{
 "cells": [
  {
   "cell_type": "markdown",
   "source": [
    "## Prerequisites\n",
    "\n",
    "Run this cell to prepare the environment. This step is obligatory."
   ],
   "metadata": {
    "id": "vtGqS-SRKnlx"
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 46390,
     "status": "ok",
     "timestamp": 1682533467826,
     "user": {
      "displayName": "Anatoliy Zaykovskiy",
      "userId": "11710160701524337708"
     },
     "user_tz": -180
    },
    "id": "bieK6_UAZ94I",
    "outputId": "180531d1-1adb-4299-ba62-dd724465cd66"
   },
   "outputs": [],
   "source": [
    "!pip install retentioneering"
   ]
  },
  {
   "cell_type": "markdown",
   "source": [
    "The full text of [Eventstream user guide](https://doc.retentioneering.com/release3/doc/user_guides/eventstream.html) is available on the retentioneering website."
   ],
   "metadata": {
    "id": "ehhXXP78mkKN"
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "## Eventstream creation"
   ],
   "metadata": {
    "id": "5lNAjTawnauQ"
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "### Default field names"
   ],
   "metadata": {
    "id": "aTSWoRC3neE1"
   }
  },
  {
   "cell_type": "code",
   "source": [
    "import pandas as pd\n",
    "\n",
    "df1 = pd.DataFrame(\n",
    "    [\n",
    "        ['user_1', 'A', '2023-01-01 00:00:00'],\n",
    "        ['user_1', 'B', '2023-01-01 00:00:01'],\n",
    "        ['user_2', 'B', '2023-01-01 00:00:02'],\n",
    "        ['user_2', 'A', '2023-01-01 00:00:03'],\n",
    "        ['user_2', 'A', '2023-01-01 00:00:04'],\n",
    "    ],\n",
    "    columns=['user_id', 'event', 'timestamp']\n",
    ")"
   ],
   "metadata": {
    "id": "Qnv8CLLknifp"
   },
   "execution_count": 2,
   "outputs": []
  },
  {
   "cell_type": "code",
   "source": [
    "from retentioneering.eventstream import Eventstream\n",
    "\n",
    "stream1 = Eventstream(df1)"
   ],
   "metadata": {
    "id": "RKad2rLIn7AX"
   },
   "execution_count": 3,
   "outputs": []
  },
  {
   "cell_type": "code",
   "source": [
    "stream1.to_dataframe()"
   ],
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 250
    },
    "id": "GvdbciRron1h",
    "executionInfo": {
     "status": "ok",
     "timestamp": 1682533511878,
     "user_tz": -180,
     "elapsed": 6,
     "user": {
      "displayName": "Anatoliy Zaykovskiy",
      "userId": "11710160701524337708"
     }
    },
    "outputId": "5f7d8db2-6188-43cb-f03e-eab737321966"
   },
   "execution_count": 4,
   "outputs": [
    {
     "data": {
      "text/plain": "                               event_id event_type  event_index event  \\\n0  67ca4c62-f168-48b9-bca5-31004aca1ea4        raw            0     A   \n1  e363da60-1e37-4b31-b942-f080a090afb5        raw            1     B   \n2  f37511d4-882c-401b-8a20-b2d60497802e        raw            2     B   \n3  26c62d80-ec33-4bb0-9cb0-4c1c26b8243a        raw            3     A   \n4  85510a1b-10e4-4284-aa6c-ef8c8ade2890        raw            4     A   \n\n            timestamp user_id  \n0 2023-01-01 00:00:00  user_1  \n1 2023-01-01 00:00:01  user_1  \n2 2023-01-01 00:00:02  user_2  \n3 2023-01-01 00:00:03  user_2  \n4 2023-01-01 00:00:04  user_2  ",
      "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>event_id</th>\n      <th>event_type</th>\n      <th>event_index</th>\n      <th>event</th>\n      <th>timestamp</th>\n      <th>user_id</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>67ca4c62-f168-48b9-bca5-31004aca1ea4</td>\n      <td>raw</td>\n      <td>0</td>\n      <td>A</td>\n      <td>2023-01-01 00:00:00</td>\n      <td>user_1</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>e363da60-1e37-4b31-b942-f080a090afb5</td>\n      <td>raw</td>\n      <td>1</td>\n      <td>B</td>\n      <td>2023-01-01 00:00:01</td>\n      <td>user_1</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>f37511d4-882c-401b-8a20-b2d60497802e</td>\n      <td>raw</td>\n      <td>2</td>\n      <td>B</td>\n      <td>2023-01-01 00:00:02</td>\n      <td>user_2</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>26c62d80-ec33-4bb0-9cb0-4c1c26b8243a</td>\n      <td>raw</td>\n      <td>3</td>\n      <td>A</td>\n      <td>2023-01-01 00:00:03</td>\n      <td>user_2</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>85510a1b-10e4-4284-aa6c-ef8c8ade2890</td>\n      <td>raw</td>\n      <td>4</td>\n      <td>A</td>\n      <td>2023-01-01 00:00:04</td>\n      <td>user_2</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ]
  },
  {
   "cell_type": "markdown",
   "source": [
    "### Custom field names"
   ],
   "metadata": {
    "id": "wgEuD1LbpIch"
   }
  },
  {
   "cell_type": "code",
   "source": [
    "df2 = pd.DataFrame(\n",
    "    [\n",
    "        ['user_1', 'A', '2023-01-01 00:00:00'],\n",
    "        ['user_1', 'B', '2023-01-01 00:00:01'],\n",
    "        ['user_2', 'B', '2023-01-01 00:00:02'],\n",
    "        ['user_2', 'A', '2023-01-01 00:00:03'],\n",
    "        ['user_2', 'A', '2023-01-01 00:00:04']\n",
    "    ],\n",
    "     columns=['client_id', 'action', 'datetime']\n",
    ")\n",
    "\n",
    "raw_data_schema = {\n",
    "    'user_id': 'client_id',\n",
    "    'event_name': 'action',\n",
    "    'event_timestamp': 'datetime'\n",
    "}\n",
    "\n",
    "stream2 = Eventstream(df2, raw_data_schema=raw_data_schema)\n",
    "stream2.to_dataframe().head(3)"
   ],
   "metadata": {
    "id": "MahQ47jZpWQ9",
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 187
    },
    "executionInfo": {
     "status": "ok",
     "timestamp": 1682533522926,
     "user_tz": -180,
     "elapsed": 864,
     "user": {
      "displayName": "Anatoliy Zaykovskiy",
      "userId": "11710160701524337708"
     }
    },
    "outputId": "906f96fc-cf3b-4d7b-f70c-0a66e6179680"
   },
   "execution_count": 5,
   "outputs": [
    {
     "data": {
      "text/plain": "                               event_id event_type  event_index event  \\\n0  9c2e03b3-9e16-4c59-ab13-21fe310f3b0f        raw            0     A   \n1  3fce68ce-3e54-411b-bc68-7ca05c172222        raw            1     B   \n2  84871810-68fa-44d0-aa1b-9b4d7d399f83        raw            2     B   \n\n            timestamp user_id  \n0 2023-01-01 00:00:00  user_1  \n1 2023-01-01 00:00:01  user_1  \n2 2023-01-01 00:00:02  user_2  ",
      "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>event_id</th>\n      <th>event_type</th>\n      <th>event_index</th>\n      <th>event</th>\n      <th>timestamp</th>\n      <th>user_id</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>9c2e03b3-9e16-4c59-ab13-21fe310f3b0f</td>\n      <td>raw</td>\n      <td>0</td>\n      <td>A</td>\n      <td>2023-01-01 00:00:00</td>\n      <td>user_1</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>3fce68ce-3e54-411b-bc68-7ca05c172222</td>\n      <td>raw</td>\n      <td>1</td>\n      <td>B</td>\n      <td>2023-01-01 00:00:01</td>\n      <td>user_1</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>84871810-68fa-44d0-aa1b-9b4d7d399f83</td>\n      <td>raw</td>\n      <td>2</td>\n      <td>B</td>\n      <td>2023-01-01 00:00:02</td>\n      <td>user_2</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ]
  },
  {
   "cell_type": "code",
   "source": [
    "df3 = pd.DataFrame(\n",
    "    [\n",
    "        ['user_1', 'A', '2023-01-01 00:00:00', 'session_1'],\n",
    "        ['user_1', 'B', '2023-01-01 00:00:01', 'session_1'],\n",
    "        ['user_2', 'B', '2023-01-01 00:00:02', 'session_2'],\n",
    "        ['user_2', 'A', '2023-01-01 00:00:03', 'session_3'],\n",
    "        ['user_2', 'A', '2023-01-01 00:00:04', 'session_3']\n",
    "    ],\n",
    "    columns=['client_id', 'action', 'datetime', 'session']\n",
    ")\n",
    "\n",
    "raw_data_schema = {\n",
    "    'user_id': 'client_id',\n",
    "    'event_name': 'action',\n",
    "    'event_timestamp': 'datetime',\n",
    "    'custom_cols': [\n",
    "        {\n",
    "            'raw_data_col': 'session',\n",
    "            'custom_col': 'session_id'\n",
    "        }\n",
    "    ]\n",
    "}\n",
    "\n",
    "stream3 = Eventstream(df3, raw_data_schema=raw_data_schema)\n",
    "stream3.to_dataframe().head(3)"
   ],
   "metadata": {
    "id": "nF_GgR1Kpt5S",
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 240
    },
    "executionInfo": {
     "status": "ok",
     "timestamp": 1682533616073,
     "user_tz": -180,
     "elapsed": 9,
     "user": {
      "displayName": "Anatoliy Zaykovskiy",
      "userId": "11710160701524337708"
     }
    },
    "outputId": "bebbf70d-24bf-4a7a-fba1-ec513e255ad3"
   },
   "execution_count": 6,
   "outputs": [
    {
     "data": {
      "text/plain": "                               event_id event_type  event_index event  \\\n0  97ff3f06-6593-4c7f-a5b6-040377d04ece        raw            0     A   \n1  97852c27-4b28-4ea0-8aa9-42ab8faf47d0        raw            1     B   \n2  c197d2ea-617f-4b13-b637-c1b9b70c6f57        raw            2     B   \n\n            timestamp user_id session_id  \n0 2023-01-01 00:00:00  user_1  session_1  \n1 2023-01-01 00:00:01  user_1  session_1  \n2 2023-01-01 00:00:02  user_2  session_2  ",
      "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>event_id</th>\n      <th>event_type</th>\n      <th>event_index</th>\n      <th>event</th>\n      <th>timestamp</th>\n      <th>user_id</th>\n      <th>session_id</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>97ff3f06-6593-4c7f-a5b6-040377d04ece</td>\n      <td>raw</td>\n      <td>0</td>\n      <td>A</td>\n      <td>2023-01-01 00:00:00</td>\n      <td>user_1</td>\n      <td>session_1</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>97852c27-4b28-4ea0-8aa9-42ab8faf47d0</td>\n      <td>raw</td>\n      <td>1</td>\n      <td>B</td>\n      <td>2023-01-01 00:00:01</td>\n      <td>user_1</td>\n      <td>session_1</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>c197d2ea-617f-4b13-b637-c1b9b70c6f57</td>\n      <td>raw</td>\n      <td>2</td>\n      <td>B</td>\n      <td>2023-01-01 00:00:02</td>\n      <td>user_2</td>\n      <td>session_2</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ]
  },
  {
   "cell_type": "markdown",
   "source": [
    "### Eventstream field names"
   ],
   "metadata": {
    "id": "wEdtu-T5vUQO"
   }
  },
  {
   "cell_type": "code",
   "source": [
    "from retentioneering.eventstream import EventstreamSchema\n",
    "\n",
    "new_eventstream_schema = EventstreamSchema(\n",
    "    user_id='client_id',\n",
    "    event_name='action',\n",
    "    event_timestamp='datetime'\n",
    ")\n",
    "\n",
    "stream1_new_schema = Eventstream(df1, schema=new_eventstream_schema)\n",
    "stream1_new_schema.to_dataframe().head(3)"
   ],
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 240
    },
    "id": "hH6YUPxZvXj8",
    "executionInfo": {
     "status": "ok",
     "timestamp": 1682533622903,
     "user_tz": -180,
     "elapsed": 988,
     "user": {
      "displayName": "Anatoliy Zaykovskiy",
      "userId": "11710160701524337708"
