{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 2020 Dask User Survey Results\n",
    "\n",
    "This notebook presents the results of the 2020 Dask User Survey,\n",
    "which ran earlier this summer. Thanks to everyone who took the time to fill out the survey!\n",
    "These results help us better understand the Dask community and will guide future development efforts.\n",
    "\n",
    "The raw data, as well as the start of an analysis, can be found in this binder:\n",
    "\n",
    "[![2020 Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/dask/dask-examples/main?urlpath=%2Ftree%2Fsurveys%2F2020.ipynb)\n",
    "\n",
    "Let us know if you find anything in the data.\n",
    "\n",
    "## Highlights\n",
    "\n",
    "We had 240 responses to the survey (slightly fewer than last year, which had about 260). Overall things were similar to last year's. The biggest shift in the community is a stronger demand for better performance."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-27T19:24:27.038817Z",
     "iopub.status.busy": "2022-07-27T19:24:27.038571Z",
     "iopub.status.idle": "2022-07-27T19:24:28.747900Z",
     "shell.execute_reply": "2022-07-27T19:24:28.746153Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_10066/4082487205.py:17: FutureWarning: Using .astype to convert from timezone-aware dtype to timezone-naive dtype is deprecated and will raise in a future version.  Use obj.tz_localize(None) or obj.tz_convert('UTC').tz_localize(None) instead\n",
      "  .assign(Timestamp=lambda df: pd.to_datetime(df['Timestamp'], format=\"%Y/%m/%d %H:%M:%S %p %Z\").astype('datetime64[ns]'))\n",
      "/tmp/ipykernel_10066/4082487205.py:22: FutureWarning: Index.__and__ operating as a set operation is deprecated, in the future this will be a logical operation matching Series.__and__.  Use index.intersection(other) instead.\n",
      "  common = df2019.columns & df2020.columns\n"
     ]
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "import textwrap\n",
    "import re\n",
    "\n",
    "\n",
    "df2019 = (\n",
    "    pd.read_csv(\"data/2019-user-survey-results.csv.gz\", parse_dates=[\"Timestamp\"])\n",
    "      .replace({\"How often do you use Dask?\": \"I use Dask all the time, even when I sleep\"}, \"Every day\")\n",
    ")\n",
    "\n",
    "df2020 = (\n",
    "    pd.read_csv(\"data/2020-user-survey-results.csv.gz\")\n",
    "      .assign(Timestamp=lambda df: pd.to_datetime(df['Timestamp'], format=\"%Y/%m/%d %H:%M:%S %p %Z\").astype('datetime64[ns]'))\n",
    "      .replace({\"How often do you use Dask?\": \"I use Dask all the time, even when I sleep\"}, \"Every day\")\n",
    ")\n",
    "df2020.head()\n",
    "\n",
    "common = df2019.columns & df2020.columns\n",
    "added = df2020.columns.difference(df2019.columns)\n",
    "dropped = df2019.columns.difference(df2020.columns)\n",
    "\n",
    "df = pd.concat([df2019, df2020])\n",
    "df['Year'] = df.Timestamp.dt.year\n",
    "df = df.set_index(['Year', 'Timestamp']).sort_index()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Most of the questions are the same as in 2019. We added a couple questions about deployment and dashboard usage. Let's look at those first.\n",
    "\n",
    "Among respondents who use a Dask package to deploy a cluster (about 53% of respondents), there's a wide spread of methods."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-27T19:24:28.751579Z",
     "iopub.status.busy": "2022-07-27T19:24:28.751373Z",
     "iopub.status.idle": "2022-07-27T19:24:28.896435Z",
     "shell.execute_reply": "2022-07-27T19:24:28.895924Z"
    }
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "k = 'Do you use Dask projects to deploy?'\n",
    "d = df2020['Do you use Dask projects to deploy?'].dropna().str.split(\";\").explode()\n",
    "top = d.value_counts()\n",
    "top = top[top > 10].index\n",
    "sns.countplot(y=k, data=d[d.isin(top)].to_frame(), order=top);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Most people access the dashboard through a web browser. Those not using the dashboard are likely (hopefully) just using Dask on a single machine with the threaded scheduler (though the dashboard works fine on a single machine as well)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-27T19:24:28.900416Z",
     "iopub.status.busy": "2022-07-27T19:24:28.899115Z",
     "iopub.status.idle": "2022-07-27T19:24:29.013971Z",
