{ "cells": [ { "cell_type": "markdown", "id": "76d8206a-83f1-41c1-8fa6-fd70ca444669", "metadata": {}, "source": [ "# 2021 Dask User Survey Results\n", "\n", "This post presents the results of the 2021 Dask User Survey, which ran earlier this year.\n", "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", "[![2021 Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/dask/dask-examples/main?urlpath=%2Ftree%2Fsurveys%2F2021.ipynb)\n", "\n", "Let us know if you find anything in the data." ] }, { "cell_type": "markdown", "id": "380c49e1-3e15-468f-ae7a-60d7cadca070", "metadata": {}, "source": [ "## Contents\n", "\n", "- [Highlights](#highlights)\n", "- [Who are Dask users?](#who-are-dask-users)\n", "- [How people like to use Dask](#how-people-like-to-use-dask)\n", "- [Diagnostics](#diagnostics)\n", "- [Stability](#stability)\n", "- [User satisfaction, support, and documentation](#user-satisfaction)\n", "- [Suggestions for improvement](#suggestions-for-improvement)\n", "- [Previous survey results](#previous-survey-results)\n" ] }, { "cell_type": "markdown", "id": "d65a2a5c-f76b-4644-9bdc-acbea53deaf9", "metadata": {}, "source": [ "## Highlights \n", "\n", "We had 247 responses to the survey (roughly the same as last year, which had just under 240 responses). Overall, responses were similar to previous years.\n", "\n", "We asked 43 questions in the survey (an increase of 18 questions compared to the year before). We asked a bunch of new questions about the types of datasets people work with, the stability of Dask, and what kinds of industries people work in.\n", "\n", "Our community wants:\n", "\n", "- More documentation and examples\n", "- More intermediate level documentation\n", "- To improve the resiliency of Dask (i.e. do computations complete?)\n", "\n", "Users also value these features:\n", "\n", "- Improved scaling\n", "- Ease of deployment\n", "- Better scikit-learn & machine learning support" ] }, { "cell_type": "markdown", "id": "e7e15abb-5195-4825-b28e-8d63ba8321f8", "metadata": {}, "source": [ "### The typical Dask user\n", "\n", "The survey shows us there is a lot of diversity in our community, and there is no one way to use Dask. That said, our hypothetical \"typical\" Dask user:\n", "\n", "- Works with gigabyte sized datasets\n", "- Stored on a local filesystem\n", "- Has been using Dask between 1 and 3 years\n", "- Uses Dask occasionally, not every day\n", "- Uses Dask interactively at least part of the