     }
    },
    "outputId": "ad3eb187-36a7-476f-e34f-6c170d48ddea"
   },
   "execution_count": 7,
   "outputs": [
    {
     "data": {
      "text/plain": "                               event_id event_type  event_index action  \\\n0  c9940979-b144-4642-9c2b-39876ecc2311        raw            0      A   \n1  540daf68-b11c-4e2f-87e5-c2fefb880b23        raw            1      B   \n2  9fad0b1a-be9a-4402-b582-a3339535a2c6        raw            2      B   \n\n             datetime client_id  \n0 2023-01-01 00:00:00    user_1  \n1 2023-01-01 00:00:01    user_1  \n2 2023-01-01 00:00:02    user_2  ",
      "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>event_id</th>\n      <th>event_type</th>\n      <th>event_index</th>\n      <th>action</th>\n      <th>datetime</th>\n      <th>client_id</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>c9940979-b144-4642-9c2b-39876ecc2311</td>\n      <td>raw</td>\n      <td>0</td>\n      <td>A</td>\n      <td>2023-01-01 00:00:00</td>\n      <td>user_1</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>540daf68-b11c-4e2f-87e5-c2fefb880b23</td>\n      <td>raw</td>\n      <td>1</td>\n      <td>B</td>\n      <td>2023-01-01 00:00:01</td>\n      <td>user_1</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>9fad0b1a-be9a-4402-b582-a3339535a2c6</td>\n      <td>raw</td>\n      <td>2</td>\n      <td>B</td>\n      <td>2023-01-01 00:00:02</td>\n      <td>user_2</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ]
  },
  {
   "cell_type": "code",
   "source": [
    "stream1_new_schema.schema"
   ],
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "NuayqnFGyLuU",
    "executionInfo": {
     "status": "ok",
     "timestamp": 1682533623512,
     "user_tz": -180,
     "elapsed": 5,
     "user": {
      "displayName": "Anatoliy Zaykovskiy",
      "userId": "11710160701524337708"
     }
    },
    "outputId": "c84dde70-e1b2-4fd8-b46d-66fb914cca5f"
   },
   "execution_count": 8,
   "outputs": [
    {
     "data": {
      "text/plain": "EventstreamSchema(event_id='event_id', event_type='event_type', event_index='event_index', event_name='action', event_timestamp='datetime', user_id='client_id', custom_cols=[])"
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ]
  },
  {
   "cell_type": "markdown",
   "source": [
    "### User sampling"
   ],
   "metadata": {
    "id": "Lo-EDNjup0y3"
   }
  },
  {
   "cell_type": "code",
   "source": [
    "from retentioneering import datasets\n",
    "\n",
    "simple_shop_df = datasets.load_simple_shop(as_dataframe=True)\n",
    "sampled_stream = Eventstream(\n",
    "    simple_shop_df,\n",
    "    user_sample_size=0.1,\n",
    "    user_sample_seed=42\n",
    ")\n",
    "\n",
    "print('Original number of the events:', len(simple_shop_df))\n",
    "print('Sampled number of the events:', len(sampled_stream.to_dataframe()))\n",
    "\n",
    "unique_users_original = simple_shop_df['user_id'].nunique()\n",
    "unique_users_sampled = sampled_stream.to_dataframe()['user_id'].nunique()\n",
    "\n",
    "print('Original unique users number: ', unique_users_original)\n",
    "print('Sampled unique users number: ', unique_users_sampled)"
   ],
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "xvC0Y23cqYwB",
    "executionInfo": {
     "status": "ok",
     "timestamp": 1682533628796,
     "user_tz": -180,
     "elapsed": 1177,
     "user": {
      "displayName": "Anatoliy Zaykovskiy",
      "userId": "11710160701524337708"
     }
    },
    "outputId": "406b908f-e00c-4f15-ac96-15dfb2d7570a"
   },
   "execution_count": 9,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Original number of the events: 32283\n",
      "Sampled number of the events: 3298\n",
      "Original unique users number:  3751\n",
      "Sampled unique users number:  375\n"
     ]
    }
   ]
  },
  {
   "cell_type": "markdown",
   "source": [
    "<a name=\"displaying_eventstream\"></a>\n",
    "### Displaying eventstream"
   ],
   "metadata": {
    "id": "i9CxVJyezztC"
   }
  },
  {
   "cell_type": "code",
   "source": [
    "stream3.to_dataframe()"
   ],
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 337
    },
    "id": "p4KUwnZh0BvG",
    "executionInfo": {
     "status": "ok",
     "timestamp": 1682533633144,
     "user_tz": -180,
     "elapsed": 13,
     "user": {
      "displayName": "Anatoliy Zaykovskiy",
      "userId": "11710160701524337708"
     }
    },
    "outputId": "8436d30d-b016-4417-f8bd-ad8943dff4d7"
   },
   "execution_count": 10,
   "outputs": [
    {
     "data": {
      "text/plain": "                               event_id event_type  event_index event  \\\n0  97ff3f06-6593-4c7f-a5b6-040377d04ece        raw            0     A   \n1  97852c27-4b28-4ea0-8aa9-42ab8faf47d0        raw            1     B   \n2  c197d2ea-617f-4b13-b637-c1b9b70c6f57        raw            2     B   \n3  cbb49db3-b102-4e73-a974-11a142c72e98        raw            3     A   \n4  31e35db3-fb38-4b9d-88d0-ece785e6dd31        raw            4     A   \n\n            timestamp user_id session_id  \n0 2023-01-01 00:00:00  user_1  session_1  \n1 2023-01-01 00:00:01  user_1  session_1  \n2 2023-01-01 00:00:02  user_2  session_2  \n3 2023-01-01 00:00:03  user_2  session_3  \n4 2023-01-01 00:00:04  user_2  session_3  ",
      "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>event_id</th>\n      <th>event_type</th>\n      <th>event_index</th>\n      <th>event</th>\n      <th>timestamp</th>\n      <th>user_id</th>\n      <th>session_id</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>97ff3f06-6593-4c7f-a5b6-040377d04ece</td>\n      <td>raw</td>\n      <td>0</td>\n      <td>A</td>\n      <td>2023-01-01 00:00:00</td>\n      <td>user_1</td>\n      <td>session_1</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>97852c27-4b28-4ea0-8aa9-42ab8faf47d0</td>\n      <td>raw</td>\n      <td>1</td>\n      <td>B</td>\n      <td>2023-01-01 00:00:01</td>\n      <td>user_1</td>\n      <td>session_1</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>c197d2ea-617f-4b13-b637-c1b9b70c6f57</td>\n      <td>raw</td>\n      <td>2</td>\n      <td>B</td>\n      <td>2023-01-01 00:00:02</td>\n      <td>user_2</td>\n      <td>session_2</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>cbb49db3-b102-4e73-a974-11a142c72e98</td>\n      <td>raw</td>\n      <td>3</td>\n      <td>A</td>\n      <td>2023-01-01 00:00:03</td>\n      <td>user_2</td>\n      <td>session_3</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>31e35db3-fb38-4b9d-88d0-ece785e6dd31</td>\n      <td>raw</td>\n      <td>4</td>\n      <td>A</td>\n      <td>2023-01-01 00:00:04</td>\n      <td>user_2</td>\n      <td>session_3</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ]
  },
  {
   "cell_type": "markdown",
   "source": [
    "## Eventstream index and reindex"
   ],
   "metadata": {
    "id": "0En63MqeFDWP"
   }
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "outputs": [
    {
     "data": {
      "text/plain": "                               event_id event_type  event_index event  \\\n0  a1176281-859e-4a10-9cdb-2753093cd4b7        raw            0     A   \n1  3249e407-9653-4381-b5d6-771df04f98c5        raw            1     B   \n2  611fe1f0-906a-4165-ab38-d5f6189accfb        raw            2     B   \n3  3c28b7c9-15c2-47b5-bc40-efcc0d802b1c        raw            3     A   \n4  801f0ba6-a8ec-4963-a867-5c79440d2564        raw            4     A   \n\n            timestamp user_id  \n0 2023-01-01 00:00:00  user_1  \n1 2023-01-01 00:00:00  user_1  \n2 2023-01-01 00:00:03  user_2  \n3 2023-01-01 00:00:03  user_2  \n4 2023-01-01 00:00:04  user_2  ",
      "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>event_id</th>\n      <th>event_type</th>\n      <th>event_index</th>\n      <th>event</th>\n      <th>timestamp</th>\n      <th>user_id</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>a1176281-859e-4a10-9cdb-2753093cd4b7</td>\n      <td>raw</td>\n      <td>0</td>\n      <td>A</td>\n      <td>2023-01-01 00:00:00</td>\n      <td>user_1</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>3249e407-9653-4381-b5d6-771df04f98c5</td>\n      <td>raw</td>\n      <td>1</td>\n      <td>B</td>\n      <td>2023-01-01 00:00:00</td>\n      <td>user_1</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>611fe1f0-906a-4165-ab38-d5f6189accfb</td>\n      <td>raw</td>\n      <td>2</td>\n      <td>B</td>\n      <td>2023-01-01 00:00:03</td>\n      <td>user_2</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>3c28b7c9-15c2-47b5-bc40-efcc0d802b1c</td>\n      <td>raw</td>\n      <td>3</td>\n      <td>A</td>\n      <td>2023-01-01 00:00:03</td>\n      <td>user_2</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>801f0ba6-a8ec-4963-a867-5c79440d2564</td>\n      <td>raw</td>\n      <td>4</td>\n      <td>A</td>\n      <td>2023-01-01 00:00:04</td>\n      <td>user_2</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df4 = pd.DataFrame(\n",
    "    [\n",
    "        ['user_1', 'A', '2023-01-01 00:00:00'],\n",
    "        ['user_1', 'B', '2023-01-01 00:00:00'],\n",
    "        ['user_2', 'B', '2023-01-01 00:00:03'],\n",
    "        ['user_2', 'A', '2023-01-01 00:00:03'],\n",
    "        ['user_2', 'A', '2023-01-01 00:00:04']\n",
    "    ],\n",
    "    columns=['user_id', 'event', 'timestamp']\n",
    ")\n",
    "\n",
    "stream4 = Eventstream(df4)\n",
    "stream4.to_dataframe()"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "outputs": [
    {
     "data": {
      "text/plain": "                               event_id event_type  event_index event  \\\n0  c227811a-ad29-4fe9-adf2-2e1a97de1b22        raw            0     B   \n1  898de74d-6c21-4d4c-a1db-10f8116283e8        raw            1     A   \n2  ec2ea8bc-6420-4875-95ae-19c81eb384ba        raw            2     B   \n3  99a4fab9-c2b0-4de5-b6d9-c0fa4981be18        raw            3     A   \n4  398b378e-c9e5-4c5e-b18e-e51c05bfc5f3        raw            4     A   \n\n            timestamp user_id  \n0 2023-01-01 00:00:00  user_1  \n1 2023-01-01 00:00:00  user_1  \n2 2023-01-01 00:00:03  user_2  \n3 2023-01-01 00:00:03  user_2  \n4 2023-01-01 00:00:04  user_2  ",
      "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>event_id</th>\n      <th>event_type</th>\n      <th>event_index</th>\n      <th>event</th>\n      <th>timestamp</th>\n      <th>user_id</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>c227811a-ad29-4fe9-adf2-2e1a97de1b22</td>\n      <td>raw</td>\n      <td>0</td>\n      <td>B</td>\n      <td>2023-01-01 00:00:00</td>\n      <td>user_1</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>898de74d-6c21-4d4c-a1db-10f8116283e8</td>\n      <td>raw</td>\n      <td>1</td>\n      <td>A</td>\n      <td>2023-01-01 00:00:00</td>\n      <td>user_1</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>ec2ea8bc-6420-4875-95ae-19c81eb384ba</td>\n      <td>raw</td>\n      <td>2</td>\n      <td>B</td>\n      <td>2023-01-01 00:00:03</td>\n      <td>user_2</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>99a4fab9-c2b0-4de5-b6d9-c0fa4981be18</td>\n      <td>raw</td>\n      <td>3</td>\n      <td>A</td>\n      <td>2023-01-01 00:00:03</td>\n      <td>user_2</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>398b378e-c9e5-4c5e-b18e-e51c05bfc5f3</td>\n      <td>raw</td>\n      <td>4</td>\n      <td>A</td>\n      <td>2023-01-01 00:00:04</td>\n      <td>user_2</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Eventstream(df4, events_order=[\"B\", \"A\"]).to_dataframe()"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "source": [