     "shell.execute_reply": "2022-07-27T19:24:29.013456Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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GZybpI5J+p2SD/Pph3cx+Zcefs6QB+XNeIGl+499Ec2uOpA/kfc3P+1616fM/Of/7mC9pRKvPxMzMel+7v4yPBw6KiLlNy+6WNIs0luS6Vi+MiD9JWpK/ZMYCtwEbAbsCzwPzIuINSY3tb5V0DTAlIi4HyOsGRsQuuQA6EejY7P5N4GsRsX9+zadJf2XvALwOLJR0BvAq8K/APhHxsqRvAMeRvgC7chfpDse/BL4dEc9JGgDcKGkU8ATwEWBERISkoc0vzl+WawITIiIKHK8zo0hnNg0mFXLXAueRxvL8UmmMz1jgU8AJwJiI+Od8/P8AboqIo3K2OyU1Wgt2BUbl9zS8xbGvjIhz877+DfgM6ecPqYVqT2ALUkvSlhHxWtN73xfYCtgFEHCNpHERcZWkjwJfAT4InBgRj0nqTvbRvP3nvB6wUUS8L79+aPMbkTSIdGPID0TEA5IuAr4E/E/e5NmI2FHSl4GvAZ/t+GFI+jzweYCN1ly5xUdmZmbd1a7L5j0dihEAImIesH6BfTdaSRoFyW1N87cWzHdlfp5N+vIr4sY85uU14F5gU9KX+bbADEl3k764Ny24PzVNf1zSXaSunJF5ny8ArwHnSfon4JWm7b8DDI2ILyxHMQLwy4h4NSKeJV22f5eIuBnYUtJ6wCeAKyJiSSev3Rf4Zn7f00gXtxuW1/02Ip7r4tjvy60g80mtZM1db7+IiKUR8SDwMKlw63jsfUmfV6Ow2yqvO5p0S4LXI+LSFsdul72zn/PDwOaSzpD0QdLPptk2wCMR8UCenwyMa1rf5b+3iDgnIsZExJi1B/uWTmZmvaVdC8nLPVzX0BhHsh2py+Zx0pk6L5C6gop4PT+/SbEzgppf0/w6kb58P1FwH812ILWGbEb6q3nniPirpEnAoIhYImkX4APAocA/A42r2M4EdpK0doEv/iUsKxAHdVjXsZhpzF9MKhIOBY5qsV8BH42IhW9ZKP0dxX6Ok8gtZbkFaq8CuZqPfWpE/KST/W4ELAXWl7RSRCztZva3/Zzzz2V74B9IrS8f562fS3Nx2Zme/HszM7Ne0K6FZAtJ13Ty+BWweYF9zwD2B56LiDfzF/JQUjfBbZ1s/yKwejfzF33N7cBukrYEkLSapK3bvSCPb5gIbAD8hnS688vA85LWZ9m4kiHAmhFxHXAsqSuh4TekcS7XSuoq5yJgpzz90Q7rDpQ0SNI6pIKgcaXcSfmYRMQ9eVnHz+R64GjlPjBJO3SRo6PVSdegWZlU/DQ7WNJKSmN+NgcWdlh/PXBU/oyQtJGk9ZQG0V5IGpt0H6n7bLmzK43BWSkiriC1Tu3YYZP7geGNfwfAEcDN7fZpZmZ9o91fgQe2Wfe2gZudmE86u+ZnHZYNyV0PHf0cODcXAUVPJ50HLJE0l/Tl/NfONoqIP+e/7i9tDGIkjSl5oJPNT5f0HWA1UiEzPiLeAOZKmgPcQ+oamJG3X500jmMQ6S/wt1yjJSIuy8XINZL2i4hXm1YPZNlf5ScD50v6P8AdHTLdCVxL6q74bkT8Ke/7aUn3AVc3bTuVZd0cpwLfJY2RmJe/2BeRCsXObCPpiab5r5K+2O8AHiX9/JoLhoWkL/T1gS82jx/J+W6Q9F7gtlxTvAQcDnwRmB4R03POmXlczPJkh9TqcqGWDR7+Voc8r0maAFyWi6KZwNlt9mdmZn1Eyze0wXoqf2nOBI5sat3obLuTgJciorOzd1YjFQk7RsTzZWW1zo3a6F0x5Qtbdr2hWR8bdsL8qiOYtSRpdkS87TpjRe5lY71M0oakcTW3tytGutjHPqQuiDNcjJiZ2YrOA/cqkLtcCl0ELiJOarH8dyw748TMzGyF1mULiaQiA1jNzMzMeqxIC8kkpfu5zARuIQ1GdAelmZmZ9ZouC5KIGKd0L5edSaecXitpSESsXXY4MzMzq4cuCxJJuwN75MdQ0r1tppcby8zMzOqkSJfNzcAs0nUhrsvX5DAzMzPrNUUKknWA3Uj3/JgoaSlwW0R8p9RkZmZmVhtFxpD8TdLDwCbAxqT70/g2p2ZmZtZriowh+QPpEuG/J11me4K7bczMzKw3Femy2arFnVjNzMzMekWRS8dvKelGSQsAJI2S9K8l5zIzM7MaKVKQnEu6a+pigIiYBxxaZigzMzOrlyIFyWoRcWeHZUvKCGNmZmb1VKQgeVbSFkAASPoY8GSpqczMzKxWigxq/QpwDjBC0h+BR4DDS01lZmZmtVLkOiQPA/tIGgysFBEvlh/LzMzM6qRlQSLp8Ij4qaTjOiwHICK+V3I2MzMzq4l2LSSD8/PqfRHEzMzM6qtlQRIRP8mTZ0XEn/soj5mZmdVQkbNsbpV0g6TPSFqr9ERmZmZWO10WJBGxFfCvwEhgtqQpknyWjZmZmfWaIi0kRMSdEXEcsAvwHDC51FRmZmZWK0Xu9rsG8BHS5eK3AK4iFSZmtbbKBiMZdsKsqmOYmb0jFLkw2lzgauCUiLit3DhmZmZWR0UKks0jIkpPYmZmZrVVZFCrixEzMzMrVaFBrWZmZmZlckFiZmZmlStyls2FwNu6bSLiqFISmZmZWe0UGdQ6pWl6EOkU4D+VE8fMzMzqqMuCJCKuaJ6XdCnwu9ISmZmZWe30ZAzJVsCw3g5iZmZm9VVkDMmLpDEkys9PAd8oOZeZmZnVSJEum9X7IoiZmZnVV5FBrUg6ABiXZ6dFxJR225uZmZl1R5djSCSdBhwD3Jsfx0g6texgZmZmVh9FWkj2A0ZHxFIASZOBOcC3ygxmZmZm9VGoywYYCjyXp9csJ4rZiuX+Z+5ntzN2qzpGvzXj6BlVRzCzFUiRguRUYI6kqaQzbcbh1hEzMzPrRUXOsrlU0jRgZ1JB8o2IeKrsYGZmZlYfRa5DcjlwATClMY7EzMzMrDcVuVLr2cBhwIOSTpM0ouRMZmZmVjNdFiQR8buIOAzYEVgE/FbSrZImSFq57IBmZmb2zlfoXjaS1gE+DXyWdMrvD0gFym9LS2ZmZma1UWQMyZXACOBi4B8j4sm86v9JmlVmODMzM6uHIqf9nhkRN3W2IiLG9HIeMzMzq6EiY0g6LUbMzMzMekuhMSRmZmZmZXJBYmZmZpUrdC8bSQeQLhkPcHNE/Kq8SGZmZlY3XbaQSDoVOAa4Nz8m5mVmZmZmvaJIC8mHgdGNy8ZLmky6FolvsGdmZma9ougYkqFN02uWkMPMzMxqrEgLyanAHElTSXf7HYdbR8zMzKwXdVmQRMSlkqYBO5MKkm9ExFNlBzMzM7P6aFmQSNqxw6In8vOGkjaMiLvKi2VmZmZ10q6F5L/z8yBgDDCX1EIyCrgD2L3caGZmZlYXLQe1RsT4iBgPPArsGBFjImInYAfgob4KaGZmZu98Rc6yGRER8xszEbEAGF1aIjMzM6udImfZ3CfpPOCnQACHA/eVmsrMzMxqpUhBMgH4EulqrQC3AD8uLZGZmZnVTpHTfl8Dvp8fZmZmZr3Od/tdwUn6vqRjm+avz11sjfn/lnScpL0kTenmvj8tacMC2w2XtKBbwZe99qUWyydJ+lhP9tnN40+S9DFJq0q6WtKC/Pi7so9tZmbLuCBZ8d0KjAWQtBKwLjCyaf1YYEYP9/1poMuCZEUhaUCb1SsBP4iI9wH/Avx736QyMzModrffzfsiiPXYDHJBQipEFgAvSlpL0qrAe0k3QwQYIulySfdLukSSACSdIGlmbhk4R8nHSNefuUTS3ZLe1XxQSTtJmivpNuArTcuHS5ou6a78aBRLG0i6Je9rgaQ9ml7z73lft0tav+kw++R9PSBp/7ztIEkXSpovaY6k8V0cdy9JUyX9DJif39uZku6VdC2wHkBEvBoRU/NxBwGvLddPxczMuqVIC8kkSX+Q9HNJX5a0XemprLCI+BOwRNIwUmFyG+nCdbuSCop5EfFG3nwH4FhgW2BzYLe8/MyI2Dm3DrwL2D8iLgdmAYdFxOiIeLXDoS8EJkbErh2WPwP8fUTsCBwC/DAv/yRwfUSMBrYH7s7LBwO3R8T2pAHTn2va13BgT9Idp8+WNIhc/ETEdsAngMl5eavjAuwCfDsitgU+AmwDbJePNbZpOyRtAnwPOAkzM+szXRYkETGO9Ff2GcBawLWSnis7mHVLo5WkUZDc1jR/a9N2d0bEExGxlFQQDM/Lx0u6Q9J8YG/e2uXzNpLWBIZGxM150cVNq1cGzs37uoxU/ADMBCZIOgnYLiJezMvfABpjW2Y3ZQL4RUQsjYgHgYeBEaQrBF8MEBH3ky7ct3Wb4zbe9yN5ehxwaUS8mYu5mzq8vR8AJ0fErBbv/fOSZkmatfilxZ1/QGZm1m1dnmUjaXdgj/wYSvrymF5uLOumxjiS7UhdNo+TxkG8AFzQtN3rTdNvAgNz68JZwJiIeDwXDIO6OJ5I16TpzFeBp0mtICuRuz4i4hZJ40itHRdLOj0iLgIWR0RjX2/y1n+THY8R+diFj5u93Ml+WhkFfKHVyog4BzgHYMiwIe32Y2Zm3VCky+Zm4CDSf8J7RcSXI+LSUlNZd80A9geey3/5P0cqHncltZa00yg+npU0BGg+s+VFYPWOL4iIvwHP52IV4LCm1WsCT+ZWmCOAAQCSNgWeiYhzgfOBjjdv7MzBklaStAWpi2khqVvnsLzPrYFheXmnx+3ELcChkgZI2gAY32H9V4HnC2QzM7NeVOTCaOuQxhqMAyZKWgrcFhHfKTWZdcd80tk1P+uwbEhEPNvuhRHxN0nn5u0XkbpWGiaRxm68CuzaYRzJBOACSa8A1zctPwu4QtLBwFSWtU7sBRwvaTHwEnBkgfe1kFQQrw98MSJek3RWzjQfWAJ8OiJez8s7O25HV5G6peYDD+T9N/sSqQXwDczMrM9oWWt5m42k95IGF+5B6hp4LCL2LDmbWb82ZNiQ2P747auO0W/NOLqnZ5ub2TuZpNkRMabj8iJjSP5A+kv198DZwISmszbMzMzMlluRLputcr+8mZmZWSmKDGrdUNJVkp6R9LSkKyRtXHoyMzMzq40iBcmFwDWkS4hvBPwqLzMzMzPrFUUKkndHxIURsSQ/JgHvLjmXmZmZ1UiRguRZSYfn6zYMkHQ48Jeyg5mZmVl9FClIjgI+DjwFPEm6cNZRZYYyMzOzeunyLJuIeAw4oA+