mw-lifecycle-analysis/text_analysis/case1/031025_phab_comments.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "ba9e5acd-e17d-4318-9272-04c9f6706186",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd \n",
    "import spacy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "e4f0b3f0-5255-46f1-822f-e455087ba315",
   "metadata": {},
   "outputs": [],
   "source": [
    "phab_path = \"/mmfs1/gscratch/comdata/users/mjilg/mw-repo-lifecycles/case1/0312_resolved_ve_phab_comments.csv\"\n",
    "phab_df = pd.read_csv(phab_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "d449164e-1d28-4580-9eb1-f0f69978f114",
   "metadata": {},
   "outputs": [],
   "source": [
    "#find gerrit phab PHID: PHID-USER-idceizaw6elwiwm5xshb\n",
    "phab_df['isGerrit'] = phab_df['AuthorPHID'] == 'PHID-USER-idceizaw6elwiwm5xshb'\n",
    "#cleaning df\n",
    "phab_df['id'] = phab_df.index + 1\n",
    "#may have to build out the reply_to column \n",
    "phab_df['reply_to'] = phab_df.groupby('TaskPHID')['id'].shift()\n",
    "phab_df['reply_to'] = phab_df['reply_to'].where(pd.notnull(phab_df['reply_to']), None)\n",
    "\n",
    "phab_df = phab_df.rename(columns={\n",
    "    'AuthorPHID': 'speaker',\n",
    "    'TaskPHID': 'conversation_id',\n",
    "    'WMFaffil':'meta.affil',\n",
    "    'isGerrit': 'meta.gerrit'\n",
    "})\n",
    "\n",
    "#  before 9-30-2013 after 11-11-2012\n",
    "phab_df['timestamp'] = pd.to_datetime(phab_df['date_created'], unit='s', origin='unix', utc=True)\n",
    "filtered_phab_df = phab_df[(phab_df['date_created'] < 1380585599) & (phab_df['date_created'] > 1352592000)]\n",
    "\n",
    "#removing headless conversations\n",
    "task_phab_df = filtered_phab_df[filtered_phab_df['comment_type']==\"task_description\"]\n",
    "headed_task_phids = task_phab_df['conversation_id'].unique()\n",
    "filtered_phab_df = filtered_phab_df[filtered_phab_df['conversation_id'].isin(headed_task_phids)]\n",
    "\n",
    "#removing gerrit comments \n",
    "comment_phab_df = filtered_phab_df[filtered_phab_df['meta.gerrit'] != True]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "942344db-c8f5-4ed6-a757-c97f8454f18b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Unique conversation_ids: 1937\n",
      "Unique ids: 7987\n",
      "Unique speakers: 217\n"
     ]
    }
   ],
   "source": [
    "unique_conversation_ids = len(comment_phab_df['conversation_id'].unique())\n",
    "unique_ids = len(comment_phab_df['id'].unique())\n",
    "unique_speakers = len(comment_phab_df['speaker'].unique())\n",
    "\n",
    "print(f\"Unique conversation_ids: {unique_conversation_ids}\")\n",
    "print(f\"Unique ids: {unique_ids}\")\n",
    "print(f\"Unique speakers: {unique_speakers}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "d226d781-b002-4842-a3ae-92d4851a5878",
   "metadata": {},
   "outputs": [],
   "source": [
    "import re\n",
    "\n",
    "def preprocess_text(text):\n",
    "    text = str(text)\n",
    "    text = text.replace('*', ' ')\n",
    "    text = text.replace('-', ' ')\n",
    "    text = re.sub(r'http\\S+', '', text)\n",
    "    return text"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "3ae40d24-bbe8-49c3-a3a9-70bde1b4d559",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_43056/3649688126.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  comment_phab_df['processed_text'] = comment_phab_df['text'].apply(preprocess_text)\n"
     ]
    }
   ],
   "source": [
    "comment_phab_df['processed_text'] = comment_phab_df['text'].apply(preprocess_text)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "b8eddf40-1fe2-4fce-be74-b32552b40c57",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_43056/1316816771.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  comment_phab_df['processed_resolved_text'] = comment_phab_df['resolved_text'].apply(preprocess_text)\n"
     ]
    }
   ],
   "source": [
    "comment_phab_df['processed_resolved_text'] = comment_phab_df['resolved_text'].apply(preprocess_text)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "a8469b16-4ae6-4b06-bf1b-1f2f6c736cab",
   "metadata": {},
   "outputs": [],
   "source": [
    "nlp = spacy.load(\"en_core_web_sm\")\n",
    "\n",
    "def extract_dependency_tree(text):\n",
    "    doc = nlp(text)\n",
    "    dependency_trees = []\n",
    "    \n",
    "    for sentence in doc.sents:\n",
    "        for token in sentence:\n",
    "            token_info = (\n",
    "                token.text, \n",
    "                token.lemma_, \n",
    "                token.dep_, \n",
    "                token.head.text, \n",
    "                list(token.ancestors), \n",
    "                list(token.subtree), \n",
    "                list(token.children)\n",
    "            )\n",
    "            dependency_trees.append(token_info)\n",
    "        \n",
    "    return dependency_trees"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "8b9a12f9-71bf-4bc9-bcfd-c73aab4be920",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_43056/2805711855.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  comment_phab_df['dependency_tree'] = comment_phab_df['processed_text'].apply(extract_dependency_tree)\n"
     ]
    }
   ],
   "source": [