    "IndexOrder = [\n",
    "    \"profile\",\n",
    "    \"path_start\",\n",
    "    \"new_user\",\n",
    "    \"existing_user\",\n",
    "    \"cropped_left\",\n",
    "    \"session_start\",\n",
    "    \"session_start_cropped\",\n",
    "    \"group_alias\",\n",
    "    \"raw\",\n",
    "    \"raw_sleep\",\n",
    "    None,\n",
    "    \"synthetic\",\n",
    "    \"synthetic_sleep\",\n",
    "    \"positive_target\",\n",
    "    \"negative_target\",\n",
    "    \"session_end_cropped\",\n",
    "    \"session_end\",\n",
    "    \"session_sleep\",\n",
    "    \"cropped_right\",\n",
    "    \"absent_user\",\n",
    "    \"lost_user\",\n",
    "    \"path_end\"\n",
    "]"
   ],
   "metadata": {
    "id": "Qye9ZuiJFgVZ"
   },
   "execution_count": 13,
   "outputs": []
  },
  {
   "cell_type": "code",
   "source": [
    "add_events_stream = stream4.add_positive_events(targets=['B'])\n",
    "add_events_stream.to_dataframe()"
   ],
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 489
    },
    "id": "uHPBO_fsIKSC",
    "executionInfo": {
     "status": "ok",
     "timestamp": 1682534665066,
     "user_tz": -180,
     "elapsed": 6,
     "user": {
      "displayName": "Anatoliy Zaykovskiy",
      "userId": "11710160701524337708"
     }
    },
    "outputId": "1ded345e-fd0c-4b6c-e649-99b38293521f"
   },
   "execution_count": 14,
   "outputs": [
    {
     "data": {
      "text/plain": "                               event_id       event_type  event_index  \\\n0  a1176281-859e-4a10-9cdb-2753093cd4b7              raw            0   \n1  3249e407-9653-4381-b5d6-771df04f98c5              raw            1   \n2  d5e048b4-4f86-4739-86a4-18909aa55818  positive_target            1   \n3  611fe1f0-906a-4165-ab38-d5f6189accfb              raw            2   \n4  27d9398b-439a-4483-98be-45f09f5f1eaf  positive_target            2   \n5  3c28b7c9-15c2-47b5-bc40-efcc0d802b1c              raw            3   \n6  801f0ba6-a8ec-4963-a867-5c79440d2564              raw            4   \n\n               event           timestamp user_id  \n0                  A 2023-01-01 00:00:00  user_1  \n1                  B 2023-01-01 00:00:00  user_1  \n2  positive_target_B 2023-01-01 00:00:00  user_1  \n3                  B 2023-01-01 00:00:03  user_2  \n4  positive_target_B 2023-01-01 00:00:03  user_2  \n5                  A 2023-01-01 00:00:03  user_2  \n6                  A 2023-01-01 00:00:04  user_2  ",
      "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>event_id</th>\n      <th>event_type</th>\n      <th>event_index</th>\n      <th>event</th>\n      <th>timestamp</th>\n      <th>user_id</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>a1176281-859e-4a10-9cdb-2753093cd4b7</td>\n      <td>raw</td>\n      <td>0</td>\n      <td>A</td>\n      <td>2023-01-01 00:00:00</td>\n      <td>user_1</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>3249e407-9653-4381-b5d6-771df04f98c5</td>\n      <td>raw</td>\n      <td>1</td>\n      <td>B</td>\n      <td>2023-01-01 00:00:00</td>\n      <td>user_1</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>d5e048b4-4f86-4739-86a4-18909aa55818</td>\n      <td>positive_target</td>\n      <td>1</td>\n      <td>positive_target_B</td>\n      <td>2023-01-01 00:00:00</td>\n      <td>user_1</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>611fe1f0-906a-4165-ab38-d5f6189accfb</td>\n      <td>raw</td>\n      <td>2</td>\n      <td>B</td>\n      <td>2023-01-01 00:00:03</td>\n      <td>user_2</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>27d9398b-439a-4483-98be-45f09f5f1eaf</td>\n      <td>positive_target</td>\n      <td>2</td>\n      <td>positive_target_B</td>\n      <td>2023-01-01 00:00:03</td>\n      <td>user_2</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>3c28b7c9-15c2-47b5-bc40-efcc0d802b1c</td>\n      <td>raw</td>\n      <td>3</td>\n      <td>A</td>\n      <td>2023-01-01 00:00:03</td>\n      <td>user_2</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>801f0ba6-a8ec-4963-a867-5c79440d2564</td>\n      <td>raw</td>\n      <td>4</td>\n      <td>A</td>\n      <td>2023-01-01 00:00:04</td>\n      <td>user_2</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ]
  },
  {
   "cell_type": "code",
   "source": [
    "custom_sorting = [\n",
    "    'profile',\n",
    "    'path_start',\n",
    "    'new_user',\n",
    "    'existing_user',\n",
    "    'cropped_left',\n",
    "    'session_start',\n",
    "    'session_start_cropped',\n",
    "    'group_alias',\n",
    "    'positive_target',\n",
    "    'raw',\n",
    "    'raw_sleep',\n",
    "    None,\n",
    "    'synthetic',\n",
    "    'synthetic_sleep',\n",
    "    'negative_target',\n",
    "    'session_end_cropped',\n",
    "    'session_end',\n",
    "    'session_sleep',\n",
    "    'cropped_right',\n",
    "    'absent_user',\n",
    "    'lost_user',\n",
    "    'path_end'\n",
    "]\n",
    "\n",
    "add_events_stream.index_order = custom_sorting\n",
    "add_events_stream.index_events()\n",
    "add_events_stream.to_dataframe()"
   ],
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 434
    },
    "id": "eLBIvTv5Icy6",
    "executionInfo": {
     "status": "ok",
     "timestamp": 1682534703220,
     "user_tz": -180,
     "elapsed": 6,
     "user": {
      "displayName": "Anatoliy Zaykovskiy",
      "userId": "11710160701524337708"
     }
    },
    "outputId": "45d16359-284f-4471-90c8-61cd9471ad47"
   },
   "execution_count": 15,
   "outputs": [
    {
     "data": {
      "text/plain": "                               event_id       event_type  event_index  \\\n0  a1176281-859e-4a10-9cdb-2753093cd4b7              raw            0   \n1  d5e048b4-4f86-4739-86a4-18909aa55818  positive_target            1   \n2  3249e407-9653-4381-b5d6-771df04f98c5              raw            1   \n3  27d9398b-439a-4483-98be-45f09f5f1eaf  positive_target            2   \n4  611fe1f0-906a-4165-ab38-d5f6189accfb              raw            2   \n5  3c28b7c9-15c2-47b5-bc40-efcc0d802b1c              raw            3   \n6  801f0ba6-a8ec-4963-a867-5c79440d2564              raw            4   \n\n               event           timestamp user_id  \n0                  A 2023-01-01 00:00:00  user_1  \n1  positive_target_B 2023-01-01 00:00:00  user_1  \n2                  B 2023-01-01 00:00:00  user_1  \n3  positive_target_B 2023-01-01 00:00:03  user_2  \n4                  B 2023-01-01 00:00:03  user_2  \n5                  A 2023-01-01 00:00:03  user_2  \n6                  A 2023-01-01 00:00:04  user_2  ",
      "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>event_id</th>\n      <th>event_type</th>\n      <th>event_index</th>\n      <th>event</th>\n      <th>timestamp</th>\n      <th>user_id</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>a1176281-859e-4a10-9cdb-2753093cd4b7</td>\n      <td>raw</td>\n      <td>0</td>\n      <td>A</td>\n      <td>2023-01-01 00:00:00</td>\n      <td>user_1</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>d5e048b4-4f86-4739-86a4-18909aa55818</td>\n      <td>positive_target</td>\n      <td>1</td>\n      <td>positive_target_B</td>\n      <td>2023-01-01 00:00:00</td>\n      <td>user_1</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>3249e407-9653-4381-b5d6-771df04f98c5</td>\n      <td>raw</td>\n      <td>1</td>\n      <td>B</td>\n      <td>2023-01-01 00:00:00</td>\n      <td>user_1</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>27d9398b-439a-4483-98be-45f09f5f1eaf</td>\n      <td>positive_target</td>\n      <td>2</td>\n      <td>positive_target_B</td>\n      <td>2023-01-01 00:00:03</td>\n      <td>user_2</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>611fe1f0-906a-4165-ab38-d5f6189accfb</td>\n      <td>raw</td>\n      <td>2</td>\n      <td>B</td>\n      <td>2023-01-01 00:00:03</td>\n      <td>user_2</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>3c28b7c9-15c2-47b5-bc40-efcc0d802b1c</td>\n      <td>raw</td>\n      <td>3</td>\n      <td>A</td>\n      <td>2023-01-01 00:00:03</td>\n      <td>user_2</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>801f0ba6-a8ec-4963-a867-5c79440d2564</td>\n      <td>raw</td>\n      <td>4</td>\n      <td>A</td>\n      <td>2023-01-01 00:00:04</td>\n      <td>user_2</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ]
  },
  {
   "cell_type": "markdown",
   "source": [
    "## Descriptive methods"
   ],
   "metadata": {
    "id": "bGmRhXMhSCS8"
   }
  },
  {
   "cell_type": "code",
   "source": [
    "from retentioneering import datasets\n",
    "\n",
    "stream_with_sessions = datasets\\\n",
    "    .load_simple_shop()\\\n",
    "    .split_sessions(timeout=(30, 'm'))\n",
    "\n",
    "stream_with_sessions.to_dataframe().head()"
   ],
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 337
    },
    "id": "d1RZ51Hd1C_w",
    "executionInfo": {
     "status": "ok",
     "timestamp": 1682534832955,
     "user_tz": -180,
     "elapsed": 1442,
     "user": {
      "displayName": "Anatoliy Zaykovskiy",
      "userId": "11710160701524337708"
     }
    },
    "outputId": "dee65fdf-c5ca-48f3-e1e2-425d54cd18be"
   },
   "execution_count": 16,
   "outputs": [
    {
     "data": {
      "text/plain": "                               event_id     event_type  event_index  \\\n0  5be7ea13-10cf-4425-8bd5-4946239c6875  session_start            0   \n1  44a8a07b-b045-49e1-bbc8-ffe02aea0ed8            raw            0   \n2  39f580c0-ac9f-4b18-9192-fc16ca5dc52c            raw            1   \n3  06f1f986-f3ce-4972-b0fd-42962e4deaec            raw            2   \n4  df7ed498-ff1d-4053-b989-fec179f3eeaf            raw            3   \n\n           event                  timestamp    user_id   session_id  \n0  session_start 2019-11-01 17:59:13.273932  219483890  219483890_1  \n1        catalog 2019-11-01 17:59:13.273932  219483890  219483890_1  \n2       product1 2019-11-01 17:59:28.459271  219483890  219483890_1  \n3           cart 2019-11-01 17:59:29.502214  219483890  219483890_1  \n4        catalog 2019-11-01 17:59:32.557029  219483890  219483890_1  ",