time\n", "- Uses a compute cluster (probably)\n", "- Likes to view the Dask dashboard with a web browser\n", "- For the most part, Dask is stable enough for their needs, but improving the Dask's resiliancy would be helpful\n", "- Uses the Dask dataframe, delayed, and maybe the Dask Array API, alongside numpy/pandas and other python libraries\n", "- The most useful thing that would help this person is more documentation, and more examples using Dask in their field.\n", "- They likely work in a scientific field (perhaps geoscience, life science, physics, or astronomy), or alternatively they might work in accounting, finance, insurance, or as a tech worker.\n", "\n", "You can read the survey results from previous years here: [2020 survey results](https://blog.dask.org/2020/09/22/user_survey), [2019 survey results](https://blog.dask.org/2019/08/05/user-survey)." ] }, { "cell_type": "code", "execution_count": 1, "id": "a45f6f64-b1a7-467e-917d-eb1f0d29541b", "metadata": { "execution": { "iopub.execute_input": "2022-07-27T19:24:34.433492Z", "iopub.status.busy": "2022-07-27T19:24:34.433039Z", "iopub.status.idle": "2022-07-27T19:24:36.146804Z", "shell.execute_reply": "2022-07-27T19:24:36.146291Z" } }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_10088/2760444752.py:19: 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" ] } ], "source": [ "# Let's load in the survey data...\n", "%matplotlib inline\n", "\n", "from pprint import pprint\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", "\n", "df2021 = (\n", " pd.read_csv(\"data/2021-user-survey-results.csv.gz\")\n", " .assign(Timestamp=lambda df: pd.to_datetime(df['Timestamp']).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", "\n", "common = df2019.columns.intersection(df2020.columns).intersection(df2021.columns)\n", "added = df2021.columns.difference(df2020.columns)\n", "dropped = df2020.columns.difference(df2021.columns)\n", "\n", "df = pd.concat([df2019, df2020, df2021])\n", "df['Year'] = df.Timestamp.dt.year\n", "df = df.set_index(['Year', 'Timestamp']).sort_index()" ] }, { "cell_type": "markdown", "id": "a24c470c-5f1a-489a-af11-176b071e8030", "metadata": {}, "source": [ "## Who are Dask users? " ] }, { "cell_type": "markdown", "id": "68d1923d-0907-4d3c-945e-dc69c5a1a18e", "metadata": {}, "source": [ "Most people said they use Dask occasionally, while a smaller group use Dask every day. There is a wide variety in how long people have used Dask for, with