    "comment_phab_df['dependency_tree'] = comment_phab_df['processed_text'].apply(extract_dependency_tree)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "337a528a-5667-4e1f-ac9a-37caabc03a18",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_43056/2117289791.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  comment_phab_df['resolved_dependency_tree'] = comment_phab_df['processed_resolved_text'].apply(extract_dependency_tree)\n"
     ]
    }
   ],
   "source": [
    "comment_phab_df['resolved_dependency_tree'] = comment_phab_df['processed_resolved_text'].apply(extract_dependency_tree)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "a3f5d40b-f56e-4e31-a7f9-40b7ddb4d2a4",
   "metadata": {},
   "outputs": [],
   "source": [
    "#get VAD scores\n",
    "import numpy as np\n",
    "#https://saifmohammad.com/WebPages/nrc-vad.html\n",
    "column_headings = ['Word', 'Valence', 'Arousal', 'Domination']\n",
    "vad_lexicon = pd.read_csv('NRC-VAD-Lexicon.txt', delimiter='\\t', header=None, names=column_headings)\n",
    "vad_dict = vad_lexicon.set_index('Word').T.to_dict()\n",
    "\n",
    "def vad_scoring(dependency_tree):\n",
    "    valence = []\n",
    "    arousal = []\n",
    "    dominance = []\n",
    "    for token, lemma, dep, head, ancestors, subtree, children in dependency_tree:\n",
    "        if lemma in vad_dict:\n",
    "            valence.append(vad_dict[lemma]['Valence'])\n",
    "            arousal.append(vad_dict[lemma]['Arousal'])\n",
    "            dominance.append(vad_dict[lemma]['Domination'])\n",
    "\n",
    "    # Compute average scores across the comment\n",
    "    avg_valence = np.mean(valence) if valence else 0\n",
    "    avg_arousal = np.mean(arousal) if arousal else 0\n",
    "    avg_dominance = np.mean(dominance) if dominance else 0\n",
    "\n",
    "    return [avg_valence, avg_arousal, avg_dominance]\n",
    "\n",
    "def dominance_prevail(dependency_tree):\n",
    "    dominant_words = 0 \n",
    "    for token, lemma, dep, head, ancestors, subtree, children in dependency_tree:\n",
    "        if lemma in vad_dict:\n",
    "            if vad_dict[lemma]['Domination'] >= 0.75:\n",
    "                dominant_words += 1\n",
    "            if vad_dict[lemma]['Domination'] <= 0.25:\n",
    "                dominant_words += 1\n",
    "    return dominant_words\n",
    "\n",
    "def arousal_prevail(dependency_tree):\n",
    "    arousal_words = 0 \n",
    "    for token, lemma, dep, head, ancestors, subtree, children in dependency_tree:\n",
    "        if lemma in vad_dict:\n",
    "            if vad_dict[lemma]['Arousal'] >= 0.75:\n",
    "                arousal_words += 1\n",
    "            if vad_dict[lemma]['Arousal'] <= 0.25:\n",
    "                arousal_words += 1\n",
    "    return arousal_words\n",
    "\n",
    "def valence_prevail(dependency_tree):\n",
    "    valence_words = 0 \n",
    "    for token, lemma, dep, head, ancestors, subtree, children in dependency_tree:\n",
    "        if lemma in vad_dict:\n",
    "            if vad_dict[lemma]['Valence'] >= 0.75:\n",
    "                valence_words += 1\n",
    "            if vad_dict[lemma]['Valence'] <= 0.25:\n",
    "                valence_words += 1\n",
    "    return valence_words\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "828fb57a-e152-42ef-9c60-660648898532",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_43056/2858732056.py:2: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  comment_phab_df['avg_vad_scores'] = comment_phab_df['dependency_tree'].apply(vad_scoring)\n",
      "/tmp/ipykernel_43056/2858732056.py:3: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  comment_phab_df['dominant_wc'] = comment_phab_df['dependency_tree'].apply(dominance_prevail)\n",
      "/tmp/ipykernel_43056/2858732056.py:4: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  comment_phab_df['arousal_wc'] = comment_phab_df['dependency_tree'].apply(arousal_prevail)\n",
      "/tmp/ipykernel_43056/2858732056.py:5: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  comment_phab_df['valence_wc'] = comment_phab_df['dependency_tree'].apply(valence_prevail)\n"
     ]
    }
   ],
   "source": [
    "#establishing per-comment VAD scores \n",
    "comment_phab_df['avg_vad_scores'] = comment_phab_df['dependency_tree'].apply(vad_scoring)\n",
    "comment_phab_df['dominant_wc'] = comment_phab_df['dependency_tree'].apply(dominance_prevail)\n",
    "comment_phab_df['arousal_wc'] = comment_phab_df['dependency_tree'].apply(arousal_prevail)\n",
    "comment_phab_df['valence_wc'] = comment_phab_df['dependency_tree'].apply(valence_prevail)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "27e47f6f-0257-4b70-b222-e91ef888c900",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_43056/335308388.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  comment_phab_df[['average_v_score', 'average_a_score', 'average_d_score']] = pd.DataFrame(comment_phab_df['avg_vad_scores'].tolist(), index=comment_phab_df.index)\n",
      "/tmp/ipykernel_43056/335308388.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  comment_phab_df[['average_v_score', 'average_a_score', 'average_d_score']] = pd.DataFrame(comment_phab_df['avg_vad_scores'].tolist(), index=comment_phab_df.index)\n",