      "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>event_id</th>\n      <th>event_type</th>\n      <th>event_index</th>\n      <th>event</th>\n      <th>timestamp</th>\n      <th>user_id</th>\n      <th>session_id</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>5be7ea13-10cf-4425-8bd5-4946239c6875</td>\n      <td>session_start</td>\n      <td>0</td>\n      <td>session_start</td>\n      <td>2019-11-01 17:59:13.273932</td>\n      <td>219483890</td>\n      <td>219483890_1</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>44a8a07b-b045-49e1-bbc8-ffe02aea0ed8</td>\n      <td>raw</td>\n      <td>0</td>\n      <td>catalog</td>\n      <td>2019-11-01 17:59:13.273932</td>\n      <td>219483890</td>\n      <td>219483890_1</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>39f580c0-ac9f-4b18-9192-fc16ca5dc52c</td>\n      <td>raw</td>\n      <td>1</td>\n      <td>product1</td>\n      <td>2019-11-01 17:59:28.459271</td>\n      <td>219483890</td>\n      <td>219483890_1</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>06f1f986-f3ce-4972-b0fd-42962e4deaec</td>\n      <td>raw</td>\n      <td>2</td>\n      <td>cart</td>\n      <td>2019-11-01 17:59:29.502214</td>\n      <td>219483890</td>\n      <td>219483890_1</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>df7ed498-ff1d-4053-b989-fec179f3eeaf</td>\n      <td>raw</td>\n      <td>3</td>\n      <td>catalog</td>\n      <td>2019-11-01 17:59:32.557029</td>\n      <td>219483890</td>\n      <td>219483890_1</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ]
  },
  {
   "cell_type": "markdown",
   "source": [
    "### General statistics"
   ],
   "metadata": {
    "id": "w9SLW02d1Nk6"
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "#### Describe"
   ],
   "metadata": {
    "id": "NHe2F9OXJjaE"
   }
  },
  {
   "cell_type": "code",
   "source": [
    "stream_with_sessions.describe()"
   ],
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 896
    },
    "id": "1KB_Nfs34LEJ",
    "executionInfo": {
     "status": "ok",
     "timestamp": 1682534895622,
     "user_tz": -180,
     "elapsed": 8,
     "user": {
      "displayName": "Anatoliy Zaykovskiy",
      "userId": "11710160701524337708"
     }
    },
    "outputId": "baf72aae-20aa-4371-c5ed-3db16de51168"
   },
   "execution_count": 17,
   "outputs": [
    {
     "data": {
      "text/plain": "                                                       value\ncategory             metric                                 \noverall              unique_users                       3751\n                     unique_events                        14\n                     unique_sessions                    6454\n                     eventstream_start   2019-11-01 17:59:13\n                     eventstream_end     2020-04-29 12:48:07\n                     eventstream_length    179 days 18:48:53\npath_length_time     mean                    9 days 11:15:18\n                     std                    23 days 02:52:25\n                     median                  0 days 00:01:21\n                     min                     0 days 00:00:00\n                     max                   149 days 04:51:05\npath_length_steps    mean                              12.05\n                     std                               11.43\n                     median                              9.0\n                     min                                   3\n                     max                                 122\nsession_length_time  mean                    0 days 00:00:52\n                     std                     0 days 00:01:08\n                     median                  0 days 00:00:30\n                     min                     0 days 00:00:00\n                     max                     0 days 00:23:44\nsession_length_steps mean                                7.0\n                     std                                4.18\n                     median                              6.0\n                     min                                   3\n                     max                                  55",
      "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></th>\n      <th>value</th>\n    </tr>\n    <tr>\n      <th>category</th>\n      <th>metric</th>\n      <th></th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th rowspan=\"6\" valign=\"top\">overall</th>\n      <th>unique_users</th>\n      <td>3751</td>\n    </tr>\n    <tr>\n      <th>unique_events</th>\n      <td>14</td>\n    </tr>\n    <tr>\n      <th>unique_sessions</th>\n      <td>6454</td>\n    </tr>\n    <tr>\n      <th>eventstream_start</th>\n      <td>2019-11-01 17:59:13</td>\n    </tr>\n    <tr>\n      <th>eventstream_end</th>\n      <td>2020-04-29 12:48:07</td>\n    </tr>\n    <tr>\n      <th>eventstream_length</th>\n      <td>179 days 18:48:53</td>\n    </tr>\n    <tr>\n      <th rowspan=\"5\" valign=\"top\">path_length_time</th>\n      <th>mean</th>\n      <td>9 days 11:15:18</td>\n    </tr>\n    <tr>\n      <th>std</th>\n      <td>23 days 02:52:25</td>\n    </tr>\n    <tr>\n      <th>median</th>\n      <td>0 days 00:01:21</td>\n    </tr>\n    <tr>\n      <th>min</th>\n      <td>0 days 00:00:00</td>\n    </tr>\n    <tr>\n      <th>max</th>\n      <td>149 days 04:51:05</td>\n    </tr>\n    <tr>\n      <th rowspan=\"5\" valign=\"top\">path_length_steps</th>\n      <th>mean</th>\n      <td>12.05</td>\n    </tr>\n    <tr>\n      <th>std</th>\n      <td>11.43</td>\n    </tr>\n    <tr>\n      <th>median</th>\n      <td>9.0</td>\n    </tr>\n    <tr>\n      <th>min</th>\n      <td>3</td>\n    </tr>\n    <tr>\n      <th>max</th>\n      <td>122</td>\n    </tr>\n    <tr>\n      <th rowspan=\"5\" valign=\"top\">session_length_time</th>\n      <th>mean</th>\n      <td>0 days 00:00:52</td>\n    </tr>\n    <tr>\n      <th>std</th>\n      <td>0 days 00:01:08</td>\n    </tr>\n    <tr>\n      <th>median</th>\n      <td>0 days 00:00:30</td>\n    </tr>\n    <tr>\n      <th>min</th>\n      <td>0 days 00:00:00</td>\n    </tr>\n    <tr>\n      <th>max</th>\n      <td>0 days 00:23:44</td>\n    </tr>\n    <tr>\n      <th rowspan=\"5\" valign=\"top\">session_length_steps</th>\n      <th>mean</th>\n      <td>7.0</td>\n    </tr>\n    <tr>\n      <th>std</th>\n      <td>4.18</td>\n    </tr>\n    <tr>\n      <th>median</th>\n      <td>6.0</td>\n    </tr>\n    <tr>\n      <th>min</th>\n      <td>3</td>\n    </tr>\n    <tr>\n      <th>max</th>\n      <td>55</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ]
  },
  {
   "cell_type": "markdown",
   "source": [
    "#### Describe events\n"
   ],
   "metadata": {
    "id": "7q6kjYjdMIgz"
   }
  },
  {
   "cell_type": "code",
   "source": [
    "stream = datasets.load_simple_shop()\n",
    "stream.describe_events()"
   ],
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 952
    },
    "id": "9SkeBrB1Nr6m",
    "executionInfo": {
     "status": "ok",
     "timestamp": 1682535411485,
     "user_tz": -180,
     "elapsed": 650,
     "user": {
      "displayName": "Anatoliy Zaykovskiy",
      "userId": "11710160701524337708"
     }
    },
    "outputId": "6aafafa7-30c3-4d22-98df-da2237c87650"
   },
   "execution_count": 18,
   "outputs": [
    {
     "data": {
      "text/plain": "                      basic_statistics               \\\n                 number_of_occurrences unique_users   \nevent                                                 \ncart                              2842         1924   \ncatalog                          14518         3611   \ndelivery_choice                   1686         1356   \ndelivery_courier                   834          748   \ndelivery_pickup                    506          469   \nmain                              5635         2385   \npayment_card                       565          521   \npayment_cash                       197          190   \npayment_choice                    1107          958   \npayment_done                       706          653   \nproduct1                          1515         1122   \nproduct2                          2172         1430   \n\n                                                                   \\\n                 number_of_occurrences_shared unique_users_shared   \nevent                                                               \ncart                                     0.09                0.51   \ncatalog                                  0.45                0.96   \ndelivery_choice                          0.05                0.36   \ndelivery_courier                         0.03                0.20   \ndelivery_pickup                          0.02                0.13   \nmain                                     0.17                0.64   \npayment_card                             0.02                0.14   \npayment_cash                             0.01                0.05   \npayment_choice                           0.03                0.26   \npayment_done                             0.02                0.17   \nproduct1                                 0.05                0.30   \nproduct2                                 0.07                0.38   \n\n                 time_to_FO_user_wise                                   \\\n                                 mean              std          median   \nevent                                                                    \ncart                  3 days 08:59:14 11 days 19:28:46 0 days 00:00:56   \ncatalog               0 days 05:44:21  3 days 03:22:32 0 days 00:00:00   \ndelivery_choice       5 days 09:18:08 15 days 03:19:15 0 days 00:01:12   \ndelivery_courier      6 days 18:14:55 16 days 17:51:39 0 days 00:01:28   \ndelivery_pickup       7 days 21:12:17 18 days 22:51:54 0 days 00:01:34   \nmain                  3 days 20:15:36  9 days 02:58:23 0 days 00:00:07   \npayment_card          6 days 21:42:26 17 days 18:52:33 0 days 00:01:40   \npayment_cash         13 days 23:17:25 24 days 00:00:02 0 days 00:02:18   \npayment_choice        6 days 12:49:38 17 days 02:54:51 0 days 00:01:24   \npayment_done          7 days 01:37:54 17 days 09:10:00 0 days 00:01:34   \nproduct1              5 days 23:49:43 16 days 04:36:13 0 days 00:00:50   \nproduct2              4 days 06:13:24 13 days 03:26:17 0 days 00:00:34   \n\n                                                   steps_to_FO_user_wise  \\\n                             min               max                  mean   \nevent                                                                      \ncart             0 days 00:00:01 118 days 16:11:36                  4.51   \ncatalog          0 days 00:00:00 100 days 08:19:51                  0.30   \ndelivery_choice  0 days 00:00:03 118 days 16:11:37                  6.78   \ndelivery_courier 0 days 00:00:06 118 days 16:11:38                  8.96   \ndelivery_pickup  0 days 00:00:06 114 days 01:24:06                  9.51   \nmain             0 days 00:00:00  97 days 21:24:23                  2.00   \npayment_card     0 days 00:00:08 138 days 04:51:25                 11.14   \npayment_cash     0 days 00:00:10 118 days 16:11:39                 14.15   \npayment_choice   0 days 00:00:06 118 days 16:11:39                  9.42   \npayment_done     0 days 00:00:08 115 days 09:18:59                 12.21   \nproduct1         0 days 00:00:00 118 days 19:38:40                  5.46   \nproduct2         0 days 00:00:00 126 days 23:36:45                  4.32   \n\n                                        \n                    std median min max  \nevent                                   \ncart               4.09    3.0   1  41  \ncatalog            0.57    0.0   0   7  \ndelivery_choice    5.56    5.0   2  49  \ndelivery_courier   6.84    7.0   3  45  \ndelivery_pickup    8.06    7.0   3  71  \nmain               2.94    1.0   0  20  \npayment_card       7.34    9.0   5  65  \npayment_cash      11.10    9.5   5  73  \npayment_choice     6.37    7.0   4  52  \npayment_done       8.29   10.0   5  84  \nproduct1           6.04    3.0   1  61  \nproduct2           4.51    3.0   1  36  ",