the most common response being between one and three years." ] }, { "cell_type": "code", "execution_count": 2, "id": "feedb3bc-81a6-48f3-b178-440ffcdf5af0", "metadata": { "execution": { "iopub.execute_input": "2022-07-27T19:24:36.149941Z", "iopub.status.busy": "2022-07-27T19:24:36.149485Z", "iopub.status.idle": "2022-07-27T19:24:36.266604Z", "shell.execute_reply": "2022-07-27T19:24:36.266106Z" } }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "q = \"How often do you use Dask?\"\n", "ax = sns.countplot(y=q, data=df2021[q].dropna().str.split(\";\").explode().to_frame());\n", "ax.set(ylabel=\"\", title=q);" ] }, { "cell_type": "code", "execution_count": 3, "id": "bdf6c339-f5b6-4166-9276-5e96914db395", "metadata": { "execution": { "iopub.execute_input": "2022-07-27T19:24:36.269988Z", "iopub.status.busy": "2022-07-27T19:24:36.269543Z", "iopub.status.idle": "2022-07-27T19:24:36.379169Z", "shell.execute_reply": "2022-07-27T19:24:36.378678Z" } }, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "q = \"How long have you used Dask?\" # New question in 2021\n", "order = [\"More than 3 years\", \"1 - 3 years\", \"3 months - 1 year\", \"Less than 3 months\", \"I've never used Dask\"]\n", "ax = sns.countplot(y=q, data=df2021[q].dropna().str.split(\";\").explode().to_frame(), order=order);\n", "ax.set(ylabel=\"\", title=q);" ] }, { "cell_type": "markdown", "id": "1b158090-7827-4df6-8ae1-b6f488883b76", "metadata": {}, "source": [ "Just over half of respondants use Dask with other people (their team or organisation), and the other half use Dask on their own. " ] }, { "cell_type": "code", "execution_count": 4, "id": "ab69c571-e7f6-4376-9a0e-04126d9c22cb", "metadata": { "execution": { "iopub.execute_input": "2022-07-27T19:24:36.383504Z", "iopub.status.busy": "2022-07-27T19:24:36.382162Z", "iopub.status.idle": "2022-07-27T19:24:36.492966Z", "shell.execute_reply": "2022-07-27T19:24:36.492484Z" } }, "outputs": [ { "data": { "image/png": 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2qv48rj2T1QWwOvAs4KXAfhMeLXgi8GlgI9pxe03f5x3APlV1D/AlYJe+/fbApVV147hyPgxc3NuxD3B4X34msDWwAXAVsE1f/kzgnP56E2An2jHdKclak7RVkrQEGG6lxW82cGSS1wJ39WXPB96T5BJayFsOWHsaZWXk9UrA0X3E+ABawAI4G9gnybuBdarqjr78UcA3gNdW1SWTlH9+Vf26qu4Efg58ty+/DJjVX28FHNVfH0ELi9CC3qFJ3ggsPY2+HAzs0V/vAUw01WKyugCOr6p7qupHwGMmqePqqrqsh9gfAidXVY3rzyHArv316ydpx7N6/VTVKcCqSVYCfgA8u//3OeBpSdYEfltVY3OzT66qW6rqj8CPgHXGF57kTUkuSHLBXX+4dZKuSJIWhuFWWjh3Me/Pz3Ijr18C/CewGXBhkmVoIfUVfURzk6pau6qumEY9mwJj230UOLWqNgT+eqzOqjoKeBlwB3BSku369rcA19BGGidz58jre0be38Pkc/Kr1/tm4P3AWsAlSVadqiNVdSYwK8lzgKWrajoPvNUkbc34DSfYZsL+VNU1wHX9OD0D+N8Jypmo/AJOp43WbkP7kHIDsCMt9E7UhruZ4DhW1UFVtXlVbb7M8itO0hVJ0sIw3EoL5zrg0UlWTfJQ2q1ykiwFrFVVpwLvAlYGVgBOAvZMkr7dpvOrIMks4JPAZ/qilYBf9te7j2z3eOCqqjoQOIF2Sx7gT8DLgV2TvGYh+wlwFm0aAbTb+Wf0ep9QVedW1QeBG2kh91ZgqrR2OPBlJh4tnbSuJeBg2vSEr1XV3ROsP73XT5JtgRur6vc9GK8GrNfnRJ9Bm/LwgwnKkCTNAMOttBD6XNGPAOcCJ9Lmw0K7Pf+lJJcBFwMHVNXvaKOuDwFm92kFH52k6Cf0h7+uAL4GfGbkmxL+DfhEkjOZdxrATsDlfcrD+sydH0pV3U4L3ntP5yG2SewF7JFkNm1e7lv78v37A1aX08LgpcCpwFPHP1A24kjgkbSAuyB1LW4n0D50TBay9wU27+3YDxj9SrZzgZ/01z8A1mTJhXBJ0gJKm44mSUte/5aDHarqdTPcjs1pHzy2me/GS9jDH7turf+6D890MyTpPnXh/rvOf6MpJLmwqjafaJ3fcyvpPpHkM8CLgBfPb9sl3I73AP/A3G9MkCQNiOFW0n2iqvac/1ZLXlXtx+RfJSZJeoBzzq0kSZIGw3ArSZKkwTDcSpIkaTAMt5IkSRoMw60kSZIGw3ArSZKkwTDcSpIkaTAMt5IkSRoMw60kSZIGw3ArSZKkwTDcSpIkaTAMt5IkSRoMw60kSZIGw3ArSZKkwTDcSpIkaTAMt5IkSRoMw60kSZIGw3ArSZKkwTDcSpIkaTAMt5IkSRoMw60kSZIGw3ArSZKkwVhmphsgSQ9mT3ncqlyw/64z3QxJGgxHbiVJkjQYhltJkiQNhuFWkiRJg2G4lSRJ0mAYbiVJkjQYhltJkiQNhuFWkiRJg2G4lSRJ0mAYbiVJkjQYhltJkiQNhuFWkiRJg2G4lSRJ0mAYbiVJkjQYy8x0AyTpwexPv/4h//eRp810MyTdT639wctmugkPOI7cSpIkaTAMt5IkSRoMw60kSZIGw3ArSZKkwTDcSpIkaTAMt5IkSRoMw60kSZIGw3ArSZKkwTDcSpIkaTAMt5IkSRoMw60kSZIGw3ArSZKkwTDcSpIkaTAMt5IkSRoMw60kSZIGw3ArSZKkwTDcSpIkaTAMt5IkSRoMw60kSZIGw3ArSZKkwTDcSpIkaTAMt5IkSRoMw60kSZIGw3ArSZKkwTDcSpIkaTAMt1ogSSrJESPvl0lyQ5ITF6CMbZP8vyXTwmFLsm+Sd8x0OxZWktOSbD7T7RgvyaFJrk5yaZKfJDk8yZqLUNaOi7uNkqTpMdxqQd0ObJjkYf39XwG/XMAytgXud+E2yTILs24JtWXp+6CO+7RPDwDvrKqNgScDFwOnJll2htskSVpAhlstjP8FXtJfvxr4MkCSpZL8NMmjRt7/LMlqYzsmmQW8Gdg7ySVJtknyqCTHJjm//7d133bLJGclubj/++S+fPckxyf5Zh9te0uSt/ftzkmyyvgGJ1knyclJZvd/1+7LD03yqSSnAv86bp/dkxyd5JvAd5M8PMkhvY0XJ9mhb7dBkvN6f2YnWa8vf+3I8v8ZC6xJPpfkgiQ/TPLhkfrmJPlgkjOAVyZ5YZKL+mjiySNNe2ofAb0qyV4TnaAkf9dHIE9L8vkkn52ov0k26cdsdpKvJ3lk3+4vI6xJVksyZ+SYfCPJd5L8OMmHJql/wj6OrF+6t+XyJJcl2bsvn7A94/adZ2Q0yW3939WTnN6P9+VJtunLn5/k7H4sj06ywkRtHlPNAcBvgBdN1Z8k+yX5UW/vJydo60d7e/1dK0n3EX/hamF8Bdg5yXLARsC5AFV1D/AlYJe+3fbApVV149iOVTUH+G/ggKrapKp+AHy6v98CeAVwcN/8SuDZVbUp8EHg4yNt2BB4DbAl8DHgD327s4FdJ2jzZ4HDq2oj4EjgwJF1TwK2r6p/nmC/rYDdqmo74H3AKb2dzwX2T/JwWlj/dFVtAmwOXJvkKcBOwNZ9+d0jx+V9VbV5P3bPSbLRSH1/rKpnAScDnwde0UcTXzmyzfrAC3rfP5TkIaMNTrIG8AHgmbSR9fXH9Wm0v4cD7+7H5TJgwrA6zpa9L5vQQvhE0wym6iN93zWrasOqehrwxb58Ydoz5jXASf14bwxckvbB6v20/j4duAB4+zTLu4i5x+5e/ekfov4G2KC3919Gd07yb8CjgT36z8boujf1sHzBb2+/ewG6KEmaH29LaoFV1ey0EdhXA98et/oQ4BvAfwCvZ25omcr2tNHIsfePSLIisBJwWB8JLWA0