      "/tmp/ipykernel_43056/335308388.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  comment_phab_df[['average_v_score', 'average_a_score', 'average_d_score']] = pd.DataFrame(comment_phab_df['avg_vad_scores'].tolist(), index=comment_phab_df.index)\n"
     ]
    }
   ],
   "source": [
    "comment_phab_df[['average_v_score', 'average_a_score', 'average_d_score']] = pd.DataFrame(comment_phab_df['avg_vad_scores'].tolist(), index=comment_phab_df.index)\n",
    "comment_phab_df = comment_phab_df.drop(columns=['avg_vad_scores'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "184ccbe6-0a7a-41b8-9b02-bc439ff975d0",
   "metadata": {},
   "outputs": [],
   "source": [
    "# expand the dependency parser \n",
    "\n",
    "#pattern = r'\\b(ve|VE|visualeditor|VisualEditor)\\b'\n",
    "#pattern = r'\\b(WMF|Foundation)\\b'\n",
    "#pattern = r'\\b(bots|scripts|gadgets)\\b'\n",
    "\n",
    "dependency_relations = []\n",
    "resolved_dependency_relations = []\n",
    "\n",
    "for index, row in comment_phab_df.iterrows():\n",
    "    text = row['text']\n",
    "    timestamp = row['timestamp']\n",
    "    comment_id = row['id']\n",
    "    conversation_id = row['conversation_id']\n",
    "    WMFaffil = row['meta.affil']\n",
    "    \n",
    "    for token, lemma, dep, head, ancestors, subtree, children in row['dependency_tree']:\n",
    "        dependency_relations.append({\n",
    "            'comment_id': comment_id,\n",
    "            'timestamp': timestamp,\n",
    "            'wmfAffil':WMFaffil,\n",
    "            'token': token,\n",
    "            'dependency': dep,\n",
    "            'head': head,\n",
    "            'depth': len(list(ancestors)), \n",
    "            'children': len(list(children)) \n",
    "        })\n",
    "    for token, lemma, dep, head, ancestors, subtree, children in row['resolved_dependency_tree']:\n",
    "        resolved_dependency_relations.append({\n",
    "            'comment_id': comment_id,\n",
    "            'timestamp': timestamp,\n",
    "            'wmfAffil':WMFaffil,\n",
    "            'token': token,\n",
    "            'dependency': dep,\n",
    "            'head': head,\n",
    "            'depth': len(list(ancestors)), \n",
    "            'children': len(list(children)) \n",
    "        })\n",
    "\n",
    "resolved_dependency_relations_df = pd.DataFrame(resolved_dependency_relations)            \n",
    "dependency_relations_df = pd.DataFrame(dependency_relations)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "82498686-14f4-40c8-9e33-27b31f115b47",
   "metadata": {},
   "outputs": [],
   "source": [
    "#now analysis/plotting \n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from matplotlib.gridspec import GridSpec"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "3e5dfff1-3882-4e75-867e-1a42badb346f",
   "metadata": {},
   "outputs": [],
   "source": [
    "given_date = pd.Timestamp(\"2013-07-01\").tz_localize(None)\n",
    "task_phab_df['timestamp'] = pd.to_datetime(task_phab_df['timestamp'], unit='s').dt.tz_localize(None)\n",
    "task_phab_df = task_phab_df[(task_phab_df['date_created'] < 1380585599) & (task_phab_df['date_created'] > 1352592000)]\n",
    "task_phab_df['week_bin'] = ((task_phab_df['timestamp'] - given_date).dt.days // 7)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "c7bc1479-620e-4da7-8fa0-b7c554e8f2d9",
   "metadata": {},
   "outputs": [],
   "source": [
    "task_phab_df\n",
    "task_phab_df.to_csv(\"/mmfs1/gscratch/comdata/users/mjilg/mw-repo-lifecycles/case1/phab_tasks.csv\", index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "82cd9dde-0d14-4de5-8482-5a39de8d2869",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10, 6))\n",
    "#task_phab_df = phab_df[phab_df['comment_type']==\"task_description\"]\n",
    "task_phab_df['first_comment'] = task_phab_df.groupby('speaker')['timestamp'].rank(method='first') <= 5\n",
    "#task_phab_df = task_phab_df[(task_phab_df['date_created'] < 1380585599) & (task_phab_df['date_created'] > 1352592000)]\n",
    "\n",
    "#task_phab_df['week'] = task_phab_df['timestamp'].dt.to_period('W').dt.start_time\n",
    "#unique_taskPHIDs = task_phab_df.groupby('week')['conversation_id'].nunique()\n",
    "\n",
    "wmf_task_phab_df = task_phab_df[(task_phab_df['meta.affil'] == True)]\n",
    "wmf_tasks = wmf_task_phab_df.groupby('week_bin')['conversation_id'].nunique()\n",
    "\n",
    "other_task_phab_df = task_phab_df[(task_phab_df['meta.affil'] != True)]\n",
    "other_tasks = other_task_phab_df.groupby('week_bin')['conversation_id'].nunique()\n",
    "\n",
    "'''\n",
    "task_phab_df['week'] = task_phab_df['timestamp'].dt.to_period('W').dt.start_time\n",
    "unique_taskPHIDs = task_phab_df.groupby('week')['conversation_id'].nunique()\n",
    "\n",
    "wmf_task_phab_df = task_phab_df[(task_phab_df['meta.affil'] == True)]\n",
    "wmf_tasks = wmf_task_phab_df.groupby('week')['conversation_id'].nunique()\n",
    "\n",
    "other_task_phab_df = task_phab_df[(task_phab_df['meta.affil'] != True)]\n",
    "other_tasks = other_task_phab_df.groupby('week')['conversation_id'].nunique()\n",
    "\n",