      "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 tr th {\n        text-align: left;\n    }\n\n    .dataframe thead tr:last-of-type th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr>\n      <th></th>\n      <th colspan=\"4\" halign=\"left\">basic_statistics</th>\n      <th colspan=\"5\" halign=\"left\">time_to_FO_user_wise</th>\n      <th colspan=\"5\" halign=\"left\">steps_to_FO_user_wise</th>\n    </tr>\n    <tr>\n      <th></th>\n      <th>number_of_occurrences</th>\n      <th>unique_users</th>\n      <th>number_of_occurrences_shared</th>\n      <th>unique_users_shared</th>\n      <th>mean</th>\n      <th>std</th>\n      <th>median</th>\n      <th>min</th>\n      <th>max</th>\n      <th>mean</th>\n      <th>std</th>\n      <th>median</th>\n      <th>min</th>\n      <th>max</th>\n    </tr>\n    <tr>\n      <th>event</th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>cart</th>\n      <td>2842</td>\n      <td>1924</td>\n      <td>0.09</td>\n      <td>0.51</td>\n      <td>3 days 08:59:14</td>\n      <td>11 days 19:28:46</td>\n      <td>0 days 00:00:56</td>\n      <td>0 days 00:00:01</td>\n      <td>118 days 16:11:36</td>\n      <td>4.51</td>\n      <td>4.09</td>\n      <td>3.0</td>\n      <td>1</td>\n      <td>41</td>\n    </tr>\n    <tr>\n      <th>catalog</th>\n      <td>14518</td>\n      <td>3611</td>\n      <td>0.45</td>\n      <td>0.96</td>\n      <td>0 days 05:44:21</td>\n      <td>3 days 03:22:32</td>\n      <td>0 days 00:00:00</td>\n      <td>0 days 00:00:00</td>\n      <td>100 days 08:19:51</td>\n      <td>0.30</td>\n      <td>0.57</td>\n      <td>0.0</td>\n      <td>0</td>\n      <td>7</td>\n    </tr>\n    <tr>\n      <th>delivery_choice</th>\n      <td>1686</td>\n      <td>1356</td>\n      <td>0.05</td>\n      <td>0.36</td>\n      <td>5 days 09:18:08</td>\n      <td>15 days 03:19:15</td>\n      <td>0 days 00:01:12</td>\n      <td>0 days 00:00:03</td>\n      <td>118 days 16:11:37</td>\n      <td>6.78</td>\n      <td>5.56</td>\n      <td>5.0</td>\n      <td>2</td>\n      <td>49</td>\n    </tr>\n    <tr>\n      <th>delivery_courier</th>\n      <td>834</td>\n      <td>748</td>\n      <td>0.03</td>\n      <td>0.20</td>\n      <td>6 days 18:14:55</td>\n      <td>16 days 17:51:39</td>\n      <td>0 days 00:01:28</td>\n      <td>0 days 00:00:06</td>\n      <td>118 days 16:11:38</td>\n      <td>8.96</td>\n      <td>6.84</td>\n      <td>7.0</td>\n      <td>3</td>\n      <td>45</td>\n    </tr>\n    <tr>\n      <th>delivery_pickup</th>\n      <td>506</td>\n      <td>469</td>\n      <td>0.02</td>\n      <td>0.13</td>\n      <td>7 days 21:12:17</td>\n      <td>18 days 22:51:54</td>\n      <td>0 days 00:01:34</td>\n      <td>0 days 00:00:06</td>\n      <td>114 days 01:24:06</td>\n      <td>9.51</td>\n      <td>8.06</td>\n      <td>7.0</td>\n      <td>3</td>\n      <td>71</td>\n    </tr>\n    <tr>\n      <th>main</th>\n      <td>5635</td>\n      <td>2385</td>\n      <td>0.17</td>\n      <td>0.64</td>\n      <td>3 days 20:15:36</td>\n      <td>9 days 02:58:23</td>\n      <td>0 days 00:00:07</td>\n      <td>0 days 00:00:00</td>\n      <td>97 days 21:24:23</td>\n      <td>2.00</td>\n      <td>2.94</td>\n      <td>1.0</td>\n      <td>0</td>\n      <td>20</td>\n    </tr>\n    <tr>\n      <th>payment_card</th>\n      <td>565</td>\n      <td>521</td>\n      <td>0.02</td>\n      <td>0.14</td>\n      <td>6 days 21:42:26</td>\n      <td>17 days 18:52:33</td>\n      <td>0 days 00:01:40</td>\n      <td>0 days 00:00:08</td>\n      <td>138 days 04:51:25</td>\n      <td>11.14</td>\n      <td>7.34</td>\n      <td>9.0</td>\n      <td>5</td>\n      <td>65</td>\n    </tr>\n    <tr>\n      <th>payment_cash</th>\n      <td>197</td>\n      <td>190</td>\n      <td>0.01</td>\n      <td>0.05</td>\n      <td>13 days 23:17:25</td>\n      <td>24 days 00:00:02</td>\n      <td>0 days 00:02:18</td>\n      <td>0 days 00:00:10</td>\n      <td>118 days 16:11:39</td>\n      <td>14.15</td>\n      <td>11.10</td>\n      <td>9.5</td>\n      <td>5</td>\n      <td>73</td>\n    </tr>\n    <tr>\n      <th>payment_choice</th>\n      <td>1107</td>\n      <td>958</td>\n      <td>0.03</td>\n      <td>0.26</td>\n      <td>6 days 12:49:38</td>\n      <td>17 days 02:54:51</td>\n      <td>0 days 00:01:24</td>\n      <td>0 days 00:00:06</td>\n      <td>118 days 16:11:39</td>\n      <td>9.42</td>\n      <td>6.37</td>\n      <td>7.0</td>\n      <td>4</td>\n      <td>52</td>\n    </tr>\n    <tr>\n      <th>payment_done</th>\n      <td>706</td>\n      <td>653</td>\n      <td>0.02</td>\n      <td>0.17</td>\n      <td>7 days 01:37:54</td>\n      <td>17 days 09:10:00</td>\n      <td>0 days 00:01:34</td>\n      <td>0 days 00:00:08</td>\n      <td>115 days 09:18:59</td>\n      <td>12.21</td>\n      <td>8.29</td>\n      <td>10.0</td>\n      <td>5</td>\n      <td>84</td>\n    </tr>\n    <tr>\n      <th>product1</th>\n      <td>1515</td>\n      <td>1122</td>\n      <td>0.05</td>\n      <td>0.30</td>\n      <td>5 days 23:49:43</td>\n      <td>16 days 04:36:13</td>\n      <td>0 days 00:00:50</td>\n      <td>0 days 00:00:00</td>\n      <td>118 days 19:38:40</td>\n      <td>5.46</td>\n      <td>6.04</td>\n      <td>3.0</td>\n      <td>1</td>\n      <td>61</td>\n    </tr>\n    <tr>\n      <th>product2</th>\n      <td>2172</td>\n      <td>1430</td>\n      <td>0.07</td>\n      <td>0.38</td>\n      <td>4 days 06:13:24</td>\n      <td>13 days 03:26:17</td>\n      <td>0 days 00:00:34</td>\n      <td>0 days 00:00:00</td>\n      <td>126 days 23:36:45</td>\n      <td>4.32</td>\n      <td>4.51</td>\n      <td>3.0</td>\n      <td>1</td>\n      <td>36</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ]
  },
  {
   "cell_type": "code",
   "source": [
    "stream.describe_events()\n",
    "stream.describe_events(event_list=['payment_done', 'cart']).T"
   ],
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 488
    },
    "id": "Isw57wZlRKmc",
    "executionInfo": {
     "status": "ok",
     "timestamp": 1682535468578,
     "user_tz": -180,
     "elapsed": 8,
     "user": {
      "displayName": "Anatoliy Zaykovskiy",
      "userId": "11710160701524337708"
     }
    },
    "outputId": "14b6772c-f89d-4ea6-ecb0-3ff5f6084739"
   },
   "execution_count": 19,
   "outputs": [
    {
     "data": {
      "text/plain": "event                                                            cart  \\\nbasic_statistics      number_of_occurrences                      2842   \n                      unique_users                               1924   \n                      number_of_occurrences_shared               0.09   \n                      unique_users_shared                        0.51   \ntime_to_FO_user_wise  mean                            3 days 08:59:14   \n                      std                            11 days 19:28:46   \n                      median                          0 days 00:00:56   \n                      min                             0 days 00:00:01   \n                      max                           118 days 16:11:36   \nsteps_to_FO_user_wise mean                                       4.51   \n                      std                                        4.09   \n                      median                                      3.0   \n                      min                                           1   \n                      max                                          41   \n\nevent                                                    payment_done  \nbasic_statistics      number_of_occurrences                       706  \n                      unique_users                                653  \n                      number_of_occurrences_shared               0.02  \n                      unique_users_shared                        0.17  \ntime_to_FO_user_wise  mean                            7 days 01:37:54  \n                      std                            17 days 09:10:00  \n                      median                          0 days 00:01:34  \n                      min                             0 days 00:00:08  \n                      max                           115 days 09:18:59  \nsteps_to_FO_user_wise mean                                      12.21  \n                      std                                        8.29  \n                      median                                     10.0  \n                      min                                           5  \n                      max                                          84  ",
      "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>event</th>\n      <th>cart</th>\n      <th>payment_done</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th rowspan=\"4\" valign=\"top\">basic_statistics</th>\n      <th>number_of_occurrences</th>\n      <td>2842</td>\n      <td>706</td>\n    </tr>\n    <tr>\n      <th>unique_users</th>\n      <td>1924</td>\n      <td>653</td>\n    </tr>\n    <tr>\n      <th>number_of_occurrences_shared</th>\n      <td>0.09</td>\n      <td>0.02</td>\n    </tr>\n    <tr>\n      <th>unique_users_shared</th>\n      <td>0.51</td>\n      <td>0.17</td>\n    </tr>\n    <tr>\n      <th rowspan=\"5\" valign=\"top\">time_to_FO_user_wise</th>\n      <th>mean</th>\n      <td>3 days 08:59:14</td>\n      <td>7 days 01:37:54</td>\n    </tr>\n    <tr>\n      <th>std</th>\n      <td>11 days 19:28:46</td>\n      <td>17 days 09:10:00</td>\n    </tr>\n    <tr>\n      <th>median</th>\n      <td>0 days 00:00:56</td>\n      <td>0 days 00:01:34</td>\n    </tr>\n    <tr>\n      <th>min</th>\n      <td>0 days 00:00:01</td>\n      <td>0 days 00:00:08</td>\n    </tr>\n    <tr>\n      <th>max</th>\n      <td>118 days 16:11:36</td>\n      <td>115 days 09:18:59</td>\n    </tr>\n    <tr>\n      <th rowspan=\"5\" valign=\"top\">steps_to_FO_user_wise</th>\n      <th>mean</th>\n      <td>4.51</td>\n      <td>12.21</td>\n    </tr>\n    <tr>\n      <th>std</th>\n      <td>4.09</td>\n      <td>8.29</td>\n    </tr>\n    <tr>\n      <th>median</th>\n      <td>3.0</td>\n      <td>10.0</td>\n    </tr>\n    <tr>\n      <th>min</th>\n      <td>1</td>\n      <td>5</td>\n    </tr>\n    <tr>\n      <th>max</th>\n      <td>41</td>\n      <td>84</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ]
  },
  {
