+{
+ "cells": [],
+ "metadata": {},
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/.ipynb_checkpoints/Untitled1-checkpoint.ipynb b/.ipynb_checkpoints/Untitled1-checkpoint.ipynb
new file mode 100644
index 0000000..027901f
--- /dev/null
+++ b/.ipynb_checkpoints/Untitled1-checkpoint.ipynb
@@ -0,0 +1,393 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "import sys\n",
+    "import matplotlib.pyplot as plt\n",
+    "import seaborn as sns\n",
+    "\n",
+    "nb_dir = os.path.split(os.getcwd())[0]\n",
+    "if nb_dir not in sys.path:\n",
+    "    sys.path.append(nb_dir)\n",
+    "    \n",
+    "from features.communication import *\n",
+    "import participants.query_db\n",
+    "\n",
+    "participants_inactive_usernames = participants.query_db.get_usernames()\n",
+    "df_sms = get_sms_data(participants_inactive_usernames)\n",
+    "df_calls = get_call_data(participants_inactive_usernames)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "    count_calls = count_comms(df_calls)\n",
+    "    count_sms = count_comms(df_sms)\n",
+    "\n",
+    "    count_joined = count_calls.merge(\n",
+    "        count_sms, on=\"participant_id\", suffixes=(\"_calls\", \"_sms\")\n",
+    "    )"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>participant_id</th>\n",
+       "      <th>no_incoming</th>\n",
+       "      <th>no_outgoing</th>\n",
+       "      <th>no_missed</th>\n",
+       "      <th>no_all_calls</th>\n",
+       "      <th>no_incoming_ratio</th>\n",
+       "      <th>no_outgoing_ratio</th>\n",
+       "      <th>duration_total_incoming</th>\n",
+       "      <th>duration_total_outgoing</th>\n",
+       "      <th>duration_max_incoming</th>\n",
+       "      <th>duration_max_outgoing</th>\n",
+       "      <th>no_received</th>\n",
+       "      <th>no_sent</th>\n",
+       "      <th>no_all_sms</th>\n",
+       "      <th>no_received_ratio</th>\n",
+       "      <th>no_sent_ratio</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>13</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>21.0</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>26.0</td>\n",
+       "      <td>0.115385</td>\n",
+       "      <td>0.807692</td>\n",
+       "      <td>342.0</td>\n",
+       "      <td>2836.0</td>\n",
+       "      <td>196.0</td>\n",
+       "      <td>355.0</td>\n",
+       "      <td>7.0</td>\n",
+       "      <td>7.0</td>\n",
+       "      <td>14.0</td>\n",
+       "      <td>0.500000</td>\n",
+       "      <td>0.500000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>14</td>\n",
+       "      <td>16.0</td>\n",
+       "      <td>22.0</td>\n",
+       "      <td>11.0</td>\n",
+       "      <td>49.0</td>\n",
+       "      <td>0.326531</td>\n",
+       "      <td>0.448980</td>\n",
+       "      <td>1873.0</td>\n",
+       "      <td>2789.0</td>\n",
+       "      <td>346.0</td>\n",
+       "      <td>694.0</td>\n",
+       "      <td>20.0</td>\n",
+       "      <td>14.0</td>\n",
+       "      <td>34.0</td>\n",
+       "      <td>0.588235</td>\n",
+       "      <td>0.411765</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>15</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>0.600000</td>\n",
+       "      <td>0.400000</td>\n",
+       "      <td>310.0</td>\n",
+       "      <td>19.0</td>\n",
+       "      <td>154.0</td>\n",
+       "      <td>19.0</td>\n",
+       "      <td>73.0</td>\n",
+       "      <td>73.0</td>\n",
+       "      <td>146.0</td>\n",
+       "      <td>0.500000</td>\n",
+       "      <td>0.500000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>16</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>6.0</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>13.0</td>\n",
+       "      <td>0.307692</td>\n",
+       "      <td>0.461538</td>\n",
+       "      <td>1963.0</td>\n",
+       "      <td>849.0</td>\n",
+       "      <td>1037.0</td>\n",
+       "      <td>638.0</td>\n",
+       "      <td>8.0</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>10.0</td>\n",
+       "      <td>0.800000</td>\n",
+       "      <td>0.200000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>17</td>\n",
+       "      <td>20.0</td>\n",
+       "      <td>60.0</td>\n",
+       "      <td>8.0</td>\n",
+       "      <td>88.0</td>\n",
+       "      <td>0.227273</td>\n",
+       "      <td>0.681818</td>\n",
+       "      <td>5789.0</td>\n",
+       "      <td>17046.0</td>\n",
+       "      <td>1966.0</td>\n",
+       "      <td>3830.0</td>\n",
+       "      <td>7.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>8.0</td>\n",
+       "      <td>0.875000</td>\n",
+       "      <td>0.125000</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",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>56</th>\n",
+       "      <td>91</td>\n",
+       "      <td>15.0</td>\n",
+       "      <td>13.0</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>31.0</td>\n",
+       "      <td>0.483871</td>\n",
+       "      <td>0.419355</td>\n",
+       "      <td>3443.0</td>\n",
+       "      <td>3636.0</td>\n",
+       "      <td>644.0</td>\n",
+       "      <td>1315.0</td>\n",
+       "      <td>83.0</td>\n",
+       "      <td>44.0</td>\n",
+       "      <td>127.0</td>\n",
+       "      <td>0.653543</td>\n",
+       "      <td>0.346457</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>57</th>\n",
+       "      <td>92</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>8.0</td>\n",
+       "      <td>0.375000</td>\n",
+       "      <td>0.500000</td>\n",
+       "      <td>231.0</td>\n",
+       "      <td>648.0</td>\n",
+       "      <td>167.0</td>\n",
+       "      <td>433.0</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>6.0</td>\n",
+       "      <td>10.0</td>\n",
+       "      <td>0.400000</td>\n",
+       "      <td>0.600000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>58</th>\n",
+       "      <td>93</td>\n",