    "unaff_new_tasks_phab_df = task_phab_df[(task_phab_df['first_comment'] == True) & (task_phab_df['meta.affil'] != True)]\n",
    "unaff_new_tasks = unaff_new_tasks_phab_df.groupby('week')['conversation_id'].nunique()\n",
    "\n",
    "aff_new_tasks_phab_df = task_phab_df[(task_phab_df['first_comment'] == True) & (task_phab_df['meta.affil'] == True)]\n",
    "aff_new_tasks = aff_new_tasks_phab_df.groupby('week')['conversation_id'].nunique()\n",
    "\n",
    "sns.lineplot(x=unique_taskPHIDs.index, y=unique_taskPHIDs.values, color='black', label='Total', marker='o')\n",
    "sns.lineplot(x=wmf_tasks.index, y=wmf_tasks.values, color='#c7756a', label='WMF-affiliated authors', marker='o')\n",
    "sns.lineplot(x=other_tasks.index, y=other_tasks.values, color='#5da2d8', label='Nonaffiliated authors', marker='o')\n",
    "#sns.lineplot(x=aff_new_tasks.index, y=aff_new_tasks.values, color='#c7756a',linestyle=\"dotted\", label=\"WMF-affiliated new authors\", marker='x')\n",
    "#sns.lineplot(x=unaff_new_tasks.index, y=unaff_new_tasks.values, color='#5da2d8', linestyle=\"dotted\", label=\"Nonaffiliated new authors\", marker='x')\n",
    "'''\n",
    "\n",
    "sns.barplot(x=other_tasks.index, y=other_tasks.values, color='#5da2d8', label='Nonaffiliated authors')\n",
    "sns.barplot(x=wmf_tasks.index, y=wmf_tasks.values, color='#c7756a', label='WMF-affiliated authors')\n",
    "\n",
    "plt.title('New Phabricator Tasks Indexed with \"VisualEditor\"')\n",
    "plt.xlabel('Timestamp')\n",
    "plt.ylabel('Unique taskPHIDs')\n",
    "plt.xticks(rotation=45)\n",
    "plt.grid(True)\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "\n",
    "#plt.savefig('042125_new_tasks_fig.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "9a9b08a7-6c95-4971-b259-8e713c58fbe7",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_5608/146435357.py:4: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  unaff_tasks_phab_df['speakers_task'] = unaff_tasks_phab_df.groupby('speaker')['timestamp'].rank(method='first').astype(int)\n",
      "/tmp/ipykernel_5608/146435357.py:17: UserWarning: Converting to PeriodArray/Index representation will drop timezone information.\n",
      "  unaff_tasks_phab_df['week'] = unaff_tasks_phab_df['timestamp'].dt.to_period('W').dt.start_time\n",
      "/tmp/ipykernel_5608/146435357.py:18: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  weekly_breakdown = unaff_tasks_phab_df.groupby(['week', 'task_bins']).size().unstack(fill_value=0)\n",
      "/tmp/ipykernel_5608/146435357.py:20: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  speaker_breakdown = unaff_tasks_phab_df.groupby(['week', 'task_bins']).nunique()['speaker'].unstack(fill_value=0)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "task_phab_df = phab_df[phab_df['comment_type'] == \"task_description\"]\n",
    "unaff_tasks_phab_df = task_phab_df[task_phab_df['meta.affil'] != True]\n",
    "# Rank speaker's task values within each group\n",
    "unaff_tasks_phab_df['speakers_task'] = unaff_tasks_phab_df.groupby('speaker')['timestamp'].rank(method='first').astype(int)\n",
    "\n",
    "# Filter dates 06-06-2013 to 09-30-2013\n",
    "unaff_tasks_phab_df = unaff_tasks_phab_df[(unaff_tasks_phab_df['date_created'] < 1380585599) & (unaff_tasks_phab_df['date_created'] > 1370476800)]\n",
    "# Bin the speakers based on the number of tasks they created\n",
    "bins = [0, 6, 26, 51, float('inf')]\n",
    "labels = ['0-5', '6-25', '26-50', '51+']\n",
    "min_speakers_task = unaff_tasks_phab_df.groupby('speaker')['speakers_task'].min().reset_index()\n",
    "min_speakers_task = min_speakers_task.rename(columns={'speakers_task': 'min_speakers_task'})\n",
    "unaff_tasks_phab_df = unaff_tasks_phab_df.merge(min_speakers_task, on='speaker', how='left')\n",
    "unaff_tasks_phab_df['task_bins'] = pd.cut(unaff_tasks_phab_df['min_speakers_task'], bins=bins, labels=labels, right=False)\n",
    "\n",
    "# Calculate the weekly breakdown of binned speakers_task values\n",
    "unaff_tasks_phab_df['week'] = unaff_tasks_phab_df['timestamp'].dt.to_period('W').dt.start_time\n",
    "weekly_breakdown = unaff_tasks_phab_df.groupby(['week', 'task_bins']).size().unstack(fill_value=0)\n",
    "\n",
    "speaker_breakdown = unaff_tasks_phab_df.groupby(['week', 'task_bins']).nunique()['speaker'].unstack(fill_value=0)\n",
    "\n",
    "# Reshape the DataFrame for use with Seaborn\n",
    "weekly_breakdown = weekly_breakdown.reset_index().melt(id_vars='week', value_vars=labels, var_name='task_bins', value_name='count')\n",
    "speaker_breakdown = speaker_breakdown.reset_index().melt(id_vars='week', value_vars=labels, var_name='task_bins', value_name='speakers')\n",
    "\n",
    "# Plot the stacked bar plot using Seaborn\n",
    "plt.figure(figsize=(12, 8))\n",
    "sns.barplot(data=weekly_breakdown, x='week', y='count', hue='task_bins', palette='colorblind')\n",
    "#sns.barplot(data=speaker_breakdown, x='week', y='speakers', hue='task_bins', palette='colorblind')\n",
    "plt.title(\"06-06-2013 to 09-30-2013 Weekly Unaffiliated Task Creation by Contirbutor Tenure\")\n",
    "plt.xlabel('Week')\n",
    "plt.ylabel('Tasks')\n",
    "plt.legend(title=\"Contributor had created # tasks by 06-06-2013:\")\n",
    "plt.xticks(rotation=45)\n",