ymJmZWU21LEgknUGbe35ExMRSEpmZmVnttGshab7b6cnAiSVnMTMzs5pqWZBExOTGtKRjm+fNzMzMelORQa3Q/nbtZmZmZsulaEFiZmZmVpp2g1pfZFnLyGqSXmisAiIi1ig7nJmZmdVDuzEkq/dlEDMzM6svd9mYmZlZ5VyQmJmZWeVckJiZmVnlXJCYmZlZ5VyQmJmZWeVckJiZmVnlXJCYmZlZ5VyQmJmZWeVckJiZmVnlWl6p1czaG7HeCGYcPaPqGGZm7whuITEzM7PKuSAxMzOzyrkgMTMzs8q5IDEzM7PKuSAxMzOzyrkgMTMzs8opIqrOYLZCkvQisLDqHC2sCzxbdYgW+mu2/poLnK2nnK1nys62aUS8u+NCX4fErOcWRsSYqkN0RtIsZ+ue/poLnK2nnK1nqsrmLhszMzOrnAsSMzMzq5wLErOeO6fqAG04W/f111zgbD3lbD1TSTYPajUzM7PKuYXEzMzMKueCxMzMzCrngsSsmyR9UNJCSQ9J+mbFWTaRNFXSfZLukXRMXr62pN9KejA/r1VhxgGS5kia0p+ySRoq6XJJ9+fPb9d+lO2r+ee5QNKlkgZVlU3SBZKekbSgaVnLLJK+lX83Fkr6hwqynZ5/pvMkXSVpaH/J1rTua5JC0rp9na1VLklH52PfI+k/+zoXuCAx6xZJA4AfAR8CtgU+IWnbCiMtAf4lIt4LvB/4Ss7zTeDGiNgKuDHPV+UY4L6m+f6S7QfAbyJiBLA9KWPl2SRtBEwExkTE+4ABwKEVZpsEfLDDsk6z5H97hwIj82vOyr8zfZntt8D7ImIU8ADwrX6UDUmbAH8PPNa0rC+zvS2XpPHAgcCoiBgJ/FcFuVyQmHXTLsBDEfFwRLwB/Jz0i1yJiHgyIu7K0y+SvlQ3ypkm580mAwdVkU/SxsCHgfOaFleeTdIawDjgfICIeCMi/tYfsmUDgXdJGgisBvyJirJFxC3Acx0Wt8pyIPDziHg9Ih4BHiL9zvRZtoi4ISKW5NnbgY37S7bs+8DXgeYzSvosW4tcXwJOi4jX8zbP9HUucEFi1l0bAY83zT+Rl1VO0nBgB+AOYP2IeBJS0QKsV1Gs/yH957u0aVl/yLY58GfgwtyddJ6kwf0hW0T8kfQX6mPAk8DzEXFDf8jWpFWW/vb7cRTw6zxdeTZJBwB/jIi5HVZVnW1rYA9Jd0i6WdLOVeRyQWLWPepkWeXnzksaAlwBHBsRL1SdB0DS/sAzETG76iydGAjsCPw4InYAXqbabq3/lcdjHAhsBmwIDJZ0eLWpCus3vx+Svk3q0ryksaiTzfosm6TVgG8DJ3S2upNlffm5DQTWInX7Hg/8QpL6OpcLErPueQLYpGl+Y1JzemUkrUwqRi6JiCvz4qclbZDXbwA80+r1JdoNOEDSIlLX1t6SftpPsj0BPBERd+T5y0kFSn/Itg/wSET8OSIWA1cCY/tJtoZWWfrF74ekTwH7A4fFsottVZ1tC1KROTf/TmwM3CXpPf0g2xPAlZHcSWrRXLevc7kgMeuemcBWkjaTtAppwNc1VYXJf8WcD9wXEd9rWnUN8Kk8/Sngl32dLSK+FREbR8Rw0ud0U0Qc3k+yPQU8LmmbvOgDwL39IRupq+b9klbLP98PkMYG9YdsDa2yXAMcKmlVSZsBWwF39mUwSR8EvgEcEBGvNK2qNFtEzI+I9SJieP6deALYMf9brPpzuxrYG0DS1sAqpLv99m2uiPDDDz+68QD2I43e/wPw7Yqz7E5qQp0H3J0f+wHrkM5+eDA/r11xzr2AKXm6X2QDRgOz8md3NanJur9kOxm4H1gAXAysWlU24FLSWJbFpC/Rz7TLQuqW+AOwEPhQBdkeIo17aPw+nN1fsnVYvwhYt6+ztfjMVgF+mv+93QXsXcVn5kvHm5mZWeXcZWNmZmaVc0FiZmZmlXNBYmZmZpVzQWJmZmaVc0FiZmZmlXNBYmZWY5KOzVcRNauUT/s1M6uxfNXQMRHxbNVZrN7cQmJm1s9JOlLSPElzJV0saVNJN+ZlN0oalrebJOljTa97KT/vJWmapMsl3S/pEiUTSffLmSppajXvziwZWHUAMzNrTdJI0tUyd4uIZyWtDUwGLoqIyZKOAn4IHNTFrnYARpLuRTIj7++Hko4DxruFxKrmFhIzs/5tb+DyRsEQEc8BuwI/y+svJt1CoCt3RsQTEbGUdEn14b0f1aznXJCYmfVvoutbvjfWLyH/v55vzLdK0zavN02/iVvIrZ9xQWJm1r/dCHxc0joAucvmVtIdlAEOA36fpxcBO+XpA4GVC+z/RWD13gpr1lOukM3M+rGIuEfSvwM3S3oTmANMBC6QdDzwZ2BC3vxc4JeS7iQVMi8XOMQ5wK8lPRkR43v/HZgV49N+zczMrHLusjEzM7PKuSAxMzOzyrkgMTMzs8q5IDEzM7PKuSAxMzOzyrkgMTMzs8q5IDEzM7PK/X9u6eQxZ9MqswAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "k = \"How do you view Dask's dashboard?\"\n",
    "sns.countplot(y=k, data=df2020[k].dropna().str.split(\";\").explode().to_frame());"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Dask's learning materials are farily similar to last year. The most notable differences are from\n",
    "our survey form providing more options (our [YouTube channel](https://www.youtube.com/channel/UCj9eavqmvwaCyKhIlu2GaoA) and \"Gitter chat\"). Other than that, https://examples.dask.org might be relatively more popular."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-27T19:24:29.018383Z",
     "iopub.status.busy": "2022-07-27T19:24:29.017313Z",
     "iopub.status.idle": "2022-07-27T19:24:29.218621Z",
     "shell.execute_reply": "2022-07-27T19:24:29.217978Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "k = 'What Dask resources have you used for support in the last six months?'\n",
    "\n",
    "resource_map = {\n",
    "    \"Tutorial\": \"Tutorial at tutorial.dask.org\",\n",
    "    \"YouTube\": \"YouTube channel\",\n",
    "    \"gitter\": \"Gitter chat\"\n",
    "}\n",
    "\n",
    "d = df[k].str.split(';').explode().replace(resource_map)\n",
    "top = d.value_counts()[:8].index\n",
    "d = d[d.isin(top)]\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(8, 8))\n",
    "ax = sns.countplot(y=k, hue=\"Year\", data=d.reset_index(), ax=ax);\n",
    "ax.set(ylabel=\"\", title=k);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## How do you use Dask?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Just like last year, we'll look at resource usage grouped by how often they use Dask."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-27T19:24:29.221810Z",
     "iopub.status.busy": "2022-07-27T19:24:29.221289Z",
     "iopub.status.idle": "2022-07-27T19:24:29.617548Z",
     "shell.execute_reply": "2022-07-27T19:24:29.616335Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "resource_palette = (\n",
    "    df['What Dask resources have you used for support in the last six months?'].str.split(\";\").explode().replace(resource_map).replace(re.compile(\"GitHub.*\"), \"GitHub\").value_counts()[:6].index\n",
    ")\n",
    "resource_palette = dict(zip(resource_palette, sns.color_palette(\"Paired\")))\n",
    "\n",
    "usage_order = ['Every day', 'Occasionally', 'Just looking for now']\n",