+       "      <td>22.0</td>\n",
+       "      <td>20.0</td>\n",
+       "      <td>9.0</td>\n",
+       "      <td>51.0</td>\n",
+       "      <td>0.431373</td>\n",
+       "      <td>0.392157</td>\n",
+       "      <td>2534.0</td>\n",
+       "      <td>1444.0</td>\n",
+       "      <td>443.0</td>\n",
+       "      <td>672.0</td>\n",
+       "      <td>48.0</td>\n",
+       "      <td>19.0</td>\n",
+       "      <td>67.0</td>\n",
+       "      <td>0.716418</td>\n",
+       "      <td>0.283582</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>59</th>\n",
+       "      <td>106</td>\n",
+       "      <td>12.0</td>\n",
+       "      <td>30.0</td>\n",
+       "      <td>6.0</td>\n",
+       "      <td>48.0</td>\n",
+       "      <td>0.250000</td>\n",
+       "      <td>0.625000</td>\n",
+       "      <td>3049.0</td>\n",
+       "      <td>2637.0</td>\n",
+       "      <td>878.0</td>\n",
+       "      <td>380.0</td>\n",
+       "      <td>10.0</td>\n",
+       "      <td>10.0</td>\n",
+       "      <td>20.0</td>\n",
+       "      <td>0.500000</td>\n",
+       "      <td>0.500000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>60</th>\n",
+       "      <td>107</td>\n",
+       "      <td>11.0</td>\n",
+       "      <td>42.0</td>\n",
+       "      <td>13.0</td>\n",
+       "      <td>66.0</td>\n",
+       "      <td>0.166667</td>\n",
+       "      <td>0.636364</td>\n",
+       "      <td>3804.0</td>\n",
+       "      <td>9977.0</td>\n",
+       "      <td>1519.0</td>\n",
+       "      <td>1943.0</td>\n",
+       "      <td>80.0</td>\n",
+       "      <td>176.0</td>\n",
+       "      <td>256.0</td>\n",
+       "      <td>0.312500</td>\n",
+       "      <td>0.687500</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>61 rows × 16 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    participant_id  no_incoming  no_outgoing  no_missed  no_all_calls  \\\n",
+       "0               13          3.0         21.0        2.0          26.0   \n",
+       "1               14         16.0         22.0       11.0          49.0   \n",
+       "2               15          3.0          2.0        NaN           5.0   \n",
+       "3               16          4.0          6.0        3.0          13.0   \n",
+       "4               17         20.0         60.0        8.0          88.0   \n",
+       "..             ...          ...          ...        ...           ...   \n",
+       "56              91         15.0         13.0        3.0          31.0   \n",
+       "57              92          3.0          4.0        1.0           8.0   \n",
+       "58              93         22.0         20.0        9.0          51.0   \n",
+       "59             106         12.0         30.0        6.0          48.0   \n",
+       "60             107         11.0         42.0       13.0          66.0   \n",
+       "\n",
+       "    no_incoming_ratio  no_outgoing_ratio  duration_total_incoming  \\\n",
+       "0            0.115385           0.807692                    342.0   \n",
+       "1            0.326531           0.448980                   1873.0   \n",
+       "2            0.600000           0.400000                    310.0   \n",
+       "3            0.307692           0.461538                   1963.0   \n",
+       "4            0.227273           0.681818                   5789.0   \n",
+       "..                ...                ...                      ...   \n",
+       "56           0.483871           0.419355                   3443.0   \n",
+       "57           0.375000           0.500000                    231.0   \n",
+       "58           0.431373           0.392157                   2534.0   \n",
+       "59           0.250000           0.625000                   3049.0   \n",
+       "60           0.166667           0.636364                   3804.0   \n",
+       "\n",
+       "    duration_total_outgoing  duration_max_incoming  duration_max_outgoing  \\\n",
+       "0                    2836.0                  196.0                  355.0   \n",
+       "1                    2789.0                  346.0                  694.0   \n",
+       "2                      19.0                  154.0                   19.0   \n",
+       "3                     849.0                 1037.0                  638.0   \n",
+       "4                   17046.0                 1966.0                 3830.0   \n",
+       "..                      ...                    ...                    ...   \n",
+       "56                   3636.0                  644.0                 1315.0   \n",
+       "57                    648.0                  167.0                  433.0   \n",
+       "58                   1444.0                  443.0                  672.0   \n",
+       "59                   2637.0                  878.0                  380.0   \n",
+       "60                   9977.0                 1519.0                 1943.0   \n",
+       "\n",
+       "    no_received  no_sent  no_all_sms  no_received_ratio  no_sent_ratio  \n",
+       "0           7.0      7.0        14.0           0.500000       0.500000  \n",
+       "1          20.0     14.0        34.0           0.588235       0.411765  \n",
+       "2          73.0     73.0       146.0           0.500000       0.500000  \n",
+       "3           8.0      2.0        10.0           0.800000       0.200000  \n",
+       "4           7.0      1.0         8.0           0.875000       0.125000  \n",
+       "..          ...      ...         ...                ...            ...  \n",
+       "56         83.0     44.0       127.0           0.653543       0.346457  \n",
+       "57          4.0      6.0        10.0           0.400000       0.600000  \n",
+       "58         48.0     19.0        67.0           0.716418       0.283582  \n",
+       "59         10.0     10.0        20.0           0.500000       0.500000  \n",