    "plt.tight_layout()\n",
    "#plt.show()\n",
    "\n",
    "plt.savefig('042125_weekly_tasks_by_history.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "b7cfad77-d48a-4708-91f3-89ae1179b90c",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_5608/1399682200.py:27: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  comment_counts = affective_comment_phab_df.groupby('date_group').size()\n",
      "/tmp/ipykernel_5608/1399682200.py:28: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  speaker_counts = affective_comment_phab_df.groupby('date_group')['speaker'].nunique()\n",
      "/tmp/ipykernel_5608/1399682200.py:35: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  comment_counts_engaged = affective_comment_phab_df.groupby(['date_group', 'est_commenter', 'meta.affil']).size()\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of comments for each date group:\n",
      "date_group\n",
      "Before announcement                              1858\n",
      "After announcement, before opt-out deployment    1403\n",
      "After opt-out deployment                         4726\n",
      "dtype: int64\n",
      "\n",
      "Number of speakers for each date group:\n",
      "date_group\n",
      "Before announcement                              104\n",
      "After announcement, before opt-out deployment     92\n",
      "After opt-out deployment                         184\n",
      "Name: speaker, dtype: int64\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_5608/1399682200.py:36: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  speaker_counts_engaged = affective_comment_phab_df.groupby(['date_group', 'est_commenter', 'meta.affil'])['speaker'].nunique()\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Number of comments for each date group and engaged commenter subgroup:\n",
      "date_group                                     est_commenter  meta.affil\n",
      "Before announcement                            False          False          613\n",
      "                                                              True            84\n",
      "                                               True           False          836\n",
      "                                                              True           325\n",
      "After announcement, before opt-out deployment  False          False          589\n",
      "                                                              True           104\n",
      "                                               True           False          492\n",
      "                                                              True           218\n",
      "After opt-out deployment                       False          False         2512\n",
      "                                                              True           510\n",
      "                                               True           False         1402\n",
      "                                                              True           302\n",
      "dtype: int64\n",
      "\n",
      "Number of speakers for each date group and engaged commenter subgroup:\n",
      "date_group                                     est_commenter  meta.affil\n",
      "Before announcement                            False          False          91\n",
      "                                                              True           25\n",
      "                                               True           False           7\n",
      "                                                              True            7\n",
      "After announcement, before opt-out deployment  False          False          77\n",
      "                                                              True           31\n",
      "                                               True           False           7\n",
      "                                                              True            7\n",
      "After opt-out deployment                       False          False         172\n",
      "                                                              True           52\n",
      "                                               True           False           7\n",
      "                                                              True            7\n",
      "Name: speaker, dtype: int64\n",
      "\n",
      "Number of comments for each engaged commenter subgroup, and WMF affiliation:\n",
      "est_commenter  meta.affil\n",
      "False          False         3714\n",
      "               True           698\n",
      "True           False         2730\n",
      "               True           845\n",
      "dtype: int64\n",
      "\n",
      "Number of speakers for each engaged commenter subgroup, and WMF affiliation:\n",
      "est_commenter  meta.affil\n",
      "False          False         200\n",
      "               True           72\n",
      "True           False           7\n",
      "               True            7\n",