   "cell_type": "markdown",
   "source": [
    "### Time-based histograms"
   ],
   "metadata": {
    "id": "k7v2zN1p4Rkj"
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "#### User lifetime"
   ],
   "metadata": {
    "id": "20wdTUNL5WJs"
   }
  },
  {
   "cell_type": "code",
   "source": [
    "stream.user_lifetime_hist();"
   ],
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 449
    },
    "id": "5ILZ2Lwu4hTg",
    "executionInfo": {
     "status": "ok",
     "timestamp": 1682535876902,
     "user_tz": -180,
     "elapsed": 759,
     "user": {
      "displayName": "Anatoliy Zaykovskiy",
      "userId": "11710160701524337708"
     }
    },
    "outputId": "d3872853-ed28-4b11-b996-967712276f3c"
   },
   "execution_count": 20,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 600x450 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ]
  },
  {
   "cell_type": "markdown",
   "source": [
    "#### Timedelta between two events\n"
   ],
   "metadata": {
    "id": "HTW7lgU5S3c_"
   }
  },
  {
   "cell_type": "code",
   "source": [
    "stream.timedelta_hist(log_scale=True, timedelta_unit='m');"
   ],
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 453
    },
    "id": "oSmM7jrpT1-1",
    "executionInfo": {
     "status": "ok",
     "timestamp": 1682536647332,
     "user_tz": -180,
     "elapsed": 994,
     "user": {
      "displayName": "Anatoliy Zaykovskiy",
      "userId": "11710160701524337708"
     }
    },
    "outputId": "0aa5bd30-3209-41f0-9155-234f06ed44f1"
   },
   "execution_count": 21,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 600x450 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ]
  },
  {
   "cell_type": "code",
   "source": [
    "stream_with_synthetic = datasets\\\n",
    "    .load_simple_shop()\\\n",
    "    .add_start_end_events()\\\n",
    "    .split_sessions(timeout=(30, 'm'))\n",
    "\n",
    "stream_with_synthetic.timedelta_hist(log_scale=True, timedelta_unit='m')\n",
    "stream_with_synthetic.timedelta_hist(\n",
    "    raw_events_only=True,\n",
    "    log_scale=True,\n",
    "    timedelta_unit='m'\n",
    ");"
   ],
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 944
    },
    "id": "oOmuXJjxWNcU",
    "executionInfo": {
     "status": "ok",
     "timestamp": 1682536659137,
     "user_tz": -180,
     "elapsed": 5377,
     "user": {
      "displayName": "Anatoliy Zaykovskiy",
      "userId": "11710160701524337708"
     }
    },
    "outputId": "c0d1964a-f4ac-4a34-8492-a4968d9e205f"
   },
   "execution_count": 22,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 600x450 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": "<Figure size 600x450 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ]
  },
  {
   "cell_type": "code",
   "source": [
    "stream.timedelta_hist(event_pair=('product1', 'cart'), timedelta_unit='m');"
   ],
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 449
    },
    "id": "3Ca9XUOVXbRK",
    "executionInfo": {
     "status": "ok",
     "timestamp": 1682539478849,
     "user_tz": -180,
     "elapsed": 937,
     "user": {
      "displayName": "Anatoliy Zaykovskiy",
      "userId": "11710160701524337708"
     }
    },
    "outputId": "d14d127e-521b-42c3-ddbb-c4dcdc162386"
   },
   "execution_count": 23,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 600x450 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ]
  },
  {
   "cell_type": "code",
   "source": [
    "stream.timedelta_hist(\n",
    "    event_pair=('product1', 'cart'),\n",
    "    timedelta_unit='m',\n",
    "    adjacent_events_only=False\n",
    ");"
   ],
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 449
    },
    "id": "_XDrIryfXmWM",
    "executionInfo": {
     "status": "ok",
     "timestamp": 1682536989414,
     "user_tz": -180,
     "elapsed": 1117,
     "user": {
      "displayName": "Anatoliy Zaykovskiy",
      "userId": "11710160701524337708"
     }
    },
    "outputId": "3bddc560-849b-425d-9076-04a6e2f85573"
   },
   "execution_count": 24,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 600x450 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ]
  },
  {
   "cell_type": "code",
   "source": [
    "stream.timedelta_hist(\n",
    "        event_pair=('product1', 'cart'),\n",
    "        timedelta_unit='m',\n",
    "        adjacent_events_only=False,\n",
    "        lower_cutoff_quantile=0.9\n",
    "    );"
   ],
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 449
    },
    "id": "Q62Lpl6LKQBg",
    "executionInfo": {
     "status": "ok",
     "timestamp": 1682539467236,
     "user_tz": -180,
     "elapsed": 6,
     "user": {
      "displayName": "Anatoliy Zaykovskiy",
      "userId": "11710160701524337708"
     }
    },
    "outputId": "d49dc1ea-021b-4c52-95fe-8103de202f39"
   },
   "execution_count": 25,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 600x450 with 1 Axes>",
      "image/png": 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qZCSZFStWODzXletFpqvX32nTphlJZsKECVnaZr73T5w4YSSZkSNH5joWc+bMyVJHflm+fLmRZAYOHJjlsSvX2ezW+djYWHPbbbc5TMvptTHGmFKlSmU7lrlxc3Mzffv2va55jDEmPT3d+Pj4mBdeeMEY88+ylC1b1nTq1Mm4uLiYs2fPGmOMmTBhgilRooQ5ffq0MebmvlfefvttI8nMnz/fPi01NdVER0dneT2bNWuW5fMyLS3NhISEmIcfftg+Lbfvquw8/vjjpkSJEmbDhg1ZHst8PfO6nmT3eXH1MmeyOjMY87/30qpVq+zTjh8/btzd3c1zzz2Xp/HIi+yWM9PV66uvr6/p169fjn1lZGSYypUrZ/nOS0lJMVFRUaZ169b2aSNHjjSSzCOPPGJJzXnNTnlRoNex7NSpk3x9fe33GzZsKOmf4zddXV0dpl+8eFGHDh2SJC1ZskRnzpzRI488osTERPvNxcVFDRs2tP9Fd+TIEW3ZskXx8fEOz9O6dWvFxMQ41DJnzhz5+vqqdevWDn3WrVtX3t7eOf6VeC1XHgt0/vx5JSYmqlGjRjLGaPPmzXnqo3fv3g5bV5o2bar09HQdOHAgx3n8/Pz03//+12H3aV4tXLhQkhx28UjSc889J0n2XRzLli3T5cuX9cwzzzi0GzBgQI599+rVSy4uLg7TrhyjS5cu6eTJk6pUqZL8/Pyy7BKQ/tkicuV4NGzYUMYYPfnkk/ZpLi4uqlevnv7+++9clzU7xhjNmzdP7dq1kzHG4f0QGxurpKQke10dOnSQq6urw9bjrVu3atu2berSpYt92pw5c9S0aVP5+/s79NeqVSulp6dr1apVDjV06dJF/v7+9vuZWxduZHmuFBYW5rAFIXP38ObNm+1nzLq7u6tEiX8+CtLT03Xy5El5e3uratWq2b4e2enbt+9N1ZmdkydPSpLDuFxL7969HbYI9e3bV66urvb3eKaoqCjFxsY6TFu4cKEaNGjgsDvJ29tbvXv31v79+7Vt2zZ7u9DQUHXs2NHezsvL66ZOMJo3b54CAgKyXZcK4/GBmebNmyebzZZlC77kWPeV63xSUpISExPVrFkz/f3330pKSnKYL7vX5kZlrn/Xq0SJEmrUqJF9Pd2+fbtOnjypF198UcYY+8lRq1evVo0aNewnQ97M98qiRYtUrlw5PfDAA/ZpHh4e6tWrV7btvb29Hc5xcHNzU4MGDW74MyMjI0Pz589Xu3bt7Fuar5T5euZ1PbHCjWaGTDExMfbPUumfPXRVq1a96c/VG+Xn56d169bp8OHD2T6+ZcsW7d69W48++qhOnjxpf/+cP39eLVu21KpVq7KcGP3000/fdF3Xk53yokB3hUdERDjcz1yA8PDwbKdnHpOye/duSdI999yTbb8+Pj6SZA9elStXztLm6i/J3bt3KykpSUFBQdn2efz48dwXJgcJCQl65ZVXtGDBgizH1Fz9AZqTq8cp84s1t2M/hw0bpqVLl6pBgwaqVKmS2rRpo0cffVSNGze+5vMdOHBAJUqUUKVKlRymh4SEyM/Pzz6umf9e3a5MmTI5fvlHRUVlmZaamqqxY8dq+vTpOnTokMPm++zG6HreN7mNUU5OnDihM2fOaOrUqZo6dWq2bTLfDwEBAWrZsqW+/PJLvfbaa5L+2Q3u6upq3z0p/fP++uOPP+yHGuTUX6Ybec3zolKlSlmCSZUqVST9c5xNSEiI/Ri5999/X/v27VN6erq9bdmyZa/5HK6urnnaXXLx4sUsx0EFBgZm+cPjauY6du9cve57e3srNDQ0y/G72b0vDxw4YP/iulK1atXsj9eoUUMHDhzIdlyrVq2a5zqvtnfvXlWtWtXhy7Io2Lt3r8LCwq55fOfPP/+skSNHau3atUpJSXF4LCkpyeHLLLvX5kYZY244mDdt2lSjRo1SamqqVq9erdDQUN1xxx2qVauWVq9erdatW2vNmjXq3LmzfZ6b+V45cOCAKlasmKXeqz9vM5UvXz5LW39/f/3xxx95XUQHJ06cUHJy8jWvj5nX9cQKN5oZcppf+meMrvW5euLECYfPQW9vb4fLnd2o8ePHKz4+XuHh4apbt67uu+8+Pf7447rtttsk/S/rxMfH59hHUlKSw/etFevL9WSnvCjQT7GcvkBymp75hZKZ0GfNmqWQkJAs7W7kwzgjI0NBQUGaPXt2to/nFAhyk56ertatW+vUqVMaNmyYoqOjVapUKR06dEg9evTI8yWYrjUe2alWrZp27typ7777TosWLdK8efP0/vvv65VXXsn2ZJPs5MeWkezO5hwwYICmT5+uwYMH66677pKvr69sNpu6du2a7Rhdz/vmekJIpszn7N69e44r9JXHsnXt2lU9e/bUli1bVLt2bX355Zdq2bKl/bjVzD5bt26d40WaM8Ndbssi3djyXK8xY8ZoxIgReuKJJ/Taa6+pTJkyKlGihAYPHpyn9+yVWzxz88svv6hFixYO0/bt25fjxXczQ+3p06dv7DifXBTUGeA5rVPp6enXDNTFxd69e9WyZUtFR0drwoQJCg8Pl5ubmxYuXKh///vfWd5jVr42Z86ccVgvr0eTJk106dIlrV27VqtXr7Zv+WratKlWr16tHTt26MSJEw5bxPLjeyUnzvzMuFE2my3b+q4McVe60cxwve2uVr9+fYc9hCNHjszxMm+5reNX69y5s5o2baqvv/5aP/74o95880298cYb+uqrrxQXF2dfF958880cLw91dcAtjFezKBJ/HmcepB0UFJTrGaIVKlSQ9L/Uf6WdO3dm6XPp0qVq3Ljxdb8wOb2R/vzzT+3atUszZ850OIFkyZIl19X/jSpVqpS6dOmiLl266OLFi+rQoYNef/11DR8+XB4eHjnWXaFCBWVkZGj37t32vzqlf05oOXPmjH1cM//ds2ePw19JJ0+evK4ta3PnzlV8fLzefvtt+7QLFy447cLtgYGBKl26tNLT0/N0BnL79u3Vp08f++7wXbt2afjw4Q5tKlasqHPnzuWpv7y6keC/Z8+eLFttdu3aJUn2QDd37ly1aNFC//d//+cw7818KWenVq1aWdaF7P5QzBQdHS3pn/BZs2bNPD3H7t27HcLruXPndOTIEd13333XnLdChQpZPickaceOHfbHM//dunVrlnHNbl5/f/9s39cHDhywb6WQ/nm/rFu3TpcuXcrx5I7CuEu8YsWKWrx4sU6dOpXjVstvv/1WaWlpWrBggcMWpOs93Oh6l//QoUO6ePGiw2fa9WjQoIHc3Ny0evVqrV692n5VjbvvvlsfffSRli1bZr+f6Wa+VypUqKBt27ZleV/t2bPnhuqXrm/MAgMD5ePjo61bt16zzrysJ9nx9/fPdjd0bod5OcPs2bMdruRy5bp6tcyth1ev5zktU2hoqJ555hk988wzOn78uO644w69/vrriouLs2cdHx8fS787ruV6slNeFInfCo+NjZWPj4/GjBmjS5cuZXk881I8oaGhql27tmbOnOmwS3XJkiVZjvvo3Lmz0tPT7bszr3T58uVcQ07mdaKubpP519GVfw0ZY/TOO+/kvoAWyDweLZObm5tiYmJkjLGPWU51Z37pXn2m8oQJEyRJbdu2lSS1bNlSrq6uWS4TcuUldvLCxcUly1+M7733Xo5/teY3FxcXPfzww5o3b162H6pXX+rJz89PsbGx+vLLL/X555/Lzc0ty0WbO3furLVr12rx4sVZ+jtz5owuX7583XXm9Prl5vDhww5n9ScnJ+vjjz9W7dq17aEuu9djzpw5WY5Xuln+/v5q1aqVwy23a6nVrVtXbm5uefqJ00xTp051+IyYMmWKLl++rLi4uGvOe99992n9+vUOFxc/f/68pk6dqsjISPuxRvfdd58OHz6suXPn2tulpKRkexhFxYoV9euvvzpcquW7777TwYMHHdo9/PDDSkxMzHZdynxtMs+2L0y/nPXwww/LGJPtXpHMurP7XExKStL06dOv67lKlSp1Xcu+adMmSbmfBZ0bDw8P1a9fX5999pkSEhIctlimpqbq3XffVcWKFRUaGmqf52a+V2JjY3Xo0CEtWLDAPu3ChQv66KOPbqh+6fo+M0qUKKH27dvr22+/zXady3z98rqeZKdixYr2Lb2Zfv/99yyX0nG2xo0bO3xO5RYsfXx8FBAQkOW4+ffff9/hfnp6epZDvYKCghQWFma/VFndunVVsWJFvfXWW9n+hO3V30VWuZ7slBdFYoulj4+PpkyZoscee0x33HGHunbtqsDAQCUkJOj7779X48aN7R/IY8eOVdu2bdWkSRM98cQTOnXqlP36jle+UM2aNVOfPn00duxYbdmyRW3atFHJkiW1e/duzZkzR++8847DwflXqlixovz8/PTBBx+odOnSKlWqlBo2bKjo6GhVrFhRzz//vA4dOiQfHx/Nmzfvpo+Ty4s2bdooJCREjRs3VnBwsLZv365Jkyapbdu2Kl26tKT/XX7jpZdeUteuXVWyZEm1a9dOtWrVUnx8vKZOnaozZ86oWbNmWr9+vWbOnKn27dvbtwAFBwdr0KBBevvtt/XAAw/o3nvv1e+//64ffvhBAQEBef7r+P7779esWbPk6+urmJgYrV27VkuXLs3T8XzXq0ePHpo5c2auu1wlady4cVqxYoUaNmyoXr16KSYmRqdOndJvv/2mpUuXZjk2sEuXLurevbvef/99xcbGZvklo6FDh2rBggW6//777Ze3OH/+vP7880/NnTtX+/fvv+6tgZmv38CBAxUbGysXFxd17do113mqVKmiJ598Uhs2bFBwcLCmTZumY8eOOXyp33///Xr11VfVs2dPNWrUSH/++admz56d64dpQfDw8FCbNm20dOnSPP96ysWLF9WyZUt17txZO3fu1Pvvv68mTZo4nBCRkxdffFGfffaZ4uLiNHDgQJUpU8b+3pk3b559d3+vXr00adIkPf7449q0aZNCQ0M1a9asbC+z9NRTT2nu3Lm699571blzZ+3du1effPJJlkvlPP744/r44481ZMgQrV+/Xk2bNtX58+e1dOlSPfPMM3rwwQfl6empmJgYffHFF6pSpYrKlCmjGjVq2I9n+9e//iVJ9mv7zpo1S2vWrJEkvfzyy7kue+a6cfWxqNfSokULPfbYY3r33Xe1e/du3XvvvcrIyNDq1avVokUL9e/fX23atJGbm5vatWunPn366Ny5c/roo48UFBSkI0eO5Pm56tatq6VLl2rChAkKCwtTVFRUtsf6ZVqyZIkiIiKyXGroepa1adOmGjdunHx9fe1bzYOCglS1alXt3Lkzy7U0b+Z7pU+fPpo0aZIeeeQRDRo0SKGhoZo9e7b9j68b2WKd03dVTsfljRkzRj/++KOaNWum3r17q1q1ajpy5IjmzJmjNWvWyM/PL8/rSXaeeOIJTZgwQbGxsXryySd1/PhxffDBB6pevbqSk5Ove/kKi6eeekrjxo3TU089pXr16mnVqlX2PUOZzp49q/Lly6tjx46qVauWvL29tXTpUm3YsMG+965EiRL6z3/+o7i4OFWvXl09e/ZUuXLldOjQIa1YsUI+Pj769ttv82UZ8pqd8uS6ziG/wo1cbujNN990aLdixQojycyZM8dheualQ66+5MGKFStMbGys8fX1NR4eHqZixYqmR48eZuPGjQ7t5s2bZ6pVq2bc3d1NTEyM+eqrr7LUlGnq1Kmmbt26xtPT05QuXdrUrFnTvPDCC+bw4cP2NtldIuGbb74xMTExxtXV1eG0/W3btplWrVoZb29vExAQYHr16mV+//33PF3yIbflVjaXm7iypg8//NDcfffdpmzZssbd3d1UrFjRDB061CQlJTn09dprr5ly5cqZEiVKOFx66NKlS2b06NEmKirKlCxZ0oSHh5vhw4c7XL7BmH8u6zNixAgTEhJiPD09zT333GO2b99uypYt63D5n5yWxRhjTp8+bXr27GkCAgKMt7e3iY2NNTt27MhyaZac