+       "60         80.0    176.0       256.0           0.312500       0.687500  \n",
+       "\n",
+       "[61 rows x 16 columns]"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "count_joined.reset_index()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "straw2analysis",
+   "language": "python",
+   "name": "straw2analysis"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/Untitled.ipynb b/Untitled.ipynb
new file mode 100644
index 0000000..40567fe
--- /dev/null
+++ b/Untitled.ipynb
@@ -0,0 +1,315 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "import sys\n",
+    "import matplotlib.pyplot as plt\n",
+    "import seaborn as sns\n",
+    "\n",
+    "nb_dir = os.path.split(os.getcwd())[0]\n",
+    "if nb_dir not in sys.path:\n",
+    "    sys.path.append(nb_dir)\n",
+    "    \n",
+    "from features.communication import *\n",
+    "import participants.query_db\n",
+    "\n",
+    "participants_inactive_usernames = participants.query_db.get_usernames()\n",
+    "df_sms = get_sms_data(participants_inactive_usernames)\n",
+    "df_calls = get_call_data(participants_inactive_usernames)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df_calls"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
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+       "  <thead>\n",
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+       "      <th></th>\n",
+       "      <th>id</th>\n",
+       "      <th>_id</th>\n",
+       "      <th>timestamp</th>\n",
+       "      <th>device_id</th>\n",
+       "      <th>call_type</th>\n",
+       "      <th>call_duration</th>\n",
+       "      <th>trace</th>\n",
+       "      <th>participant_id</th>\n",
+       "      <th>username</th>\n",
+       "      <th>freq</th>\n",
+       "      <th>contact_id</th>\n",
+       "    </tr>\n",
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+       "  <tbody>\n",
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+       "      <th>0</th>\n",
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+       "      <td>21</td>\n",
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+       "      <td>78082f9f-98c2-468d-b4a2-7c835bd812bd</td>\n",
+       "      <td>2</td>\n",
+       "      <td>237</td>\n",
+       "      <td>87ae5eb2c5b7fe30bea2821e2ec052453d89ea6b</td>\n",
+       "      <td>13</td>\n",
+       "      <td>uploader_20449</td>\n",
+       "      <td>21</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>210</td>\n",
+       "      <td>5</td>\n",
+       "      <td>1582561530334</td>\n",
+       "      <td>78082f9f-98c2-468d-b4a2-7c835bd812bd</td>\n",
+       "      <td>2</td>\n",
+       "      <td>126</td>\n",
+       "      <td>87ae5eb2c5b7fe30bea2821e2ec052453d89ea6b</td>\n",
+       "      <td>13</td>\n",
+       "      <td>uploader_20449</td>\n",
+       "      <td>21</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>253</td>\n",
+       "      <td>6</td>\n",
+       "      <td>1582627576077</td>\n",
+       "      <td>78082f9f-98c2-468d-b4a2-7c835bd812bd</td>\n",
+       "      <td>2</td>\n",
+       "      <td>255</td>\n",
+       "      <td>87ae5eb2c5b7fe30bea2821e2ec052453d89ea6b</td>\n",
+       "      <td>13</td>\n",
+       "      <td>uploader_20449</td>\n",
+       "      <td>21</td>\n",
+       "      <td>0</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",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4645</th>\n",
+       "      <td>5874</td>\n",
+       "      <td>131</td>\n",
+       "      <td>1625602519843</td>\n",
+       "      <td>4b62a655-cbf0-4ac0-a448-06726f45b56a</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2270</td>\n",
+       "      <td>f4ebca8dc7305fe424d6bf7fbcd2e5086f98b453</td>\n",
+       "      <td>90</td>\n",
+       "      <td>uploader_53573</td>\n",
+       "      <td>6</td>\n",
+       "      <td>9</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4646</th>\n",
+       "      <td>5882</td>\n",
+       "      <td>139</td>\n",
+       "      <td>1625753023456</td>\n",
+       "      <td>4b62a655-cbf0-4ac0-a448-06726f45b56a</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2e5d63f6fddca2b66be810b5946c42eda24f2dbe</td>\n",
+       "      <td>90</td>\n",
+       "      <td>uploader_53573</td>\n",
+       "      <td>2</td>\n",
+       "      <td>13</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4647</th>\n",
+       "      <td>5883</td>\n",
+       "      <td>140</td>\n",
+       "      <td>1625754998767</td>\n",
+       "      <td>4b62a655-cbf0-4ac0-a448-06726f45b56a</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2e5d63f6fddca2b66be810b5946c42eda24f2dbe</td>\n",
+       "      <td>90</td>\n",
+       "      <td>uploader_53573</td>\n",
+       "      <td>2</td>\n",
+       "      <td>13</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4648</th>\n",
+       "      <td>5884</td>\n",
+       "      <td>141</td>\n",
+       "      <td>1625823008392</td>\n",
+       "      <td>4b62a655-cbf0-4ac0-a448-06726f45b56a</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "      <td>7316d58b7bb7de097a2421c56010ac024a489451</td>\n",
+       "      <td>90</td>\n",
+       "      <td>uploader_53573</td>\n",
+       "      <td>1</td>\n",
+       "      <td>21</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4649</th>\n",
+       "      <td>5903</td>\n",
+       "      <td>158</td>\n",
+       "      <td>1626110930233</td>\n",
+       "      <td>4b62a655-cbf0-4ac0-a448-06726f45b56a</td>\n",
+       "      <td>2</td>\n",
+       "      <td>53</td>\n",
+       "      <td>7db4e9acf7c73837ddecdae5da523a28c774ba94</td>\n",
+       "      <td>90</td>\n",
+       "      <td>uploader_53573</td>\n",
+       "      <td>1</td>\n",
+       "      <td>24</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>4650 rows × 11 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        id  _id      timestamp                             device_id  \\\n",