      "Name: speaker, dtype: int64\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "'\\nplot1 = sns.lmplot(data=comment_phab_df, x=\"date_created\", y=\"dominant_wc\", hue=\"date_group\", col=\"meta.affil\", row=\\'new_commenter\\', scatter=False, legend=False, palette=palette)\\nplot1.set_axis_labels(\"Timestamp\", \"Count of Dominance Polarized Words\")\\nplot1.set_titles(row_template=\"Author\\'s 100+ Comment: {row_name}\",col_template=\"WMF Affiliation: {col_name}\")\\nplot1.fig.subplots_adjust(top=0.9)  # Adjust subplots to make room for the title\\nplot1.add_legend(title=\"Comment publication timestamp:\")\\nfig1 = plot1.fig\\n# Plot for arousal_wc\\nplot2 = sns.lmplot(data=comment_phab_df, x=\"date_created\", y=\"arousal_wc\", hue=\"date_group\", col=\"meta.affil\", row=\\'engaged_commenter\\', scatter=False, legend=False, palette=palette)\\nplot2.set_axis_labels(\"Timestamp\", \"Count of Arousal Polarized Words\")\\nplot2.set_titles(row_template=\"Author\\'s 100+ Comment: {row_name}\",col_template=\"WMF Affiliation: {col_name}\")\\nplot2.add_legend(title=\"Comment publication timestamp:\")\\n#plot2.add_legend(title=\"Before/After 07/01/2013 Wide Release\")\\n\\nplot3 = sns.lmplot(data=comment_phab_df, x=\"date_created\", y=\"valence_wc\", hue=\"date_group\", col=\"meta.affil\", row=\\'engaged_commenter\\', scatter=False, legend=False, palette=palette)\\nplot3.set_axis_labels(\"Timestamp\", \"Count of Valence Polarized Words\")\\nplot3.set_titles(row_template=\"Author\\'s 100+ Comment: {row_name}\",col_template=\"WMF Affiliation: {col_name}\")\\nplot3.add_legend(title=\"Comment publication timestamp:\")\\n'"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1577.5x1000 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bins = [\n",
    "    pd.Timestamp('1900-01-01 00:00:01+00:00'),\n",
    "    pd.Timestamp('2013-06-06 00:00:01+00:00'),\n",
    "    pd.Timestamp('2013-07-01 00:00:01+00:00'),\n",
    "    pd.Timestamp('2100-01-01 00:00:01+00:00')\n",
    "]\n",
    "labels = ['Before announcement', 'After announcement, before opt-out deployment', 'After opt-out deployment']\n",
    "\n",
    "#creating variables of interest\n",
    "affective_comment_phab_df = comment_phab_df\n",
    "affective_comment_phab_df['date_group'] = pd.cut(affective_comment_phab_df['timestamp'], bins=bins, labels=labels, right=False)\n",
    "affective_comment_phab_df['speakers_comment'] = affective_comment_phab_df.groupby('speaker')['timestamp'].rank(method='first').astype(int)\n",
    "#all comments prior to june 1 2013\n",
    "subset_comment_phab_df = affective_comment_phab_df[affective_comment_phab_df['date_created'] <= 1370044800]\n",
    "#getting counts \n",
    "comment_counts = subset_comment_phab_df.groupby('speaker')['speakers_comment'].max().reset_index()\n",
    "comment_counts = comment_counts.rename(columns={'speakers_comment': 'pre_june_2013_comments'})\n",
    "#merge back \n",
    "affective_comment_phab_df = affective_comment_phab_df.merge(comment_counts, on='speaker', how='left')\n",
    "affective_comment_phab_df['pre_june_2013_comments'] = affective_comment_phab_df['pre_june_2013_comments'].fillna(0)\n",
    "\n",
    "affective_comment_phab_df['new_commenter'] = affective_comment_phab_df['pre_june_2013_comments'] <= 10\n",
    "affective_comment_phab_df['est_commenter'] = affective_comment_phab_df['pre_june_2013_comments'] > 50\n",
    "\n",
    "palette = ['#31449c', '#4a7c85', '#c5db68']\n",
    "\n",
    "comment_counts = affective_comment_phab_df.groupby('date_group').size()\n",
    "speaker_counts = affective_comment_phab_df.groupby('date_group')['speaker'].nunique()\n",
    "\n",
    "print(\"Number of comments for each date group:\")\n",
    "print(comment_counts)\n",
    "print(\"\\nNumber of speakers for each date group:\")\n",
    "print(speaker_counts)\n",
    "\n",
    "comment_counts_engaged = affective_comment_phab_df.groupby(['date_group', 'est_commenter', 'meta.affil']).size()\n",
    "speaker_counts_engaged = affective_comment_phab_df.groupby(['date_group', 'est_commenter', 'meta.affil'])['speaker'].nunique()\n",
    "\n",
    "print(\"\\nNumber of comments for each date group and engaged commenter subgroup:\")\n",
    "print(comment_counts_engaged)\n",
    "print(\"\\nNumber of speakers for each date group and engaged commenter subgroup:\")\n",
    "print(speaker_counts_engaged)\n",
    "\n",
    "comment_counts_wmf = affective_comment_phab_df.groupby(['est_commenter', 'meta.affil']).size()\n",
    "speaker_counts_wmf = affective_comment_phab_df.groupby(['est_commenter', 'meta.affil'])['speaker'].nunique()\n",
    "\n",
    "print(\"\\nNumber of comments for each engaged commenter subgroup, and WMF affiliation:\")\n",
    "print(comment_counts_wmf)\n",
    "print(\"\\nNumber of speakers for each engaged commenter subgroup, and WMF affiliation:\")\n",
    "print(speaker_counts_wmf)\n",
    "\n",
    "#comment_phab_df['before_after'] = comment_phab_df['timestamp'] > pd.Timestamp('2013-07-01 00:00:01+00:00')\n",
    "#fig, axes = plt.subplots(2, 1, figsize=(10, 12), sharex=True)\n",
    "affective_comment_phab_df['polarized_wc'] = affective_comment_phab_df['dominant_wc'] + affective_comment_phab_df['valence_wc'] + affective_comment_phab_df['arousal_wc'] \n",
    "plot1 = sns.lmplot(data=affective_comment_phab_df, x=\"date_created\", y=\"polarized_wc\", hue=\"date_group\", col=\"meta.affil\", row='est_commenter', scatter=False, legend=False, palette=palette)\n",