    "\n",
    "def resource_plot(df, year, ax):\n",
    "    resources = (\n",
    "        df.loc[year, 'What Dask resources have you used for support in the last six months?']\n",
    "          .str.split(\";\")\n",
    "          .explode()\n",
    "          .replace(resource_map)\n",
    "    )\n",
    "    top = resources.value_counts().head(6).index\n",
    "    resources = resources[resources.isin(top)]\n",
    "\n",
    "    m = (\n",
    "        pd.merge(df.loc[year, ['How often do you use Dask?']], resources, left_index=True, right_index=True)\n",
    "          .replace(re.compile(\"GitHub.*\"), \"GitHub\")\n",
    "    )\n",
    "\n",
    "    ax = sns.countplot(hue=\"What Dask resources have you used for support in the last six months?\",\n",
    "                  y='How often do you use Dask?',\n",
    "                  order=usage_order,\n",
    "                  data=m, ax=ax,\n",
    "                  hue_order=list(resource_palette),\n",
    "                  palette=resource_palette)\n",
    "    sns.despine()\n",
    "    return ax\n",
    "\n",
    "fig, axes = plt.subplots(figsize=(20, 10), ncols=2)\n",
    "ax1 = resource_plot(df, 2019, axes[0])\n",
    "ax2 = resource_plot(df, 2020, axes[1])\n",
    "ax1.set_title(\"2019\")\n",
    "ax2.set_title(\"2020\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A few observations\n",
    "\n",
    "\n",
    "* GitHub issues are becoming relatively less popular among moderate and heavy Dask users, which perhaps reflects better documentation or stability (assuming people go to the issue tracker when they can't find the answer in the docs or they hit a bug).\n",
    "* https://examples.dask.org is notably now more popular among occasinal users.\n",
    "* In response to last year's survey, we invested time in making https://tutorial.dask.org better, which we previously felt was lacking. Its usage is still about the same as last year's (pretty popular), so it's unclear whether we should dedicate additional focus there.\n",
    "\n",
    "API usage remains about the same as last year (recall that about 20 fewer people took the survey and people can select multiple, so relative differences are most interesting). We added new choices for RAPIDS, Prefect, and XGBoost, each of which are somewhat popular (in the neighborhood of `dask.Bag`)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-27T19:24:29.620537Z",
     "iopub.status.busy": "2022-07-27T19:24:29.620182Z",
     "iopub.status.idle": "2022-07-27T19:24:29.810325Z",
     "shell.execute_reply": "2022-07-27T19:24:29.809394Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "apis = df['Dask APIs'].str.split(\";\").explode()\n",
    "top = apis.value_counts().loc[lambda x: x > 10]\n",
    "apis = apis[apis.isin(top.index)].reset_index()\n",
    "\n",
    "sns.countplot(y=\"Dask APIs\", hue=\"Year\", data=apis);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Just like last year, about 65% of our users are using Dask on a cluster at least some of the time."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-27T19:24:29.814326Z",
     "iopub.status.busy": "2022-07-27T19:24:29.812914Z",
     "iopub.status.idle": "2022-07-27T19:24:29.824091Z",
     "shell.execute_reply": "2022-07-27T19:24:29.823476Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Year\n",
       "2019    0.654902\n",
       "2020    0.666667\n",
       "Name: Local machine or Cluster?, dtype: float64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Local machine or Cluster?'].dropna().str.contains(\"Cluster\").astype(int).groupby(\"Year\").mean()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "But the majority of respondents *also* use Dask on their laptop.\n",
    "This highlights the importance of Dask scaling down, either for\n",
    "prototyping with a `LocalCluster`, or for out-of-core analysis\n",
    "using `LocalCluster` or one of the single-machine schedulers."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-27T19:24:29.827053Z",
     "iopub.status.busy": "2022-07-27T19:24:29.826736Z",
     "iopub.status.idle": "2022-07-27T19:24:29.986430Z",
     "shell.execute_reply": "2022-07-27T19:24:29.985836Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "order = [\n",
    "    'Personal laptop',\n",
    "    'Large workstation',\n",
    "    'Cluster of 2-10 machines',\n",
    "    'Cluster with 10-100 machines',\n",
    "    'Cluster with 100+ machines'\n",
    "]\n",
    "d = df['Local machine or Cluster?'].str.split(\";\").explode().reset_index()\n",
    "sns.countplot(y=\"Local machine or Cluster?\", data=d, hue=\"Year\", order=order);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Just like last year, most repondents thought that more documentation and examples would be the most valuable improvements to the project.\n",
    "\n",