+       "0      118    1  1581936081010  78082f9f-98c2-468d-b4a2-7c835bd812bd   \n",
+       "1      176    3  1582295247982  78082f9f-98c2-468d-b4a2-7c835bd812bd   \n",
+       "2      209    4  1582305634014  78082f9f-98c2-468d-b4a2-7c835bd812bd   \n",
+       "3      210    5  1582561530334  78082f9f-98c2-468d-b4a2-7c835bd812bd   \n",
+       "4      253    6  1582627576077  78082f9f-98c2-468d-b4a2-7c835bd812bd   \n",
+       "...    ...  ...            ...                                   ...   \n",
+       "4645  5874  131  1625602519843  4b62a655-cbf0-4ac0-a448-06726f45b56a   \n",
+       "4646  5882  139  1625753023456  4b62a655-cbf0-4ac0-a448-06726f45b56a   \n",
+       "4647  5883  140  1625754998767  4b62a655-cbf0-4ac0-a448-06726f45b56a   \n",
+       "4648  5884  141  1625823008392  4b62a655-cbf0-4ac0-a448-06726f45b56a   \n",
+       "4649  5903  158  1626110930233  4b62a655-cbf0-4ac0-a448-06726f45b56a   \n",
+       "\n",
+       "      call_type  call_duration                                     trace  \\\n",
+       "0             2              0  87ae5eb2c5b7fe30bea2821e2ec052453d89ea6b   \n",
+       "1             1            196  87ae5eb2c5b7fe30bea2821e2ec052453d89ea6b   \n",
+       "2             2            237  87ae5eb2c5b7fe30bea2821e2ec052453d89ea6b   \n",
+       "3             2            126  87ae5eb2c5b7fe30bea2821e2ec052453d89ea6b   \n",
+       "4             2            255  87ae5eb2c5b7fe30bea2821e2ec052453d89ea6b   \n",
+       "...         ...            ...                                       ...   \n",
+       "4645          2           2270  f4ebca8dc7305fe424d6bf7fbcd2e5086f98b453   \n",
+       "4646          3              0  2e5d63f6fddca2b66be810b5946c42eda24f2dbe   \n",
+       "4647          3              0  2e5d63f6fddca2b66be810b5946c42eda24f2dbe   \n",
+       "4648          2              0  7316d58b7bb7de097a2421c56010ac024a489451   \n",
+       "4649          2             53  7db4e9acf7c73837ddecdae5da523a28c774ba94   \n",
+       "\n",
+       "      participant_id        username  freq  contact_id  \n",
+       "0                 13  uploader_20449    21           0  \n",
+       "1                 13  uploader_20449    21           0  \n",
+       "2                 13  uploader_20449    21           0  \n",
+       "3                 13  uploader_20449    21           0  \n",
+       "4                 13  uploader_20449    21           0  \n",
+       "...              ...             ...   ...         ...  \n",
+       "4645              90  uploader_53573     6           9  \n",
+       "4646              90  uploader_53573     2          13  \n",
+       "4647              90  uploader_53573     2          13  \n",
+       "4648              90  uploader_53573     1          21  \n",
+       "4649              90  uploader_53573     1          24  \n",
+       "\n",
+       "[4650 rows x 11 columns]"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "contact_features(enumerate_contacts(df_calls))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "straw2analysis",
+   "language": "python",
+   "name": "straw2analysis"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/Untitled1.ipynb b/Untitled1.ipynb
new file mode 100644
index 0000000..8ac4962
--- /dev/null
+++ b/Untitled1.ipynb
@@ -0,0 +1,788 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "import sys\n",
+    "import matplotlib.pyplot as plt\n",
+    "import seaborn as sns\n",
+    "\n",
+    "nb_dir = os.path.split(os.getcwd())[0]\n",
+    "if nb_dir not in sys.path:\n",
+    "    sys.path.append(nb_dir)\n",
+    "    \n",
+    "from features.communication import *\n",
+    "import participants.query_db\n",
+    "\n",
+    "participants_inactive_usernames = participants.query_db.get_usernames()\n",
+    "df_sms = get_sms_data(participants_inactive_usernames)\n",
+    "df_calls = get_call_data(participants_inactive_usernames)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>id</th>\n",
+       "      <th>_id</th>\n",
+       "      <th>timestamp</th>\n",
+       "      <th>device_id</th>\n",
+       "      <th>call_type</th>\n",
+       "      <th>call_duration</th>\n",
+       "      <th>trace</th>\n",
+       "      <th>participant_id</th>\n",
+       "      <th>username</th>\n",
+       "      <th>freq</th>\n",
+       "      <th>contact_id</th>\n",
+       "      <th>total_call_duration</th>\n",
+       "      <th>no_contacts</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>118</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1581936081010</td>\n",
+       "      <td>78082f9f-98c2-468d-b4a2-7c835bd812bd</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "      <td>87ae5eb2c5b7fe30bea2821e2ec052453d89ea6b</td>\n",
+       "      <td>13</td>\n",
+       "      <td>uploader_20449</td>\n",
+       "      <td>21</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2844</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>176</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1582295247982</td>\n",
+       "      <td>78082f9f-98c2-468d-b4a2-7c835bd812bd</td>\n",
+       "      <td>1</td>\n",
+       "      <td>196</td>\n",
+       "      <td>87ae5eb2c5b7fe30bea2821e2ec052453d89ea6b</td>\n",
+       "      <td>13</td>\n",
+       "      <td>uploader_20449</td>\n",
+       "      <td>21</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2844</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>209</td>\n",
+       "      <td>4</td>\n",
+       "      <td>1582305634014</td>\n",
+       "      <td>78082f9f-98c2-468d-b4a2-7c835bd812bd</td>\n",
+       "      <td>2</td>\n",
+       "      <td>237</td>\n",
+       "      <td>87ae5eb2c5b7fe30bea2821e2ec052453d89ea6b</td>\n",
+       "      <td>13</td>\n",
+       "      <td>uploader_20449</td>\n",
+       "      <td>21</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2844</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>210</td>\n",