+si8zMKJEyccpsfHx5tSpUo5THv44YeNp6en/XIguTl27Jjp16+fCQ8PNyVLljQhISGmZcuWZurUqVnaJicnG09PTyPJfPLJJ9n2d/bsWTN8+HBTqVIl4+bmZgICAkyjRo3MW2+9Zb8kTk7rhjFZL1Vx+fJlM2DAABMYGGhsNts1Lz1UoUIF07ZtW7N48WJz++23G3d3dxMdHZ1lfbtw4YJ57rnnTGhoqPH09DSNGzc2a9euzfIey+lyQ1ePuZW++uorY7PZ7Jdnyknme+Wnn34yvXv3Nv7+/sbb29t069bNnDx50qFt5rhkZ+/evaZjx47Gz8/PeHh4mAYNGpjvvvsuS7sDBw6YBx54wHh5eZmAgAAzaNAg+yVlrr7Mz9tvv23KlStn3N3dTePGjc3GjRuz/UxJSUkxL730kn0dDAkJMR07djR79+61t/nll19M3bp1jZubW5b3h6Qcb9cSEBBg7rzzzmu2y87ly5fNm2++aaKjo42bm5sJDAw0cXFxZtOmTfY2CxYsMLfffrvx8PAwkZGR5o033rBfYunKy5/l9trs2LHD3H333fb1LrdLD6Wnp5vQ0FDz8ssv39Syfv/990aSiYuLc5j+1FNPGUnm//7v/7Kd70a/V/7++2/Ttm1b4+npaQIDA81zzz1n5s2bZySZX3/91WHe7C4vl933XE7fVTk5cOCAefzxx01gYKBxd3c3t912m+nXr59JS0uzt8nLepLTZXg++eQTc9tttxk3NzdTu3Zts3jx4nzJDDm9l3K65NHNSElJMU8++aTx9fU1pUuXNp07dzbHjx93WEfT0tLM0KFDTa1atUzp0qVNqVKlTK1atcz777+fpb/NmzebDh062L/PK1SoYDp37myWLVtmb5PT92Be5PTaXE92ys0NB0sg0+nTp40k869//cvZpWQRFBRknn/+eWeX4RS5fUkXFZcvXzZVqlTJNiBcKbc/ZJC7v/76y0jKNkAXVV9//bXx9PR0CHLGFM1l/fe//20kmf/+97/OLgXIkyJxjCUKj+x+mjLz2MzsfqrLmf766y+lpqY6/NwaihYXFxe9+uqrmjx58vXvjkGerFixQnfddZf9WOri4I033lD//v0djn+UCv+yXv35euHCBX344YeqXLmyypUr56SqgOtjM6YQX5sAhc6MGTM0Y8YM3XffffL29taaNWv02WefqU2bNtmeqALniYyMVI0aNfTdd985u5R8l/kTehs2bMj24s5AURAXF6eIiAjVrl1bSUlJ+uSTT/TXX39p9uzZevTRR51dHgq57K4VfDVfX998v0RRkTh5B4XH7bffLldXV40fP17Jycn2E3oyTxwAANyY2NhY/ec//9Hs2bOVnp6umJgYff755w6/6gXkJLtrBV9t+vTpWU46sxpbLAEAAIq406dP2y+zlZPq1atnOUTEagRLAAAAWIKTdwAAAGAJjrEsJDIyMnT48GGVLl26UP50GwAAhZUxRmfPnlVYWFiuF2lH/iNYFhKHDx9WeHi4s8sAAKDIOnjwoMqXL+/sMm5pBMtCIvNnFw8ePCgfHx8nVwMAQNGRnJys8PBw+3cpnIdgWUhk7v728fEhWAIAcAM4lMz5OBABAAAAliBYAgAAwBIESwAAAFiCYAkAAABLECwBAABgCYIlAAAALEGwBAAAgCUIlgAAALAEwRIAAACWIFgCAADAEgRLAAAAWIJgCQAAAEsQLAEAAGAJV2cXgPyVkJCgxMRES/sMCAhQRESEpX0CAICij2BZjCUkJCg6uppSU1Ms7dfT00s7dmwnXAIAAAcEy2IsMTFRqakpavjESPmERlrSZ/KR/Vo3bbQSExMJlgAAwAHB8hbgExqpMhFVnV0GAAAo5jh5BwAAAJYgWAIAAMASBEsAAABYgmAJAAAASxAsAQAAYAmCJQAAACxBsAQAAIAlCJYAAACwBMESAAAAliBYAgAAwBIESwAAAFiCYAkAAABLECzzYNWqVWrXrp3CwsJks9k0f/78LG22b9+uBx54QL6+vipVqpTq16+vhISEgi8WAADASQiWeXD+/HnVqlVLkydPzvbxvXv3qkmTJoqOjtbKlSv1xx9/aMSIEfLw8CjgSgEAAJzH1dkFFAVxcXGKi4vL8fGXXnpJ9913n8aPH2+fVrFixYIoDQAAoNBgi+VNysjI0Pfff68qVaooNjZWQUFBatiwYba7y6+Ulpam5ORkhxsAAEBRRrC8ScePH9e5c+c0btw43Xvvvfrxxx/10EMPqUOHDvrpp59ynG/s2LHy9fW138LDwwuwagAAAOsRLG9SRkaGJOnBBx/Us88+q9q1a+vFF1/U/fffrw8++CDH+YYPH66kpCT77eDBgwVVMgAAQL7gGMubFBAQIFdXV8XExDhMr1atmtasWZPjfO7u7nJ3d8/v8gAAAAoMWyxvkpubm+rXr6+dO3c6TN+1a5cqVKjgpKoAAAAKHlss8+DcuXPas2eP/f6+ffu0ZcsWlSlTRhERERo6dKi6dOmiu+++Wy1atNCiRYv07bffauXKlc4rGgAAoIARLPNg48aNatGihf3+kCFDJEnx8fGaMWOGHnroIX3wwQcaO3asBg4cqKpVq2revHlq0qSJs0oGAAAocATLPGjevLmMMbm2eeKJJ/TEE08UUEUAAACFD8dYAgAAwBIESwAAAFiCYAkAAABLECwBAABgCYIlAAAALEGwBAAAgCUIlgAAALAEwRIAAACWIFgCAADAEgRLAAAAWIJgCQAAAEsQLAEAAGAJgiUAAAAsQbAEAACAJQiWAAAAsATBEgAAAJYgWAIAAMASBEsAAABYgmAJAAAASxAsAQAAYAmCJQAAACxBsAQAAIAlCJYAAACwBMESAAAAliBYAgAAwBIESwAAAFiCYAkAAABLECwBAABgCYJlHqxatUrt2rVTWFiYbDab5s+fn2Pbp59+WjabTRMnTiyw+gAAAAoDgmUenD9/XrVq1dLkyZNzbff111/r119/VVhYWAFVBgAAUHi4OruAoiAuLk5xcXG5tjl06JAGDBigxYsXq23btgVUGQAAQOFBsLRARkaGHnvsMQ0dOlTVq1fP0zxpaWlKS0uz309OTs6v8gAAAAoEu8It8MYbb8jV1VUDBw7M8zxjx46Vr6+v/RYeHp6PFQIAAOQ/guVN2rRpk9555x3NmDFDNpstz/MNHz5cSUlJ9tvBgwfzsUoAAID8R7C8SatXr9bx48cVEREhV1dXubq66sCBA3ruuecUGRmZ43zu7u7y8fFxuAEAABRlHGN5kx577DG1atXKYVpsbKwee+wx9ezZ00lVAQAAFDyCZR6cO3dOe/bssd/ft2+ftmzZojJlyigiIkJly5Z1aF+yZEmFhISoatWqBV0qAACA0xAs82Djxo1q0aKF/f6QIUMkSfHx8ZoxY4aTqgIAAChcCJZ50Lx5cxlj8tx+//79+VcMAABAIcXJOwAAALAEwRIAAACWIFgCAADAEgRLAAAAWIJgCQAAAEsQLAEAAGAJgiUAAAAsQbAEAACAJQiWAAAAsATBEgAAAJYgWAIAAMASBEsAAABYgmAJAAAASxAsAQAAYAmCJQAAACxBsAQAAIAlCJYAAACwBMESAAAAliBYAgAAwBIESwAAAFiCYAkAAABLECwBAABgCYIlAAAALEGwBAAAgCUIlgAAALAEwRIAAACWIFgCAADAEgTLPFi1apXatWunsLAw2Ww2zZ8/3/7YpUuXNGzYMNWsWVOlSpVSWFiYHn/8cR0+fNh5BQMAADgBwTIPzp8/r1q1amny5MlZHktJSdFvv/2mESNG6LffftNXX32lnTt36oEHHnBCpQAAAM7j6uwCioK4uDjFxcVl+5ivr6+WLFniMG3SpElq0KCBEhISFBERURAlAgAAOB1bLPNBUlKSbDab/Pz8nF0KAABAgWGLpcUuXLigYcOG6ZFHHpGPj0+O7dLS0pSWlma/n5ycXBDlFVoJCQlKTEy0tM+AgAC2GAMAUIAIlha6dOmSOnfuLGOMpkyZkmvbsWPHavTo0QVUWeGWkJCg6OhqSk1NsbRfT08v7dixnXAJAEABIVhaJDNUHjhwQMuXL891a6UkDR8+XEOGDLHfT05OVnh4eH6XWSglJiYqNTVFDZ8YKZ/QSEv6TD6yX+umjVZiYiLBEgCAAkKwtEBmqNy9e7dWrFihsmXLXnMed3d3ubu7F0B1RYdPaKTKRFR1dhkAAOAGESzz4Ny5c9qzZ4/9/r59+7RlyxaVKVNGoaGh6tixo3777Td99913Sk9P19GjRyVJZcqUkZubm7PKBgAAKFAEyzzYuHGjWrRoYb+fuQs7Pj5eo0aN0oIFCyRJtWvXdphvxYoVat68eUGVCQAA4FQEyzxo3ry5jDE5Pp7bYwAAALcKrmMJAAAASxAsAQAAYAmCJQAAACxBsAQAAIAlCJYAAACwBMESAAAAliBYAgAAwBIESwAAAFiCYAkAAABLECwBAABgCYIlAAAALEGwBAAAgCVcnV0Aiqbt27cXyr7yu++AgABFRERY2icAAMUFwRLXJTXppCSbunfvbnnfl9IuWtZXftXp6emlHTu2Ey4BAMgGwRLX5VLKWUlGtR8dpsCoaEv6PPLnWm1dMFWXL1+2pD8pf+pMPrJf66aNVmJiIsESAIBsECxxQ7yDIlQmoqolfSUf2W9JP9mxsk4AAJA7Tt4BAACAJQiWAAAAsATBEgAAAJYgWAIAAMASBEsAAABYgmAJAAAASxAsAQAAYAmCJQAAACxBsAQAAIAlCJYAAACwBMESAAAAliBYAgAAwBIEyzxYtWqV2rVrp7CwMNlsNs2fP9/hcWOMXnnlFYWGhsrT01OtWrXS7t27nVMsAACAkxAs8+D8+fOqVauWJk+enO3j48eP17vvvqsPPvhA69atU6lSpRQbG6sLFy4UcKUAAADO4+rsAoqCuLg4xcXFZfuYMUYTJ07Uyy+/rAcffFCS9PHHHys4OFjz589X165dC7JUAAAAp2GL5U3at2+fjh49qlatWtmn+fr6qmHDhlq7dq0TKwMAAChYbLG8SUePHpUkBQcHO0wPDg62P5adtLQ0paWl2e8nJyfnT4EAAAAFhC2WTjJ27Fj5+vrab+Hh4c4uCQAA4KYQLG9SSEiIJOnYsWMO048dO2Z/LDvDhw9XUlKS/Xbw4MF8rRMAACC/Fdtgedttt+nkyZNZpp85c0a33XabZc8TFRWlkJAQLVu2zD4tOTlZ69at01133ZXjfO7u7vLx8XG4AQAAFGXF9hjL/fv3Kz09Pcv0tLQ0HTp06Lr6OnfunPbs2WO/v2/fPm3ZskVlypRRRESEBg8erH/961+qXLmyoqKiNGLECIWFhal9+/Y3uxgAAABFRrELlgsWLLD/f/HixfL19bXfT09P17JlyxQZGXldfW7cuFEtWrSw3x8yZIgkKT4+XjNmzNALL7yg8+fPq3fv3jpz5oyaNGmiRYsWycPD4+YWBgAAoAgpdsEycyuhzWZTfHy8w2MlS5ZUZGSk3n777evqs3nz5jLG5Pi4zWbTq6++qldfffW66wUAACguil2wzMjIkPTPsY8bNmxQQECAkysCAAC4NRS7YJlp3759zi4BAADgllJsg6UkLVu2TMuWLdPx48ftWzIzTZs2zUlVAQAAFE/FNliOHj1ar776qurVq6fQ0FDZbDZnlwQAAFCsFdtg+cEHH2jGjBl67LHHnF0KAADALaHYXiD94sWLatSokbPLAAAAuGUU22D51FNP6dNPP3V2GQAAALeMYrsr/MKFC5o6daqWLl2q22+/XSVLlnR4fMKECU6qDAAAoHgqtsHyjz/+UO3atSVJW7dudXiME3kAAACsV2yD5YoVK5xdAgAAwC2l2B5jCQAAgIJVbLdYtmjRItdd3suXLy/AagAAAIq/YhssM4+vzHTp0iVt2bJFW7duVXx8vHOKAgAAKMaKbbD897//ne30UaNG6dy5cwVcDQAAQPF3yx1j2b17d34nHAAAIB/ccsFy7dq18vDwcHYZAAAAxU6x3RXeoUMHh/vGGB05ckQbN27UiBEjnFQVAABA8VVsg6Wvr6/D/RIlSqhq1ap69dVX1aZNGydVBQAAUHwV22A5ffp0Z5cAAABwSym2wTLTpk2btH37dklS9erVVadOHSdXBAAAUDwV22B5/Phxde3aVStXrpSfn58k6cyZM2rRooU+//xzBQYGOrdAAACAYqbYnhU+YMAAnT17Vn/99ZdOnTqlU6dOaevWrUpOTtbAgQOdXR4AAECxU2y3WC5atEhLly5VtWrV7NNiYmI0efJkTt4BAADIB8V2i2VGRoZKliyZZXrJkiWVkZHhhIoAAACKt2IbLO+55x4NGjRIhw8ftk87dOiQnn32WbVs2dKJlQEAABRPxTZYTpo0ScnJyYqMjFTFihVVsWJFRUVFKTk5We+9956zywMAACh2iu0xluHh4frtt9+0dOlS7dixQ5JUrVo1tWrVysmVAQAAFE/Fbovl8uXLFRMTo+TkZNlsNrVu3VoDBgzQgAEDVL9+fVWvXl2rV692dpkAAADFTrELlhMnTlSvXr3k4+OT5TFfX1/16dNHEyZMsPQ509PTNWLECEVFRcnT01MVK1bUa6+9JmOMpc8DAABQmBW7YPn777/r3nvvzfHxNm3aaNOmTZY+5xtvvKEpU6Zo0qRJ2r59u9544w2NHz+eYzkBAMAtpdgdY3ns2LFsLzOUydXVVSdOnLD0OX/55Rc9+OCDatu2rSQpMjJSn332mdavX2/p8wAAABRmxW6LZbly5bR169YcH//jjz8UGhpq6XM2atRIy5Yt065duyT9s9V0zZo1iouLy3GetLQ0JScnO9wAAACKsmIXLO+77z6NGDFCFy5cyPJYamqqRo4cqfvvv9/S53zxxRfVtWtXRUdHq2TJkqpTp44GDx6sbt265TjP2LFj5evra7+Fh4dbWhMAAEBBK3a7wl9++WV99dVXqlKlivr376+qVatKknbs2KHJkycrPT1dL730kqXP+eWXX2r27Nn69NNPVb16dW3ZskWDBw9WWFiY4uPjs51n+PDhGjJkiP1+cnIy4RIAABRpxS5YBgcH65dfflHfvn01fPhw+5nZNptNsbGxmjx5soKDgy19zqFDh9q3WkpSzZo1deDAAY0dOzbHYOnu7i53d3dL6wAAAHCmYhcsJalChQpauHChTp8+rT179sgYo8qVK8vf3z9fni8lJUUlSjgeVeDi4sJvkgMAgFtKsQyWmfz9/VW/fv18f5527drp9ddfV0REhKpXr67NmzdrwoQJeuKJJ/L9uQEAAAqLYh0sC8p7772nESNG6JlnntHx48cVFhamPn366JVXXnF2aQAAAAWGYGmB0qVLa+LEiZo4caKzSwEAAHCaYne5IQAAADgHwRIAAACWIFgCAADAEgRLAAAAWIJgCQAAAEsQLAEAAGAJgiUAAAAsQbAEAACAJQiWAAAAsATBEgAAAJYgWAIAAMASBEsAAABYwtXZBQBFzfbt2y3vMyAgQBEREZb3CwBAQSJYAnmUmnRSkk3du3e3vG9PTy/t2LGdcAkAKNIIlkAeXUo5K8mo9qPDFBgVbVm/yUf2a9200UpMTCRYAgCKNIIlcJ28gyJUJqKqs8sAAKDQ4eQdAAAAWIJgCQAAAEsQLAEAAGAJgiUAAAAsQbAEAACAJQiWAAAAsATBEgAAAJYgWAIAAMASBEsAAABYgmAJAAAASxAsAQAAYAmCJQAAACxBsLTIoUOH1L17d5UtW1aenp6qWbOmNm7c6OyyAAAACoyrswsoDk6fPq3GjRurRYsW+uGHHxQYGKjdu3fL39/f2aUBAAAUGIKlBd544w2Fh4dr+vTp9mlRUVFOrAgAAKDgsSvcAgsWLFC9evXUqVMnBQUFqU6dOvroo49ynSctLU3JyckONwAAgKKMYGmBv//+W1OmTFHlypW1ePFi9e3bVwMHDtTMmTNznGfs2LHy9fW138LDwwuwYgAAAOsRLC2QkZGhO+64Q2PGjFGdOnXUu3dv9erVSx988EGO8wwfPlxJSUn228GDBwuwYgAAAOsRLC0QGhqqmJgYh2nVqlVTQkJCjvO4u7vLx8fH4QYAAFCUESwt0LhxY+3cudNh2q5du1ShQgUnVQQAAFDwCJYWePbZZ/Xrr79qzJgx2rNnjz799FNNnTpV/fr1c3ZpAAAABYZgaYH69evr66+/1meffaYaNWrotdde08SJE9WtWzdnlwYAAFBguI6lRe6//37df//9zi4DAADAadhiCQAAAEsQLAEAAGAJgiUAAAAsQbAEAACAJQiWAAAAsATBEgAAAJYgWAIAAMASBEsAAABYgmAJAAAASxAsAQAAYAmCJQAAACxBsAQAAIAlXJ1dAIB/bN++3dL+AgICFBERYWmf+SEhIUGJiYmW9llUlh0AihuCJeBkqUknJdnUvXt3S/v19PTSjh3bC3XASkhIUHR0NaWmpljab1FYdgAojgiWgJNdSjkryaj2o8MUGBVtSZ/JR/Zr3bTRSkxMLNThKjExUampKWr4xEj5hEZa0mdRWXYAKI4IlkAh4R0UoTIRVZ1dhlP4hEbesssOAMUJJ+8AAADAEgRLAAAAWIJgCQAAAEsQLAEAAGAJgiUAAAAsQbAEAACAJQiWAAAAsATBEgAAAJYgWAIAAMASBEsAAABYgmAJAAAASxAsAQAAYAmCZT4YN26cbDabBg8e7OxSAAAACgzB0mIbNmzQhx9+qNtvv93ZpQAAABQogqWFzp07p27duumjjz6Sv7+/s8sBAAAoUARLC/Xr109t27ZVq1atrtk2LS1NycnJDjcAAICizNXZBRQXn3/+uX777Tdt2LAhT+3Hjh2r0aNH53NVAAAABYctlhY4ePCgBg0apNmzZ8vDwyNP8wwfPlxJSUn228GDB/O5SgAAgPzFFksLbNq0ScePH9cdd9xhn5aenq5Vq1Zp0qRJSktLk4uLi8M87u7ucnd3L+hSAQAA8g3B0gItW7bUn3/+6TCtZ8+eio6O1rBhw7KESgAAgOKIYGmB0qVLq0aNGg7TSpUqpbJly2aZDgAAUFxxjCUAAAAswRbLfLJy5UpnlwAAAFCg2GIJAAAASxAsAQAAYAmCJQAAACxBsAQAAIAlCJYAAACwBMESAAAAliBYAgAAwBIESwAAAFiCYAkAAABLECwBAABgCYIlAAAALMFvhQMolrZv325pfwEBAYqIiLC0TwAobgiWAIqV1KSTkmzq3r27pf16enppx47thEsAyAXBEkCxcinlrCSj2o8OU2BUtCV9Jh/Zr3XTRisxMZFgCQC5IFgCKJa8gyJUJqKqs8sAgFsKJ+8AAADAEgRLAAAAWIJgCQAAAEsQLAEAAGAJgiUAAAAsQbAEAACAJQiWAAAAsATBEgAAAJYgWAIAAMASBEsAAABYgmAJAAAASxAsAQAAYAmCJQAAACxBsLTA2LFjVb9+fZUuXVpBQUFq3769du7c6eyyAAAAChTB0gI//fST+vXrp19//VVLlizRpUuX1KZNG50/f97ZpQEAABQYV2cXUBwsWrTI4f6MGTMUFBSkTZs26e6773ZSVQAAAAWLYJkPkpKSJEllypTJsU1aWprS0tLs95OTk/O9Ltx6tm/fbml/aWlpcnd3t6w/q+sDYK2EhAQlJiZa3m9AQIAiIiIs7xfOR7C0WEZGhgYPHqzGjRurRo0aObYbO3asRo8eXYCV4VaSmnRSkk3du3e3tmObTTLG2j4lXUq7aHmfAG5OQkKCoqOrKTU1xfK+PT29tGPHdsJlMUSwtFi/fv20detWrVmzJtd2w4cP15AhQ+z3k5OTFR4ent/l4RZxKeWsJKPajw5TYFS0JX0e+XOtti6Ymi99Xr582ZL+AFgnMTFRqakpavjESPmERlrWb/KR/Vo3bbQSExMJlsUQwdJC/fv313fffadVq1apfPnyubZ1d3e3dJcikB3voAiViahqSV/JR/bnW58ACi+f0EjL1nkUfwRLCxhjNGDAAH399ddauXKloqKinF0SAABAgSNYWqBfv3769NNP9c0336h06dI6evSoJMnX11eenp5Org4AAKBgcB1LC0yZMkVJSUlq3ry5QkND7bcvvvjC2aUBAAAUGLZYWsDkw1myAAAARQ1bLAEAAGAJgiUAAAAsQbAEAACAJQiWAAAAsATBEgAAAJYgWAIAAMASBEsAAABYgmAJAAAASxAsAQAAYAmCJQAAACxBsAQAAIAl+K1wAMij7du3W9pfWlqa3N3dLe0zICBAERERlvYpSQkJCUpMTLS0z6Ky/Pmx7EWhTqvf77g1ECwB4BpSk05Ksql79+7WdmyzScZY2qWnp5d27NhuaWhJSEhQdHQ1paamWNanpCKx/Pm17EWlTkm6lHbR8j5RfBEsAeAaLqWclWRU+9FhCoyKtqTPI3+u1dYFUy3tM/nIfq2bNlqJiYmWBsvExESlpqao4RMj5RMaaUmfRWX582PZi0qdma/R5cuXLekPtwaCJQDkkXdQhMpEVLWkr+Qj+y3vM7/5hEbesstv5bLnp/x4jYDrwck7AAAAsATBEgAAAJYgWAIAAMASBEsAAABYgmAJAAAASxAsAQAAYAmCJQAAACxBsAQAAIAlCJYAAACwBMESAAAAliBYAgAAwBIESwAAAFiCYGmhyZMnKzIyUh4eHmrYsKHWr1/v7JIAAAAKDMHSIl988YWGDBmikSNH6rffflOtWrUUGxur48ePO7s0AACAAkGwtMiECRPUq1cv9ezZUzExMfrggw/k5eWladOmObs0AACAAkGwtMDFixe1adMmtWrVyj6tRIkSatWqldauXevEygAAAAqOq7MLKA4SExOVnp6u4OBgh+nBwcHasWNHtvOkpaUpLS3Nfj8pKUmSlJycbFld586dkySdOrBTl9NSLekz+cgBSVLSod0q6Wqjz0LaL33eon0eTZAkbdq0yb7