    "One interesting change comes from looking at \"Which would help you most right now?\" split by API group (`dask.dataframe`, `dask.array`, etc.). Last year showed that \"More examples\" in my field was the most important for all API groups (first table below). But in 2020 there are some differences (second plot below)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-27T19:24:29.990155Z",
     "iopub.status.busy": "2022-07-27T19:24:29.989683Z",
     "iopub.status.idle": "2022-07-27T19:24:30.065900Z",
     "shell.execute_reply": "2022-07-27T19:24:30.065281Z"
    }
   },
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table id=\"T_79a4c\">\n",
       "  <caption>2019 normalized by row. Darker means that a higher proporiton of users of that API prefer that priority.</caption>\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"index_name level0\" >Which would help you most right now?</th>\n",
       "      <th id=\"T_79a4c_level0_col0\" class=\"col_heading level0 col0\" >Bug fixes</th>\n",
       "      <th id=\"T_79a4c_level0_col1\" class=\"col_heading level0 col1\" >More documentation</th>\n",
       "      <th id=\"T_79a4c_level0_col2\" class=\"col_heading level0 col2\" >More examples in my field</th>\n",
       "      <th id=\"T_79a4c_level0_col3\" class=\"col_heading level0 col3\" >New features</th>\n",
       "      <th id=\"T_79a4c_level0_col4\" class=\"col_heading level0 col4\" >Performance improvements</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th class=\"index_name level0\" >Dask APIs</th>\n",
       "      <th class=\"blank col0\" >&nbsp;</th>\n",
       "      <th class=\"blank col1\" >&nbsp;</th>\n",
       "      <th class=\"blank col2\" >&nbsp;</th>\n",
       "      <th class=\"blank col3\" >&nbsp;</th>\n",
       "      <th class=\"blank col4\" >&nbsp;</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th id=\"T_79a4c_level0_row0\" class=\"row_heading level0 row0\" >Array</th>\n",
       "      <td id=\"T_79a4c_row0_col0\" class=\"data row0 col0\" >10</td>\n",
       "      <td id=\"T_79a4c_row0_col1\" class=\"data row0 col1\" >24</td>\n",
       "      <td id=\"T_79a4c_row0_col2\" class=\"data row0 col2\" >62</td>\n",
       "      <td id=\"T_79a4c_row0_col3\" class=\"data row0 col3\" >15</td>\n",
       "      <td id=\"T_79a4c_row0_col4\" class=\"data row0 col4\" >25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_79a4c_level0_row1\" class=\"row_heading level0 row1\" >Bag</th>\n",
       "      <td id=\"T_79a4c_row1_col0\" class=\"data row1 col0\" >3</td>\n",
       "      <td id=\"T_79a4c_row1_col1\" class=\"data row1 col1\" >11</td>\n",
       "      <td id=\"T_79a4c_row1_col2\" class=\"data row1 col2\" >16</td>\n",
       "      <td id=\"T_79a4c_row1_col3\" class=\"data row1 col3\" >10</td>\n",
       "      <td id=\"T_79a4c_row1_col4\" class=\"data row1 col4\" >7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_79a4c_level0_row2\" class=\"row_heading level0 row2\" >DataFrame</th>\n",
       "      <td id=\"T_79a4c_row2_col0\" class=\"data row2 col0\" >16</td>\n",
       "      <td id=\"T_79a4c_row2_col1\" class=\"data row2 col1\" >32</td>\n",
       "      <td id=\"T_79a4c_row2_col2\" class=\"data row2 col2\" >71</td>\n",
       "      <td id=\"T_79a4c_row2_col3\" class=\"data row2 col3\" >39</td>\n",
       "      <td id=\"T_79a4c_row2_col4\" class=\"data row2 col4\" >26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_79a4c_level0_row3\" class=\"row_heading level0 row3\" >Delayed</th>\n",
       "      <td id=\"T_79a4c_row3_col0\" class=\"data row3 col0\" >16</td>\n",
       "      <td id=\"T_79a4c_row3_col1\" class=\"data row3 col1\" >22</td>\n",
       "      <td id=\"T_79a4c_row3_col2\" class=\"data row3 col2\" >55</td>\n",
       "      <td id=\"T_79a4c_row3_col3\" class=\"data row3 col3\" >26</td>\n",
       "      <td id=\"T_79a4c_row3_col4\" class=\"data row3 col4\" >27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_79a4c_level0_row4\" class=\"row_heading level0 row4\" >Futures</th>\n",
       "      <td id=\"T_79a4c_row4_col0\" class=\"data row4 col0\" >12</td>\n",
       "      <td id=\"T_79a4c_row4_col1\" class=\"data row4 col1\" >9</td>\n",
       "      <td id=\"T_79a4c_row4_col2\" class=\"data row4 col2\" >25</td>\n",
       "      <td id=\"T_79a4c_row4_col3\" class=\"data row4 col3\" >20</td>\n",
       "      <td id=\"T_79a4c_row4_col4\" class=\"data row4 col4\" >17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_79a4c_level0_row5\" class=\"row_heading level0 row5\" >ML</th>\n",
       "      <td id=\"T_79a4c_row5_col0\" class=\"data row5 col0\" >5</td>\n",
       "      <td id=\"T_79a4c_row5_col1\" class=\"data row5 col1\" >11</td>\n",
       "      <td id=\"T_79a4c_row5_col2\" class=\"data row5 col2\" >23</td>\n",
       "      <td id=\"T_79a4c_row5_col3\" class=\"data row5 col3\" >11</td>\n",