+       "      <td>5</td>\n",
+       "      <td>1582561530334</td>\n",
+       "      <td>78082f9f-98c2-468d-b4a2-7c835bd812bd</td>\n",
+       "      <td>2</td>\n",
+       "      <td>126</td>\n",
+       "      <td>87ae5eb2c5b7fe30bea2821e2ec052453d89ea6b</td>\n",
+       "      <td>13</td>\n",
+       "      <td>uploader_20449</td>\n",
+       "      <td>21</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2844</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>253</td>\n",
+       "      <td>6</td>\n",
+       "      <td>1582627576077</td>\n",
+       "      <td>78082f9f-98c2-468d-b4a2-7c835bd812bd</td>\n",
+       "      <td>2</td>\n",
+       "      <td>255</td>\n",
+       "      <td>87ae5eb2c5b7fe30bea2821e2ec052453d89ea6b</td>\n",
+       "      <td>13</td>\n",
+       "      <td>uploader_20449</td>\n",
+       "      <td>21</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2844</td>\n",
+       "      <td>5</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>4352</th>\n",
+       "      <td>5560</td>\n",
+       "      <td>59</td>\n",
+       "      <td>1621275689589</td>\n",
+       "      <td>9f54e35c-d7cb-4f4c-8dc1-17dc86f2635e</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "      <td>5eb72fe829c2af4a654007220119bdcf47499555</td>\n",
+       "      <td>107</td>\n",
+       "      <td>uploader_89606</td>\n",
+       "      <td>1</td>\n",
+       "      <td>17</td>\n",
+       "      <td>0</td>\n",
+       "      <td>22</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4336</th>\n",
+       "      <td>5443</td>\n",
+       "      <td>29</td>\n",
+       "      <td>1620746142636</td>\n",
+       "      <td>9f54e35c-d7cb-4f4c-8dc1-17dc86f2635e</td>\n",
+       "      <td>2</td>\n",
+       "      <td>189</td>\n",
+       "      <td>6dd761532337dfe596eb2e34f4c91216b38e28e2</td>\n",
+       "      <td>107</td>\n",
+       "      <td>uploader_89606</td>\n",
+       "      <td>1</td>\n",
+       "      <td>18</td>\n",
+       "      <td>189</td>\n",
+       "      <td>22</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4316</th>\n",
+       "      <td>5237</td>\n",
+       "      <td>10</td>\n",
+       "      <td>1620140109908</td>\n",
+       "      <td>9f54e35c-d7cb-4f4c-8dc1-17dc86f2635e</td>\n",
+       "      <td>2</td>\n",
+       "      <td>85</td>\n",
+       "      <td>9c4eab1dfc0114aecd64a7f594977acc9ab7936c</td>\n",
+       "      <td>107</td>\n",
+       "      <td>uploader_89606</td>\n",
+       "      <td>1</td>\n",
+       "      <td>19</td>\n",
+       "      <td>85</td>\n",
+       "      <td>22</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4347</th>\n",
+       "      <td>5524</td>\n",
+       "      <td>44</td>\n",
+       "      <td>1620971679122</td>\n",
+       "      <td>9f54e35c-d7cb-4f4c-8dc1-17dc86f2635e</td>\n",
+       "      <td>1</td>\n",
+       "      <td>120</td>\n",
+       "      <td>a9fa73b6137d09288429de20172095978730e4b8</td>\n",
+       "      <td>107</td>\n",
+       "      <td>uploader_89606</td>\n",
+       "      <td>1</td>\n",
+       "      <td>20</td>\n",
+       "      <td>120</td>\n",
+       "      <td>22</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4331</th>\n",
+       "      <td>5364</td>\n",
+       "      <td>26</td>\n",
+       "      <td>1620630328635</td>\n",
+       "      <td>9f54e35c-d7cb-4f4c-8dc1-17dc86f2635e</td>\n",
+       "      <td>2</td>\n",
+       "      <td>184</td>\n",
+       "      <td>cfe98eee4a27b377f4cde1ea5c39d24d0475b533</td>\n",
+       "      <td>107</td>\n",
+       "      <td>uploader_89606</td>\n",
+       "      <td>1</td>\n",
+       "      <td>21</td>\n",
+       "      <td>184</td>\n",
+       "      <td>22</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>4650 rows × 13 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        id  _id      timestamp                             device_id  \\\n",
+       "0      118    1  1581936081010  78082f9f-98c2-468d-b4a2-7c835bd812bd   \n",
+       "1      176    3  1582295247982  78082f9f-98c2-468d-b4a2-7c835bd812bd   \n",
+       "2      209    4  1582305634014  78082f9f-98c2-468d-b4a2-7c835bd812bd   \n",
+       "3      210    5  1582561530334  78082f9f-98c2-468d-b4a2-7c835bd812bd   \n",
+       "4      253    6  1582627576077  78082f9f-98c2-468d-b4a2-7c835bd812bd   \n",
+       "...    ...  ...            ...                                   ...   \n",
+       "4352  5560   59  1621275689589  9f54e35c-d7cb-4f4c-8dc1-17dc86f2635e   \n",
+       "4336  5443   29  1620746142636  9f54e35c-d7cb-4f4c-8dc1-17dc86f2635e   \n",
+       "4316  5237   10  1620140109908  9f54e35c-d7cb-4f4c-8dc1-17dc86f2635e   \n",
+       "4347  5524   44  1620971679122  9f54e35c-d7cb-4f4c-8dc1-17dc86f2635e   \n",
+       "4331  5364   26  1620630328635  9f54e35c-d7cb-4f4c-8dc1-17dc86f2635e   \n",
+       "\n",
+       "      call_type  call_duration                                     trace  \\\n",
+       "0             2              0  87ae5eb2c5b7fe30bea2821e2ec052453d89ea6b   \n",
+       "1             1            196  87ae5eb2c5b7fe30bea2821e2ec052453d89ea6b   \n",
+       "2             2            237  87ae5eb2c5b7fe30bea2821e2ec052453d89ea6b   \n",
+       "3             2            126  87ae5eb2c5b7fe30bea2821e2ec052453d89ea6b   \n",
+       "4             2            255  87ae5eb2c5b7fe30bea2821e2ec052453d89ea6b   \n",
+       "...         ...            ...                                       ...   \n",
+       "4352          2              0  5eb72fe829c2af4a654007220119bdcf47499555   \n",
+       "4336          2            189  6dd761532337dfe596eb2e34f4c91216b38e28e2   \n",
+       "4316          2             85  9c4eab1dfc0114aecd64a7f594977acc9ab7936c   \n",
+       "4347          1            120  a9fa73b6137d09288429de20172095978730e4b8   \n",
+       "4331          2            184  cfe98eee4a27b377f4cde1ea5c39d24d0475b533   \n",