+W2Hnzp2SisBnST4sf74se1GpM78+8/7/5T937pxl33mZ/RhjLOkPN85meBVu2uHDh1WuXDn98ssvuuuuu+zTX3jhBf30009at25dlnlGjRql0aNHF2SZAAAUawcPHlT58uWdXcYtjS2WFggICJCLi4uOHTvmMP3YsWMKCQnJdp7hw4dryJAh9vsZGRk6deqUypYtK5vN8S/D5ORkhYeH6+DBg/Lx8bF+AYoxxu7GMG43hnG7cYzdjWHc/mGM0dmzZxUWFubsUm55BEsLuLm5qW7dulq2bJnat28v6Z+guGzZMvXv3z/bedzd3eXu7u4wzc/PL9fn8fHxuaU/OG4GY3djGLcbw7jdOMbuxjBukq+vr7NLgAiWlhkyZIji4+NVr149NWjQQBMnTtT58+fVs2dPZ5cGAABQIAiWFunSpYtOnDihV155RUePHlXt2rW1aNGiLCf0AAAAFFcESwv1798/x13fN8Pd3V0jR47Msusc18bY3RjG7cYwbjeOsbsxjBsKG84KBwAAgCW4QDoAAAAsQbAEAACAJQiWAAAAsATBEgAAAJYgWBYBkydPVmRkpDw8PNSwYUOtX7/e2SXlm7Fjx6p+/foqXbq0goKC1L59e/tv4Ga6cOGC+vXrp7Jly8rb21sPP/xwll89SkhIUNu2beXl5aWgoCANHTpUly9fdmizcuVK3XHHHXJ3d1elSpU0Y8aMLPUU1bEfN26cbDabBg8ebJ/GuGXv0KFD6t69u8qWLStPT0/VrFlTGzdutD9ujNErr7yi0NBQeXp6qlWrVtq9e7dDH6dOnVK3bt3k4+MjPz8/Pfnkk1l+A/qPP/5Q06ZN5eHhofDwcI0fPz5LLXPmzFF0dLQ8PDxUs2ZNLVy4MH8W2gLp6ekaMWKEoqKi5OnpqYoVK+q1115z+K1mxk5atWqV2rVrp7CwMNlsNs2fP9/h8cI0RnmpBbgmg0Lt888/N25ubmbatGnmr7/+Mr169TJ+fn7m2LFjzi4tX8TGxprp06ebrVu3mi1btpj77rvPREREmHPnztnbPP300yY8PNwsW7bMbNy40dx5552mUaNG9scvX75satSoYVq1amU2b95sFi5caAICAszw4cPtbf7++2/j5eVlhgwZYrZt22bee+894+LiYhYtWmRvU1THfv369SYyMtLcfvvtZtCgQfbpjFtWp06dMhUqVDA9evQw69atM3///bdZvHix2bNnj73NuHHjjK+vr5k/f775/fffzQMPPGCioqJMamqqvc29995ratWqZX799VezevVqU6lSJfPII4/YH09KSjLBwcGmW7duZuvWreazzz4znp6e5sMPP7S3+fnnn42Li4sZP3682bZtm3n55ZdNyZIlzZ9//lkwg3GdXn/9dVO2bFnz3XffmX379pk5c+YYb29v884779jbMHbGLFy40Lz00kvmq6++MpLM119/7fB4YRqjvNQCXAvBspBr0KCB6devn/1+enq6CQsLM2PHjnViVQXn+PHjRpL56aefjDHGnDlzxpQsWdLMmTPH3mb79u1Gklm7dq0x5p8P8hIlSpijR4/a20yZMsX4+PiYtLQ0Y4wxL7zwgqlevbrDc3Xp0sXExsba7xfFsT979qypXLmyWbJkiWnWrJk9WDJu2Rs2bJhp0qRJjo9nZGSYkJAQ8+abb9qnnTlzxri7u5vPPvvMGGPMtm3bjCSzYcMGe5sffvjB2Gw2c+jQIWOMMe+//77x9/e3j2Pmc1etWtV+v3PnzqZt27YOz9+wYUPTp0+fm1vIfNK2bVvzxBNPOEzr0KGD6datmzGGscvO1cGyMI1RXmoB8oJd4YXYxYsXtWnTJrVq1co+rUSJEmrVqpXWrl3rxMoKTlJSkiSpTJkykqRNmzbp0qVLDmMSHR2tiIgI+5isXbtWNWvWdPjVo9jYWCUnJ+uvv/6yt7myj8w2mX0U1bHv16+f2rZtm2XZGLfsLViwQPXq1VOnTp0UFBSkOnXq6KOPPrI/vm/fPh09etRheXx9fdWwYUOHcfPz81O9evXsbVq1aqUSJUpo3bp19jZ333233Nzc7G1iY2O1c+dOnT592t4mt7EtbBo1aqRly5Zp165dkqTff/9da9asUVxcnCTGLi8K0xjlpRYgLwiWhVhiYqLS09Oz/CxkcHCwjh496qSqCk5GRoYGDx6sxo0bq0aNGpKko0ePys3NTX5+fg5trxyTo0ePZjtmmY/l1iY5OVmpqalFcuw///xz/fbbbxo7dmyWxxi37P3999+aMmWKKleurMWLF6tv374aOHCgZs6cKel/y53b8hw9elRBQUEOj7u6uqpMmTKWjG1hHDdJevHFF9W1a1dFR0erZMmSqlOnjgYPHqxu3bpJYuzyojCNUV5qAfKCn3REodWvXz9t3bpVa9ascXYphd7Bgwc1aNAgLVmyRB4eHs4up8jIyMhQvXr1NGbMGElSnTp1tHXrVn3wwQeKj493cnWF25dffqnZs2fr008/VfXq1bVlyxYNHjxYYWFhjB1wC2OLZSEWEBAgFxeXLGfuHjt2TCEhIU6qqmD0799f3333nVasWKHy5cvbp4eEhOjixYs6c+aMQ/srxyQkJCTbMct8LLc2Pj4+8vT0LHJjv2nTJh0/flx33HGHXF1d5erqqp9++knvvvuuXF1dFRwczLhlIzQ0VDExMQ7TqlWrpoSEBEn/W+7clickJETHjx93ePzy5cs6deqUJWNbGMdNkoYOHWrfalmzZk099thjevbZZ+1bzBm7aytMY5SXWoC8IFgWYm5ubqpbt66WLVtmn5aRkaFly5bprrvucmJl+ccYo/79++vrr7/W8uXLFRUV5fB43bp1VbJkSYcx2blzpxISEuxjctddd+nPP/90+DBesmSJfHx87CHirrvucugjs01mH0Vt7Fu2bKk///xTW7Zssd/q1aunbt262f/PuGXVuHHjLJez2rVrlypUqCBJioqKUkhIiMPyJCcna926dQ7jdubMGW3atMneZvny5crIyFDDhg3tbVatWqVLly7Z2yxZskRVq1aVv7+/vU1uY1vYpKSkqEQJx68QFxcXZWRkSGLs8qIwjVFeagHyxNlnDyF3n3/+uXF3dzczZsww27ZtM7179zZ+fn4OZ+4WJ3379jW+vr5m5cqV5siRI/ZbSkqKvc3TTz9tIiIizPLly83GjRvNXXfdZe666y7745mXzWnTpo3ZsmWLWbRokQkMDMz2sjlDhw4127dvN5MnT872sjlFeeyvPCvcGMYtO+vXrzeurq7m9ddfN7t37zazZ882Xl5e5pNPPrG3GTdunPHz8zPffPON+eOPP8yDDz6Y7eVg6tSpY9atW2fWrFljKleu7HA5mDNnzpjg4GDz2GOPma1bt5rPP//ceHl5ZbkcjKurq3nrrbfM9u3bzciRIwvNJXOyEx8fb8qVK2e/3NBXX31lAgICzAsvvGBvw9j9c6WGzZs3m82bNxtJZsKECWbz5s3mwIEDxpjCNUZ5qQW4FoJlEfDee++ZiIgI4+bmZho0aGB+/fVXZ5eUbyRle5s+fbq9TWpqqnnmmWeMv7+/8fLyMg899JA5cuSIQz/79+83cXFxxtPT0wQEBJjnnnvOXLp0yaHNihUrTO3atY2bm5u57bbbHJ4jU1Ee+6uDJeOWvW+//dbUqFHDuLu7m+joaDN16lSHxzMyMsyIESNMcHCwcXd3Ny1btjQ7d+50aHPy5EnzyCOPGG9vb+Pj42N69uxpzp4969Dm999/N02aNDHu7u6mXLlyZty4cVlq+fLLL02VKlWMm5ubqV69uvn++++tX2CLJCcnm0GDBpmIiAjj4eFhbrvtNvPSSy85XPKGsftnfcnuMy0+Pt4YU7jGKC+1ANdiM+aKn0kAAAAAbhDHWAIAAMASBEsAAABYgmAJAAAASxAsAQAAYAmCJQAAACxBsAQAAIAlCJYAAACwBMESQKHSo0cPtW/f3tll3LDIyEhNnDjR2WUAgFNwgXQABcZms+X6+MiRI/Xss8/KGCM/P7+CKcpiJ06cUKlSpeTl5SXpn2X++uuvi3RYBoC8cnV2AQBuHUeOHLH//4svvtArr7yinTt32qd5e3vL29vbGaVZJjAw0NklAIDTsCscQIEJCQmx33x9fWWz2RymeXt7Z9kV3rx5cw0YMECDBw+Wv7+/goOD9dFHH+n8+fPq2bOnSpcurUqVKumHH35weK6tW7cqLi5O3t7eCg4O1mOPPabExMQcaxs1apRq167tMG3ixImKjIy038+s7a233lJoaKjKli2rfv366dKlS/Y2V+4Kz5z3oYceks1ms9///fff1aJFC5UuXVo+Pj6qW7euNm7cmOdxnDFjhvz8/PTdd9+patWq8vLyUseOHZWSkqKZM2cqMjJS/v7+GjhwoNLT0/PcLwDcLIIlgEJv5syZCggI0Pr16zVgwAD17dtXnTp1UqNGjfTbb7+pTZs2euyxx5SSkiJJOnPmjO655x7VqVNHGzdu1KJFi3Ts2DF17tz5pmtZsWKF9u7dqxUrVmjmzJmaMWOGZsyYkW3bDRs2SJKmT5+uI0eO2O9369ZN5cuX14YNG7Rp0ya9+OKLKlmypH0+m82WY5+ZUlJS9O677+rzzz/XokWLtHLlSj300ENauHChFi5cqFmzZunDDz/U3Llzb3qZASCv2BUOoNCrVauWXn75ZUnS8OHDNW7cOAUEBKhXr16SpFdeeUVTpkzRH3/8oTvvvFOTJk1SnTp1NGbMGHsf06ZNU3h4uHbt2qUqVarccC3+/v6aNGmSXFxcFB0drbZt22rZsmX2Wq6UuVvcz89PISEh9ukJCQkaOnSooqOjJUmVK1d2mK9q1ary9fXNtY5Lly5pypQpqlixoiSpY8eOmjVrlo4dOyZvb2/FxMSoRYsWWrFihbp06XLDywsA14NgCaDQu/322+3/d3FxUdmyZVWzZk37tODgYEnS8ePHJf2zq3nFihXZHq+5d+/emwqW1atXl4uLi/1+aGio/vzzz+vqY8iQIXrqqac0a9YstWrVSp06dbIHREnasWPHNfvw8vJymCc4OFiRkZEOyxwcHGwfEwAoCOwKB1DoXbmbWPpnV/HVu44lKSMjQ5J07tw5tWvXTlu2bHG47d69W3fffXe2z1GiRAldfZGMK4+dzK2WzOfNq1GjRumvv/5S27ZttXz5csXExOjrr7++rj6uNSY3WhsA3Ay2WAIodu644w7NmzdPkZGRcnXN28dcYGCgjh49KmOMPahu2bLlpmspWbJktifQVKlSRVWqVNGzzz6rRx55RNOnT9dDDz10088HAM7EFksAxU6/fv106tQpPfLII9qwYYP27t2rxYsXq2fPnjmeJd28eXOdOHFC48eP1969ezV58uQsZ5rfiMjISC1btkxHjx7V6dOnlZqaqv79+2vlypU6cOCAfv75Z23YsEHVqlWzzxMdHX3dWzABoDAgWAIodsLCwvTzzz8rPT1dbdq0Uc2aNTV48GD5+fmpRInsP/aqVaum999/X5MnT1atWrW0fv16Pf/88zddy9tvv60lS5YoPDxcderUkYuLi06ePKnHH39cVapUUefOnRUXF6fRo0fb59m5c6eSkpJu+rkBoKDxyzsAAACwBFssAQAAYAmCJQAAACxBsAQAAIAlCJYAAACwBMESAAAAliBYAgAAwBIESwAAAFiCYAkAAABLECwBAABgCYIlAAAALEGwBAAAgCUIlgAAALDE/wd8boG1fILylgAAAABJRU5ErkJggg=="
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ]
  },
  {
   "cell_type": "code",
   "source": [
    "stream.timedelta_hist(\n",
    "        event_pair=('product1', 'cart'),\n",
    "        timedelta_unit='m',\n",
    "        adjacent_events_only=False,\n",
    "        upper_cutoff_quantile=0.1\n",
    "    );"
   ],
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 449
    },
    "id": "3OPKdBOrKcc_",
    "executionInfo": {
     "status": "ok",
     "timestamp": 1682539468246,
     "user_tz": -180,
     "elapsed": 496,
     "user": {
      "displayName": "Anatoliy Zaykovskiy",
      "userId": "11710160701524337708"
     }
    },
    "outputId": "cbdc983f-e548-420d-c23e-bad68fe471a3"
   },
   "execution_count": 26,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 600x450 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ]
  },
  {
   "cell_type": "code",
   "source": [
    "stream_with_synthetic\\\n",
    "    .timedelta_hist(\n",
    "        event_pair=('product1', 'cart'),\n",
    "        timedelta_unit='m',\n",
    "        adjacent_events_only=False,\n",
    "        weight_col='session_id'\n",
    "    );"
   ],
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 449
    },
    "id": "Cq6NAvPEYGw_",
    "executionInfo": {
     "status": "ok",
     "timestamp": 1682539470356,
     "user_tz": -180,
     "elapsed": 491,
     "user": {
      "displayName": "Anatoliy Zaykovskiy",
      "userId": "11710160701524337708"
     }
    },
    "outputId": "da06bb64-3cd8-43eb-ef45-c90b3ffe181d"
   },
   "execution_count": 27,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 600x450 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ]
  },
  {
   "cell_type": "code",
   "source": [
    "stream\\\n",
    "    .timedelta_hist(\n",
    "        event_pair=('main', 'catalog'),\n",
    "        timedelta_unit='m',\n",
    "        adjacent_events_only=False,\n",
    "        weight_col='user_id',\n",
    "        time_agg='mean'\n",
    "    );"
   ],
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 449
    },
    "id": "NxJnm-HMYYfX",
    "executionInfo": {
     "status": "ok",
     "timestamp": 1682540317182,
     "user_tz": -180,
     "elapsed": 8,
     "user": {
      "displayName": "Anatoliy Zaykovskiy",
      "userId": "11710160701524337708"
     }
    },
    "outputId": "5e51583a-da64-4c64-bf09-eb73285e4157"
   },
   "execution_count": 28,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 600x450 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ]
  },
  {
   "cell_type": "markdown",
   "source": [
    "#### Eventstream global events\n"
   ],
   "metadata": {
    "id": "U-fHCaabYqu-"
   }
  },
  {
   "cell_type": "code",
   "source": [
    "stream_with_synthetic\\\n",
    "    .timedelta_hist(\n",
    "        event_pair=('eventstream_start', 'path_end'),\n",
    "        timedelta_unit='h',\n",
    "        adjacent_events_only=False\n",
    "    );"
   ],
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 449
    },
    "id": "DZsJ-_deZlGL",
    "executionInfo": {
     "status": "ok",
     "timestamp": 1682540766203,
     "user_tz": -180,
     "elapsed": 880,
     "user": {
      "displayName": "Anatoliy Zaykovskiy",
      "userId": "11710160701524337708"
     }
    },
    "outputId": "53303527-e812-4465-a6f3-90ef4257227a"
   },
   "execution_count": 29,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 600x450 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ]
  },
  {
   "cell_type": "markdown",
   "source": [
    "### Events intensity"
   ],
   "metadata": {
    "id": "eT5TUd5O5Pp_"
   }
  },
  {
   "cell_type": "code",
   "source": [
    "stream.event_timestamp_hist();"
   ],
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 429
    },
    "id": "5hURSECJ8ixm",
    "executionInfo": {
     "status": "ok",
     "timestamp": 1682540857450,
     "user_tz": -180,
     "elapsed": 895,
     "user": {
      "displayName": "Anatoliy Zaykovskiy",
      "userId": "11710160701524337708"
     }
    },
    "outputId": "97d3a3bc-4f98-47a5-fd2b-fc81a96b81e6"
   },
   "execution_count": 30,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 600x450 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ]
  },
  {
   "cell_type": "code",
   "source": [
    "stream\\\n",
    "    .add_start_end_events()\\\n",
    "    .event_timestamp_hist(event_list=['path_start']);"
   ],
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 484
    },
    "id": "L5cLS-Z08qqX",
    "executionInfo": {
     "status": "ok",
     "timestamp": 1682540882764,
     "user_tz": -180,
     "elapsed": 1371,
     "user": {
      "displayName": "Anatoliy Zaykovskiy",
      "userId": "11710160701524337708"
     }
    },
    "outputId": "321e2187-b465-4cf6-a6f7-7399c236ba01"
   },
   "execution_count": 31,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 600x450 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "is_executing": true
    }
   }
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.6"
  },
  "colab": {
   "provenance": [
    {
     "file_id": "1Gcj_hfBODZj4noEHMXl5O-ij4gcs5qzn",
     "timestamp": 1671629341415
    }
   ]
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}