       "      <td id=\"T_79a4c_row5_col4\" class=\"data row5 col4\" >7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_79a4c_level0_row6\" class=\"row_heading level0 row6\" >Xarray</th>\n",
       "      <td id=\"T_79a4c_row6_col0\" class=\"data row6 col0\" >8</td>\n",
       "      <td id=\"T_79a4c_row6_col1\" class=\"data row6 col1\" >11</td>\n",
       "      <td id=\"T_79a4c_row6_col2\" class=\"data row6 col2\" >34</td>\n",
       "      <td id=\"T_79a4c_row6_col3\" class=\"data row6 col3\" >7</td>\n",
       "      <td id=\"T_79a4c_row6_col4\" class=\"data row6 col4\" >9</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7f0d7a6f4d60>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "help_by_api = (\n",
    "    pd.merge(\n",
    "        df.loc[2019, 'Dask APIs'].str.split(';').explode(),\n",
    "        df.loc[2019, 'Which would help you most right now?'],\n",
    "        left_index=True, right_index=True)\n",
    "    .groupby('Which would help you most right now?')['Dask APIs'].value_counts()\n",
    "    .unstack(fill_value=0).T\n",
    "    .loc[['Array', 'Bag', 'DataFrame', 'Delayed', 'Futures', 'ML', 'Xarray']]\n",
    "    \n",
    ")\n",
    "(\n",
    "    help_by_api\n",
    "        .style\n",
    "        .background_gradient(axis=\"columns\")\n",
    "        .set_caption(\"2019 normalized by row. Darker means that a higher proporiton of \"\n",
    "                     \"users of that API prefer that priority.\")\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-27T19:24:30.068966Z",
     "iopub.status.busy": "2022-07-27T19:24:30.068765Z",
     "iopub.status.idle": "2022-07-27T19:24:30.092272Z",
     "shell.execute_reply": "2022-07-27T19:24:30.091716Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style type=\"text/css\">\n",
       "#T_09928_row0_col0, #T_09928_row1_col1, #T_09928_row2_col1, #T_09928_row3_col0, #T_09928_row4_col0, #T_09928_row5_col1, #T_09928_row6_col0 {\n",
       "  background-color: #fff7fb;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_09928_row0_col1 {\n",
       "  background-color: #f1ebf5;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_09928_row0_col2, #T_09928_row1_col2, #T_09928_row2_col2, #T_09928_row3_col2, #T_09928_row4_col4, #T_09928_row5_col2, #T_09928_row6_col2 {\n",
       "  background-color: #023858;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_09928_row0_col3, #T_09928_row4_col1 {\n",
       "  background-color: #f5eef6;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_09928_row0_col4 {\n",
       "  background-color: #d0d1e6;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_09928_row1_col0, #T_09928_row1_col3 {\n",
       "  background-color: #f0eaf4;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_09928_row1_col4 {\n",
       "  background-color: #4c99c5;\n",
       "  color: #f1f1f1;\n",
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       "#T_09928_row2_col0, #T_09928_row3_col3 {\n",
       "  background-color: #f5eff6;\n",
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       "#T_09928_row2_col3 {\n",
       "  background-color: #fcf4fa;\n",
       "  color: #000000;\n",
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       "#T_09928_row2_col4 {\n",
       "  background-color: #8eb3d5;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_09928_row3_col1 {\n",
       "  background-color: #ebe6f2;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_09928_row3_col4 {\n",
       "  background-color: #3d93c2;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_09928_row4_col2 {\n",
       "  background-color: #0567a2;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_09928_row4_col3 {\n",
       "  background-color: #cacee5;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_09928_row5_col0 {\n",
       "  background-color: #ede8f3;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_09928_row5_col3 {\n",
       "  background-color: #c1cae2;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_09928_row5_col4 {\n",
       "  background-color: #80aed2;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_09928_row6_col1 {\n",
       "  background-color: #f8f1f8;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_09928_row6_col3 {\n",
       "  background-color: #c9cee4;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_09928_row6_col4 {\n",
       "  background-color: #86b0d3;\n",
       "  color: #000000;\n",
       "}\n",
       "</style>\n",
       "<table id=\"T_09928\">\n",
       "  <caption>2020 normalized by row. Darker means that a higher proporiton of users of that API prefer that priority.</caption>\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"index_name level0\" >Which would help you most right now?</th>\n",
       "      <th id=\"T_09928_level0_col0\" class=\"col_heading level0 col0\" >Bug fixes</th>\n",