+       "\n",
+       "      participant_id        username  freq  contact_id  total_call_duration  \\\n",
+       "0                 13  uploader_20449    21           0                 2844   \n",
+       "1                 13  uploader_20449    21           0                 2844   \n",
+       "2                 13  uploader_20449    21           0                 2844   \n",
+       "3                 13  uploader_20449    21           0                 2844   \n",
+       "4                 13  uploader_20449    21           0                 2844   \n",
+       "...              ...             ...   ...         ...                  ...   \n",
+       "4352             107  uploader_89606     1          17                    0   \n",
+       "4336             107  uploader_89606     1          18                  189   \n",
+       "4316             107  uploader_89606     1          19                   85   \n",
+       "4347             107  uploader_89606     1          20                  120   \n",
+       "4331             107  uploader_89606     1          21                  184   \n",
+       "\n",
+       "      no_contacts  \n",
+       "0               5  \n",
+       "1               5  \n",
+       "2               5  \n",
+       "3               5  \n",
+       "4               5  \n",
+       "...           ...  \n",
+       "4352           22  \n",
+       "4336           22  \n",
+       "4316           22  \n",
+       "4347           22  \n",
+       "4331           22  \n",
+       "\n",
+       "[4650 rows x 13 columns]"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "contact_features(enumerate_contacts(df_calls))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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+       "      <td>9f54e35c-d7cb-4f4c-8dc1-17dc86f2635e</td>\n",
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+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>5864 rows × 11 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        id  _id      timestamp                             device_id  \\\n",
+       "195    379    7  1582964434597  78082f9f-98c2-468d-b4a2-7c835bd812bd   \n",
+       "196    380    8  1582964434974  78082f9f-98c2-468d-b4a2-7c835bd812bd   \n",
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+       "...    ...  ...            ...                                   ...   \n",
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+       "\n",
+       "      message_type                                     trace  participant_id  \\\n",
+       "195              2  417b9c87f5b573530bcffba8577777b3a964d671              13   \n",
+       "196              2  417b9c87f5b573530bcffba8577777b3a964d671              13   \n",
+       "197              2  417b9c87f5b573530bcffba8577777b3a964d671              13   \n",
+       "198              2  417b9c87f5b573530bcffba8577777b3a964d671              13   \n",
+       "199              2  417b9c87f5b573530bcffba8577777b3a964d671              13   \n",
+       "...            ...                                       ...             ...   \n",
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+       "5417             1  198d7e63a2b4d8a7ca9bb92f74e6974ca17edc56             107   \n",
+       "5447             1  d4a67b53e704247de47064850efd3647e8dcaffb             107   \n",
+       "5440             1  ffbc6a5f0f601cf2d9cdad9d3a588633e1a1967c             107   \n",
+       "\n",
+       "            username  freq  contact_id  no_contacts  \n",
+       "195   uploader_20449     5           0            6  \n",
+       "196   uploader_20449     5           0            6  \n",
+       "197   uploader_20449     5           0            6  \n",
+       "198   uploader_20449     5           0            6  \n",
+       "199   uploader_20449     5           0            6  \n",
+       "...              ...   ...         ...          ...  \n",
+       "5193  uploader_89606     3          12           16  \n",
+       "5194  uploader_89606     3          12           16  \n",
+       "5417  uploader_89606     1          13           16  \n",
+       "5447  uploader_89606     1          14           16  \n",
+       "5440  uploader_89606     1          15           16  \n",
+       "\n",
+       "[5864 rows x 11 columns]"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "contact_features(enumerate_contacts(df_sms))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
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+       "      <th></th>\n",
+       "      <th>participant_id</th>\n",
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+       "      <td>0.512821</td>\n",
+       "      <td>0.428571</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>59</th>\n",
+       "      <td>106</td>\n",
+       "      <td>0.705882</td>\n",
+       "      <td>0.454545</td>\n",
+       "      <td>0.750000</td>\n",
+       "      <td>0.769231</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>60</th>\n",
+       "      <td>107</td>\n",
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+       "      <td>0.879121</td>\n",
+       "      <td>0.192661</td>\n",
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+       "  </tbody>\n",
+       "</table>\n",
+       "<p>61 rows × 5 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    participant_id  no_calls_no_sms_ratio  \\\n",
+       "0               13               0.650000   \n",
+       "1               14               0.590361   \n",
+       "2               15               0.033113   \n",
+       "3               16               0.565217   \n",
+       "4               17               0.916667   \n",
+       "..             ...                    ...   \n",
+       "56              91               0.196203   \n",
+       "57              92               0.444444   \n",