    "plot1.set_axis_labels(\"Timestamp\", \"Count of Polarized Words\")\n",
    "plot1.set_titles(row_template=\"Established Author: {row_name}\", col_template=\"WMF Affiliation: {col_name}\")\n",
    "plot1.fig.subplots_adjust(top=0.9)  # Adjust subplots to make room for the title\n",
    "plot1.add_legend(title=\"Comment publication timestamp:\")\n",
    "fig1 = plot1.fig\n",
    "'''\n",
    "plot1 = sns.lmplot(data=comment_phab_df, x=\"date_created\", y=\"dominant_wc\", hue=\"date_group\", col=\"meta.affil\", row='new_commenter', scatter=False, legend=False, palette=palette)\n",
    "plot1.set_axis_labels(\"Timestamp\", \"Count of Dominance Polarized Words\")\n",
    "plot1.set_titles(row_template=\"Author's 100+ Comment: {row_name}\",col_template=\"WMF Affiliation: {col_name}\")\n",
    "plot1.fig.subplots_adjust(top=0.9)  # Adjust subplots to make room for the title\n",
    "plot1.add_legend(title=\"Comment publication timestamp:\")\n",
    "fig1 = plot1.fig\n",
    "# Plot for arousal_wc\n",
    "plot2 = sns.lmplot(data=comment_phab_df, x=\"date_created\", y=\"arousal_wc\", hue=\"date_group\", col=\"meta.affil\", row='engaged_commenter', scatter=False, legend=False, palette=palette)\n",
    "plot2.set_axis_labels(\"Timestamp\", \"Count of Arousal Polarized Words\")\n",
    "plot2.set_titles(row_template=\"Author's 100+ Comment: {row_name}\",col_template=\"WMF Affiliation: {col_name}\")\n",
    "plot2.add_legend(title=\"Comment publication timestamp:\")\n",
    "#plot2.add_legend(title=\"Before/After 07/01/2013 Wide Release\")\n",
    "\n",
    "plot3 = sns.lmplot(data=comment_phab_df, x=\"date_created\", y=\"valence_wc\", hue=\"date_group\", col=\"meta.affil\", row='engaged_commenter', scatter=False, legend=False, palette=palette)\n",
    "plot3.set_axis_labels(\"Timestamp\", \"Count of Valence Polarized Words\")\n",
    "plot3.set_titles(row_template=\"Author's 100+ Comment: {row_name}\",col_template=\"WMF Affiliation: {col_name}\")\n",
    "plot3.add_legend(title=\"Comment publication timestamp:\")\n",
    "'''\n",
    "# Show plots\n",
    "#fig1.savefig('031725_engaged_commenter_D_scoring_fig.png')\n",
    "#plot2.fig.savefig('031725_engaged_commenter_A_scoring_fig.png')\n",
    "#plot3.fig.savefig('031725_engaged_commenter_V_scoring_fig.png')\n",
    "#plt.savefig('031625_engaged_commenter_VAD_scoring_fig.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "5a91a59a-0d1c-48b3-93dd-b9df76ca68e5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1577.5x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set_context(\"talk\", font_scale=0.9)\n",
    "plot2 = sns.lmplot(data=affective_comment_phab_df, x=\"speakers_comment\", y=\"polarized_wc\", hue=\"date_group\", col=\"meta.affil\", scatter=False, legend=False, palette=palette)\n",
    "plot2.set_axis_labels(\"Comment Index in Speaker History\", \"Count of Polarized Words\")\n",
    "plot2.set_titles(col_template=\"WMF Affiliation: {col_name}\")\n",
    "plot2.fig.suptitle(\"Use of Emotional Language in VisualEditor Phabricator Comments\", fontsize=18)\n",
    "\n",
    "plot2.fig.subplots_adjust(top=0.85)  # Adjust subplots to make room for the title\n",
    "\n",
    "#plot2.legend.set_bbox_to_anchor([0.5, 1.05])  # Position legend at the top-center\n",
    "#plot2.legend.set_loc(\"upper center\")  # Center the legend horizontally\n",
    "plot2.add_legend(title=\"Comment published:\")\n",
    "\n",
    "plot2.fig.savefig('c1-050125_affective_language_use-paper.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "d2d67d38-f005-4c94-be3c-39eb6b22686f",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_43056/387535334.py:5: UserWarning: This pattern is interpreted as a regular expression, and has match groups. To actually get the groups, use str.extract.\n",
      "  filtered_dependencies = dependency_relations_df[dependency_relations_df['token'].str.contains(pattern, regex=True)]\n",
      "/tmp/ipykernel_43056/387535334.py:6: UserWarning: This pattern is interpreted as a regular expression, and has match groups. To actually get the groups, use str.extract.\n",
      "  resolved_filtered_dependencies = resolved_dependency_relations_df[resolved_dependency_relations_df['token'].str.contains(pattern, regex=True)]\n",
      "/tmp/ipykernel_43056/387535334.py:21: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  filtered_dependencies['timestamp'] = pd.to_datetime(filtered_dependencies['timestamp'], utc=True)\n",
      "/tmp/ipykernel_43056/387535334.py:22: UserWarning: Converting to PeriodArray/Index representation will drop timezone information.\n",
      "  filtered_dependencies['week'] = filtered_dependencies['timestamp'].dt.to_period('W').dt.start_time\n",
      "/tmp/ipykernel_43056/387535334.py:22: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  filtered_dependencies['week'] = filtered_dependencies['timestamp'].dt.to_period('W').dt.start_time\n",
      "/tmp/ipykernel_43056/387535334.py:43: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  resolved_filtered_dependencies['timestamp'] = pd.to_datetime(resolved_filtered_dependencies['timestamp'], utc=True)\n",
      "/tmp/ipykernel_43056/387535334.py:44: UserWarning: Converting to PeriodArray/Index representation will drop timezone information.\n",