       "      <th id=\"T_09928_level0_col1\" class=\"col_heading level0 col1\" >More documentation</th>\n",
       "      <th id=\"T_09928_level0_col2\" class=\"col_heading level0 col2\" >More examples in my field</th>\n",
       "      <th id=\"T_09928_level0_col3\" class=\"col_heading level0 col3\" >New features</th>\n",
       "      <th id=\"T_09928_level0_col4\" class=\"col_heading level0 col4\" >Performance improvements</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th class=\"index_name level0\" >Dask APIs</th>\n",
       "      <th class=\"blank col0\" >&nbsp;</th>\n",
       "      <th class=\"blank col1\" >&nbsp;</th>\n",
       "      <th class=\"blank col2\" >&nbsp;</th>\n",
       "      <th class=\"blank col3\" >&nbsp;</th>\n",
       "      <th class=\"blank col4\" >&nbsp;</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th id=\"T_09928_level0_row0\" class=\"row_heading level0 row0\" >Array</th>\n",
       "      <td id=\"T_09928_row0_col0\" class=\"data row0 col0\" >12</td>\n",
       "      <td id=\"T_09928_row0_col1\" class=\"data row0 col1\" >16</td>\n",
       "      <td id=\"T_09928_row0_col2\" class=\"data row0 col2\" >56</td>\n",
       "      <td id=\"T_09928_row0_col3\" class=\"data row0 col3\" >15</td>\n",
       "      <td id=\"T_09928_row0_col4\" class=\"data row0 col4\" >23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_09928_level0_row1\" class=\"row_heading level0 row1\" >Bag</th>\n",
       "      <td id=\"T_09928_row1_col0\" class=\"data row1 col0\" >7</td>\n",
       "      <td id=\"T_09928_row1_col1\" class=\"data row1 col1\" >5</td>\n",
       "      <td id=\"T_09928_row1_col2\" class=\"data row1 col2\" >24</td>\n",
       "      <td id=\"T_09928_row1_col3\" class=\"data row1 col3\" >7</td>\n",
       "      <td id=\"T_09928_row1_col4\" class=\"data row1 col4\" >16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_09928_level0_row2\" class=\"row_heading level0 row2\" >DataFrame</th>\n",
       "      <td id=\"T_09928_row2_col0\" class=\"data row2 col0\" >24</td>\n",
       "      <td id=\"T_09928_row2_col1\" class=\"data row2 col1\" >21</td>\n",
       "      <td id=\"T_09928_row2_col2\" class=\"data row2 col2\" >67</td>\n",
       "      <td id=\"T_09928_row2_col3\" class=\"data row2 col3\" >22</td>\n",
       "      <td id=\"T_09928_row2_col4\" class=\"data row2 col4\" >41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_09928_level0_row3\" class=\"row_heading level0 row3\" >Delayed</th>\n",
       "      <td id=\"T_09928_row3_col0\" class=\"data row3 col0\" >15</td>\n",
       "      <td id=\"T_09928_row3_col1\" class=\"data row3 col1\" >19</td>\n",
       "      <td id=\"T_09928_row3_col2\" class=\"data row3 col2\" >46</td>\n",
       "      <td id=\"T_09928_row3_col3\" class=\"data row3 col3\" >17</td>\n",
       "      <td id=\"T_09928_row3_col4\" class=\"data row3 col4\" >34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_09928_level0_row4\" class=\"row_heading level0 row4\" >Futures</th>\n",
       "      <td id=\"T_09928_row4_col0\" class=\"data row4 col0\" >9</td>\n",
       "      <td id=\"T_09928_row4_col1\" class=\"data row4 col1\" >10</td>\n",
       "      <td id=\"T_09928_row4_col2\" class=\"data row4 col2\" >21</td>\n",
       "      <td id=\"T_09928_row4_col3\" class=\"data row4 col3\" >13</td>\n",
       "      <td id=\"T_09928_row4_col4\" class=\"data row4 col4\" >24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_09928_level0_row5\" class=\"row_heading level0 row5\" >ML</th>\n",
       "      <td id=\"T_09928_row5_col0\" class=\"data row5 col0\" >6</td>\n",
       "      <td id=\"T_09928_row5_col1\" class=\"data row5 col1\" >4</td>\n",
       "      <td id=\"T_09928_row5_col2\" class=\"data row5 col2\" >21</td>\n",
       "      <td id=\"T_09928_row5_col3\" class=\"data row5 col3\" >9</td>\n",
       "      <td id=\"T_09928_row5_col4\" class=\"data row5 col4\" >12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_09928_level0_row6\" class=\"row_heading level0 row6\" >Xarray</th>\n",
       "      <td id=\"T_09928_row6_col0\" class=\"data row6 col0\" >3</td>\n",
       "      <td id=\"T_09928_row6_col1\" class=\"data row6 col1\" >4</td>\n",
       "      <td id=\"T_09928_row6_col2\" class=\"data row6 col2\" >25</td>\n",
       "      <td id=\"T_09928_row6_col3\" class=\"data row6 col3\" >9</td>\n",
       "      <td id=\"T_09928_row6_col4\" class=\"data row6 col4\" >13</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7f0d7a713bb0>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "help_by_api = (\n",
    "    pd.merge(\n",
    "        df.loc[2020, 'Dask APIs'].str.split(';').explode(),\n",
    "        df.loc[2020, 'Which would help you most right now?'],\n",
    "        left_index=True, right_index=True)\n",
    "    .groupby('Which would help you most right now?')['Dask APIs'].value_counts()\n",