+       "58              93               0.432203   \n",
+       "59             106               0.705882   \n",
+       "60             107               0.204969   \n",
+       "\n",
+       "    no_incoming_calls_no_recieved_sms_ratio  \\\n",
+       "0                                  0.700000   \n",
+       "1                                  0.555556   \n",
+       "2                                  0.960526   \n",
+       "3                                  0.666667   \n",
+       "4                                  0.259259   \n",
+       "..                                      ...   \n",
+       "56                                 0.846939   \n",
+       "57                                 0.571429   \n",
+       "58                                 0.685714   \n",
+       "59                                 0.454545   \n",
+       "60                                 0.879121   \n",
+       "\n",
+       "    no_outgoing_calls_no_sent_sms_ratio  \\\n",
+       "0                              0.750000   \n",
+       "1                              0.611111   \n",
+       "2                              0.026667   \n",
+       "3                              0.750000   \n",
+       "4                              0.983607   \n",
+       "..                                  ...   \n",
+       "56                             0.228070   \n",
+       "57                             0.400000   \n",
+       "58                             0.512821   \n",
+       "59                             0.750000   \n",
+       "60                             0.192661   \n",
+       "\n",
+       "    no_calls_contacts_no_sms_contacts_ratio  \n",
+       "0                                  0.454545  \n",
+       "1                                  0.714286  \n",
+       "2                                  0.173913  \n",
+       "3                                  0.666667  \n",
+       "4                                  0.857143  \n",
+       "..                                      ...  \n",
+       "56                                 0.666667  \n",
+       "57                                 0.600000  \n",
+       "58                                 0.428571  \n",
+       "59                                 0.769231  \n",
+       "60                                 0.578947  \n",
+       "\n",
+       "[61 rows x 5 columns]"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "calls_sms_features(df_calls, df_sms)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "straw2analysis",
+   "language": "python",
+   "name": "straw2analysis"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/exploration/expl_communication.py b/exploration/expl_communication.py
index e1a0c27..6a6ebc8 100644
--- a/exploration/expl_communication.py
+++ b/exploration/expl_communication.py
@@ -6,7 +6,7 @@
 #       extension: .py
 #       format_name: percent
 #       format_version: '1.3'
-#       jupytext_version: 1.11.2
+#       jupytext_version: 1.11.4
 #   kernelspec:
 #     display_name: straw2analysis
 #     language: python
@@ -39,6 +39,9 @@ print(df_calls)
 # %%
 count_comms(df_calls)
 
+# %%
+enumerate_contacts(df_calls)
+
 # %%
 df_sms = get_sms_data(["nokia_0000003"])
 count_comms(df_sms)
@@ -53,6 +56,15 @@ import participants.query_db
 participants_inactive_usernames = participants.query_db.get_usernames()
 df_calls_inactive = get_call_data(participants_inactive_usernames)
 
+# %%
+participants_inactive_usernames
+
+# %%
+df_calls_inactive.head()
+
+# %%
+enumerate_contacts(df_calls_inactive).head()
+
 # %%
 df_calls_features = count_comms(df_calls_inactive)
 df_calls_features.head()
@@ -70,6 +82,9 @@ calls_number = pd.wide_to_long(
     suffix="\D+",
 )
 
+# %%
+calls_number
+
 # %%
 sns.displot(calls_number, x="no", hue="call_type", binwidth=5, element="step", height=8)
 
diff --git a/features/communication.py b/features/communication.py
index d1dc4ee..a3c917c 100644
--- a/features/communication.py
+++ b/features/communication.py
@@ -86,7 +86,8 @@ def enumerate_contacts(comm_df: pd.DataFrame) -> pd.DataFrame:
     # In other words, recode the contacts into integers from 0 to n_contacts,
     # so that the first one is contacted the most often.
     contact_ids = (
-        contact_counts.groupby("participant_id")  # Group again for enumeration.
+        # Group again for enumeration.
+        contact_counts.groupby("participant_id")
         .cumcount()  # Enumerate (count) rows *within* participants.
         .to_frame("contact_id")
     )
@@ -150,8 +151,10 @@ def count_comms(comm_df: pd.DataFrame) -> pd.DataFrame:
         comm_features = comm_counts.join(comm_duration_total)
         comm_features = comm_features.join(comm_duration_max)
         try:
-            comm_features.drop(columns="duration_total_" + call_types[3], inplace=True)
-            comm_features.drop(columns="duration_max_" + call_types[3], inplace=True)
+            comm_features.drop(columns="duration_total_" +
+                               call_types[3], inplace=True)
+            comm_features.drop(columns="duration_max_" +
+                               call_types[3], inplace=True)
         # The missed calls are always of 0 duration.
         except KeyError:
             pass
@@ -172,19 +175,145 @@ def count_comms(comm_df: pd.DataFrame) -> pd.DataFrame:
         )
         # Ratio of incoming and outgoing messages to all messages.
     else:
-        raise KeyError("The dataframe contains neither call_type or message_type")
+        raise KeyError(
+            "The dataframe contains neither call_type or message_type")
     return comm_features
 
 
-def contact_features():
-    # TODO Implement a method that takes a DF with enumerated contacts as argument and calculates:
-    # * Duration of calls per caller (for most common callers)
-    # * Determine work vs non-work contacts by work hours heuristics
-    # * Number of people contacted
-    # And similarly for SMS.