      "  resolved_filtered_dependencies['week'] = resolved_filtered_dependencies['timestamp'].dt.to_period('W').dt.start_time\n",
      "/tmp/ipykernel_43056/387535334.py:44: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  resolved_filtered_dependencies['week'] = resolved_filtered_dependencies['timestamp'].dt.to_period('W').dt.start_time\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#pattern = r'\\b(ve|VE|visualeditor|VisualEditor)\\b'\n",
    "#pattern = r'\\b(WMF|Foundation)\\b'\n",
    "#pattern = r'\\b(contributor|community|volunteer)\\b'\n",
    "pattern = r'\\b(bots|scripts|gadgets)\\b'\n",
    "filtered_dependencies = dependency_relations_df[dependency_relations_df['token'].str.contains(pattern, regex=True)]\n",
    "resolved_filtered_dependencies = resolved_dependency_relations_df[resolved_dependency_relations_df['token'].str.contains(pattern, regex=True)]\n",
    "\n",
    "plt.figure(figsize=(12, 8))\n",
    "gs = GridSpec(2, 1, height_ratios=[6, 6])\n",
    "\n",
    "# Main plot: Token depth by timestamp\n",
    "'''\n",
    "ax0 = plt.subplot(gs[0])\n",
    "sns.scatterplot(data=filtered_dependencies, x='timestamp', y='dependency', hue='wmfAffil', style='dependency', markers=True, s=100, ax=ax0)\n",
    "ax0.set_title('VE Depth by Timestamp w/o URLS')\n",
    "ax0.set_xlabel('')\n",
    "ax0.set_ylabel('Dependency Type')\n",
    "ax0.legend().set_visible(False)\n",
    "'''\n",
    "# Calculate the median depth over time\n",
    "filtered_dependencies['timestamp'] = pd.to_datetime(filtered_dependencies['timestamp'], utc=True)\n",
    "filtered_dependencies['week'] = filtered_dependencies['timestamp'].dt.to_period('W').dt.start_time\n",
    "median_depth = filtered_dependencies.groupby('week')['depth'].median().reset_index()\n",
    "\n",
    "wmf_filtered_dependencies = filtered_dependencies[filtered_dependencies['wmfAffil'] == True]\n",
    "#wmf_median_depth = wmf_filtered_dependencies.groupby('week')['depth'].median().reset_index()\n",
    "\n",
    "other_filtered_dependencies = filtered_dependencies[filtered_dependencies['wmfAffil'] != True]\n",
    "#other_median_depth = other_filtered_dependencies.groupby('week')['depth'].median().reset_index()\n",
    "\n",
    "# Plot the median depth over time\n",
    "ax0 = plt.subplot(gs[0])\n",
    "#sns.lineplot(data=median_depth, x='week', y='depth', ax=ax0, color='black', label='Median Depth', marker='o')\n",
    "sns.scatterplot(data=wmf_filtered_dependencies, x='week', y='depth', ax=ax0, color='#c7756a', label='WMF-affiliated authors', marker='o')\n",
    "#sns.lineplot(data=wmf_median_depth, x='week', y='depth', ax=ax0, color='#c7756a', label='WMF-affiliated authors', marker='x')\n",
    "sns.scatterplot(data=other_filtered_dependencies, x='week', y='depth', ax=ax0, color='#5da2d8', label='Nonaffiliated authors', marker='o')\n",
    "#sns.lineplot(data=other_median_depth, x='week', y='depth', ax=ax0, color='#5da2d8', label='Nonaffiliated authors', marker='x')\n",
    "ax0.set_title(f'Depth of {pattern} in Phabricator Sentence Dependency Trees')\n",
    "ax0.set_ylabel('Median Depth')\n",
    "ax0.set_xlabel('')\n",
    "\n",
    "# Calculate the median depth over time\n",
    "resolved_filtered_dependencies['timestamp'] = pd.to_datetime(resolved_filtered_dependencies['timestamp'], utc=True)\n",
    "resolved_filtered_dependencies['week'] = resolved_filtered_dependencies['timestamp'].dt.to_period('W').dt.start_time\n",
    "resolved_median_depth = resolved_filtered_dependencies.groupby('week')['depth'].median().reset_index()\n",
    "\n",
    "resolved_wmf_filtered_dependencies = resolved_filtered_dependencies[resolved_filtered_dependencies['wmfAffil'] == True]\n",
    "#resolved_wmf_median_depth = resolved_wmf_filtered_dependencies.groupby('week')['depth'].median().reset_index()\n",
    "\n",
    "resolved_other_filtered_dependencies = resolved_filtered_dependencies[resolved_filtered_dependencies['wmfAffil'] != True]\n",
    "#resolved_other_median_depth = resolved_other_filtered_dependencies.groupby('week')['depth'].median().reset_index()\n",
    "\n",
    "# Plot the median depth over time\n",
    "ax1 = plt.subplot(gs[1])\n",
    "#sns.lineplot(data=resolved_median_depth, x='week', y='depth', ax=ax1, color='black', label='Median Depth', marker='o')\n",
    "sns.scatterplot(data=resolved_wmf_filtered_dependencies, x='week', y='depth', ax=ax1, color='#c7756a', label='WMF-affiliated authors', marker='o')\n",
    "#sns.lineplot(data=resolved_wmf_median_depth, x='week', y='depth', ax=ax1, color='#c7756a', label='WMF-affiliated authors', marker='x')\n",
    "sns.scatterplot(data=resolved_other_filtered_dependencies, x='week', y='depth', ax=ax1, color='#5da2d8', label='Nonaffiliated authors', marker='o')\n",
    "#sns.lineplot(data=resolved_other_median_depth, x='week', y='depth', ax=ax1, color='#5da2d8', label='Nonaffiliated authors', marker='x')\n",
    "ax1.set_title(f'Depth of {pattern} in Coreference-resolved Phabricator Sentence Dependency Trees')\n",
    "ax1.set_ylabel('Median Depth')\n",
    "ax1.set_xlabel('')\n",
    "\n",
    "plt.tight_layout()\n"
   ]
  }
 ],
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