    "    .unstack(fill_value=0).T\n",
    "    .loc[['Array', 'Bag', 'DataFrame', 'Delayed', 'Futures', 'ML', 'Xarray']]\n",
    "    \n",
    ")\n",
    "(\n",
    "    help_by_api\n",
    "        .style\n",
    "        .background_gradient(axis=\"columns\")\n",
    "        .set_caption(\"2020 normalized by row. Darker means that a higher proporiton of \"\n",
    "                     \"users of that API prefer that priority.\")\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Examples are again the most important (for all API groups except `Futures`). But \"Performance improvements\" is now the second-most important field (except for `Futures` where it's most important). How should we interpret this? A charitable interpretation is that Dask's users are scaling to larger problems and are running into new scaling challenges. A less charitable interpretation is that our user's workflows are the same but Dask is getting slower!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Common Feature Requests\n",
    "\n",
    "For specific features, we made a list of things that we (as developers) thought might be important."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-27T19:24:30.095459Z",
     "iopub.status.busy": "2022-07-27T19:24:30.094919Z",
     "iopub.status.idle": "2022-07-27T19:24:32.622387Z",
     "shell.execute_reply": "2022-07-27T19:24:32.621860Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/share/miniconda3/envs/dask-examples/lib/python3.9/site-packages/seaborn/_decorators.py:36: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x3600 with 20 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "common = (df[df.columns[df.columns.str.startswith(\"What common feature\")]]\n",
    "          .rename(columns=lambda x: x.lstrip(\"What common feature requests do you care about most?[\").rstrip(r\"]\")))\n",
    "a = common.loc[2019].apply(pd.value_counts).T.stack().reset_index().rename(columns={'level_0': 'Question', 'level_1': \"Importance\", 0: \"count\"}).assign(Year=2019)\n",
    "b = common.loc[2020].apply(pd.value_counts).T.stack().reset_index().rename(columns={'level_0': 'Question', 'level_1': \"Importance\", 0: \"count\"}).assign(Year=2020)\n",
    "\n",
    "counts = pd.concat([a, b], ignore_index=True)\n",
    "\n",
    "d = common.stack().reset_index().rename(columns={\"level_2\": \"Feature\", 0: \"Importance\"})\n",
    "order = [\"Not relevant for me\", \"Somewhat useful\", 'Critical to me']\n",
    "sns.catplot('Importance', row=\"Feature\", kind=\"count\", col=\"Year\", data=d, sharex=False, order=order);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There really aren't any changes compared to last year in the relative importance of each feature. Perhaps the biggest movement was in \"Ease of deployment\" where \"Critical to me\" is now relatively more popular (though it was the most popular even last year).\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## What other systems do you use?\n",
    "\n",
    "SSH continues to be the most popular \"cluster resource mananger\". This was the big surprise last year, so we put in some work to make it nicer. Aside from that, not much has changed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-27T19:24:32.626499Z",
     "iopub.status.busy": "2022-07-27T19:24:32.625928Z",
     "iopub.status.idle": "2022-07-27T19:24:32.795318Z",
     "shell.execute_reply": "2022-07-27T19:24:32.794813Z"
    }
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "c = df['If you use a cluster, how do you launch Dask? '].dropna().str.split(\";\").explode()\n",
    "top = c.value_counts().index[:6]\n",
    "sns.countplot(y=\"If you use a cluster, how do you launch Dask? \", data=c[c.isin(top)].reset_index(), hue=\"Year\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Dask users are about as happy with its stability as last year."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-27T19:24:32.799608Z",
     "iopub.status.busy": "2022-07-27T19:24:32.798597Z",
     "iopub.status.idle": "2022-07-27T19:24:33.028699Z",
     "shell.execute_reply": "2022-07-27T19:24:33.028100Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# fig, ax = plt.subplots(figsize=(9, 6))\n",
    "sns.countplot(y=\"Is Dask stable enough for you?\", hue=\"Year\", data=df.reset_index())\n",
    "sns.despine()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Takeaways\n",
    "\n",
    "1. Overall, most things are similar to last year.\n",
    "2. Documentation, especially domain-specific examples, continues to be important.\n",
    "3. More users are pushing Dask further. Investing in performance is likely to be valuable.\n",
    "\n",
    "Thanks again to all the respondents. We look forward to repeating this process to identify trends over time."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}