-    pass
+def contact_features(df_enumerated: pd.DataFrame) -> pd.DataFrame:
+    """
+    Counts the number of people contacted (for each participant) and, if
+    df_enumerated is a dataframe containing calls data, the total duration
+    of calls between a participant and each of her contacts. 
+
+    Parameters
+    ----------
+    df_enumerated: pd.DataFrame
+        A dataframe of calls or SMSes; return of function enumerate_contacts.
+
+    Returns
+    -------
+    comm_df: pd.DataFrame
+        The altered dataframe with the column no_contacts and, if df_enumerated
+        contains calls data, an additional column total_call_duration.
+    """
+
+    # Check whether df contains calls or SMS data since some
+    # features we want to calculate are type-specyfic
+    if "call_duration" in df_enumerated:
+        # Add a column with the total duration of calls between two people
+        duration_count = (
+            df_enumerated.groupby(
+                ["participant_id", "contact_id"]
+            )
+            # For each participant and for each caller, sum durations of their calls
+            ["call_duration"].sum()
+            .reset_index()  # Make index (which is actually the participant id) a normal column
+            .rename(columns={"call_duration": "total_call_duration"})
+        )
+        # The new dataframe now contains columns containing information about
+        # participants, callers and the total duration of their calls. All that
+        # is now left to do is to merge the original df with the new one.
+        df_enumerated = df_enumerated.merge(
+            duration_count,
+            on=["participant_id", "contact_id"]
+            )
+
+    contact_count = (
+        df_enumerated.groupby(["participant_id"])
+        .nunique()["contact_id"] # For each participant, count the number of distinct contacts
+        .reset_index()  # Make index (which is actually the participant id) a normal column
+        .rename(columns={"contact_id": "no_contacts"})
+    )
+    
+    df_enumerated = (
+        # Merge df with the newely created df containing info about number of contacts
+        df_enumerated.merge(contact_count, on="participant_id")
+        # Sort first by participant_id and then by contact_id and
+        # thereby restore the inital ordering of input dataframes.
+        .sort_values(["participant_id", "contact_id"])
+    )
+
+    # TODO:Determine work vs non-work contacts by work hours heuristics
+
+    return df_enumerated
 
 
-def calls_sms_features():
-    # TODO Relate the calls and sms data, such as comparing the number of (missed) calls and messages.
-    pass
+def calls_sms_features(df_calls: pd.DataFrame, df_sms: pd.DataFrame) -> pd.DataFrame:
+    """
+    Calculates additional features relating calls and sms data.
+
+    Parameters
+    ----------
+    df_calls: pd.DataFrame
+        A dataframe of calls (return of get_call_data).
+    df_sms: pd.DataFrame
+        A dataframe of calls (return of get_sms_data).
+
+    Returns
+    -------
+    df_calls_sms: pd.DataFrame
+        The list of features relating calls and sms data for every participant.
+        These are:
+        * no_calls_no_sms_ratio:
+            proportion of calls in total number of communications
+        * no_incoming_calls_no_recieved_sms_ratio:
+            proportion of incoming calls in total number of incoming/recieved communications
+        * no_outgoing_calls_no_sent_sms_ratio:
+            proportion of outgoing calls in total number of outgoing/sent communications
+        * no_calls_contacts_no_sms_contacts_ratio:
+            proportion of calls contacts in total number of communication contacts 
+    """
+
+    count_calls = count_comms(df_calls)
+    count_sms = count_comms(df_sms)
+
+    count_joined = (
+        count_calls.merge(
+            count_sms, on="participant_id", suffixes=("_calls", "_sms")
+        )  # Merge calls and sms features
+        .reset_index()  # Make participant_id a regular column
+        .assign(
+            no_calls_no_sms_ratio=(
+                lambda x: x.no_all_calls / (x.no_all_calls + x.no_all_sms)
+            ),
+            no_incoming_calls_no_recieved_sms_ratio=(
+                lambda x: x.no_received / (x.no_incoming + x.no_received)
+            ),
+            no_outgoing_calls_no_sent_sms_ratio=(
+                lambda x: x.no_outgoing / (x.no_outgoing + x.no_sent)
+            )  # Calculate new features and create additional columns
+        )[
+            ["participant_id",
+             "no_calls_no_sms_ratio",
+             "no_incoming_calls_no_recieved_sms_ratio",
+             "no_outgoing_calls_no_sent_sms_ratio"]
+        ]  # Filter out only the relevant feautres
+    )
+
+    features_calls = contact_features(enumerate_contacts(df_calls))
+    features_sms = contact_features(enumerate_contacts(df_sms))
+
+    features_joined = (
+        features_calls.merge(
+            features_sms, on="participant_id", suffixes=("_calls", "_sms")
+        )  # Merge calls and sms features
+        .reset_index()  # Make participand_id a regular column
+        .assign(
+            no_calls_contacts_no_sms_contacts_ratio=(
+                lambda x: x.no_contacts_calls /
+                    (x.no_contacts_calls + x.no_contacts_sms)
+            )  # Calculate new features and create additional columns
+        )[
+            ["participant_id",
+             "no_calls_contacts_no_sms_contacts_ratio"]
+        ]  # Filter out only the relevant feautres
+        # Since we are interested only in some features and ignored
+        # others, a lot of duplicate rows were created. Remove them.
+        .drop_duplicates()
+    )
+
+    # Join the newely created dataframes
+    df_calls_sms = count_joined.merge(features_joined, on="participant_id")
+
+    return df_calls_sms