xJ1aVbcCtya5BfhmX34ZLYCMtxXwt/31EcC/jaw7uqomSxjfq6rf9tfPB16WuXNelwPWpgXq9yV5HHBcVf00yfOAzYDze78eBlzf93tVkjfRfv5WB54KzO7rvtr/fSZwelVdDTDSBoBvVdWdwJ1JrgceA1w7sn5L4Ptj+yQ5mhZo5+lvkpWAlavq+335YcDRkxyH8cfkpl72ccCzaKFx1FR9BLgKeHySzwDfoo2ML2x7xpwPHNLD/vFVdUmS5/S6z+znYVna+ZqOjLyeqD8/Av4IHJzkW8DovPMPAOdW1ZsmKriqDgIOAthozYfVNNsjSZoGw60W1gnAJ2nzZ1cdW1hV1yS5Lsl2wDOYO1o5laWArarqjtGFPficWlV/08P0aSOr7xx5fc/I+3uY3nU9Gihun2K70XWhjaT+eNw2VyQ5lzZV46Qkb+jbHlZV7x3dMMm6wDuALarq5iSH0kLy+Poyro2jRvt+N/fub5jaVP0dcxdz7+wsN27d+HbN834afaQv35g2Av1PwKuAvafRrnnalpZYl+1lnp7k2bTzcESS/YGbaWH81dMse9SmwMmT9aeq7kqyJfA8YGfgLcB2fd/zgc2SrDLug4kkaQlzWoIW1iHAR6rqsgnWHUybnvC1SUZEbwVWHHn/XVowANq8y/5yJeY+rLb7Irb3LFoAgRa4z1iIMk4C9uyBiiSb9n8fD1xVVQfSQv9GtGkFOyZ5dN9mlSTrAI+ghctbkjyGPqdzAmfTbn+vO7b/ArTzvL7vI9MeGnvFRBtV1S3AzWNzU4HXAWOjpnNoI88A45/8/6ven4cBLwfOHLd+vn3s0wWWqqpjaaOcT59Pe0aNtm0H+oh+P77XV9XngS8ATwfOAbZO8sS+zfJJnnSvEudtW9LmMq8OfGey/vS5uytV1beBt9GmWoz5DrAf8K1+F0KSdB9x5FYLpaqupc2VncgJtOkIk01J+CZwTNoDWXsCewH/mWQ27Zo8nTaP9d9o0xLeDpyyiE3ei3bL+p3ADcAeC1HGR2nTLWb3gDsHeCltbu1rk/yZ9hDSR6rqt0neT7vdvhTwZ+CfquqcJBcDP6Tdmh8fDAGoqhv6bfDj+v7X0+bPzldV/TLJx2lzoX9Fu31+yySb7wb8d5Lle3vGjssnga8leR33PvZn0KZ2PBE4qqrmmZJQVZdOo49rAl8cedBqbIR7svaM+jzwjSTn0T5EjI1Ebwu8s5+H24Bd+3HcHfhykof27d4P/GSCcvdP8gFgeVoofm5V/QmYrD8r9nYsRxstn2fkuaqO7sH2hCQvHn9nQpK0ZKTK6V5avPoDRgdU1Tbz3VhLRJIVquq2PnL7deCQqvr6Yih3d2DzqnrL/LbV9Gy05sPqxL9/4kw3Q9L91NofnOgGqZJc2B/0vRenJWixSvIe4FjmjsRpZuyb5BLgcuBq4PgZbY0kSfcRpyVosaqq/WhzDTWDqmqJ/F/MqupQ4NAlUbYkSYuDI7eSJEkaDMOtJEmSBsNwK0mSpMEw3EqSJGkwDLeSJEkaDMOtJEmSBsNwK0mSpMEw3EqSJGkwDLeSJEkaDMOtJEmSBsNwK0mSpMEw3EqSJGkwDLeSJEkaDMOtJEmSBsNwK0mSpMEw3EqSJGkwDLeSJEkaDMOtJEmSBsNwK0mSpMEw3EqSJGkwDLeSJEkajGVmugGS9GC27OobsPYHL5jpZkjSYDhyK0mSpMEw3EqSJGkwDLeSJEkaDMOtJEmSBsNwK0mSpMEw3EqSJGkwDLeSJEkaDMOtJEmSBsNwK0mSpMEw3EqSJGkwDLeSJEkaDMOtJEmSBsNwK0mSpMEw3EqSJGkwlpnpBkjSg9mV11/J1p/Zeqab8aBw5p5nznQTJN0HHLmVJEnSYBhuJUmSNBiGW0mSJA2G4VaSJEmDYbiVJEnSYBhuJUmSNBiGW0mSJA2G4VaSJEmDYbiVJEnSYBhuJUmSNBiGW0mSJA2G4VaSJEmDYbiVJEnSYBhuJUmSNBiGW0mSJA2G4VaSJEmDYbiVJEnSYBhuJUmSNBiGW0mSJA2G4VaSJEmDYbiVJEnSYBhuJUmSNBiGW0mSJA2G4VaSJEmDMd9wm+TuJJckuTTJRUn+333RsAnasW2SE2eibi1+SU5LsvkCbL97kjVG3s9JstqSad2kbVgsdSZZOck/Lo42zaeelyV5z0Luu8+492f1f2clec2ilHF/1K/HHyeZneTKJJ9NsvIilDXta1uStHhNZ+T2jqrapKo2Bt4LfGIJt+l+LckyM92GB6ndgTXmt9Go+/G5WhlY4uG2qk6oqv0Wcvd5gmlVjX2onQVMK9xOUcb91S5VtRGwEXAn8I0Zbo8kaSEs6LSERwA3j71J8s4k5/fRjg/3ZR9N8taRbT6WZK80+ye5PMllSXbq67ftIx3H9BGTI5Okr3thX3YG8LcTNaiP6B2f5JtJrk7yliRvT3JxknOSrJLkCUkuGtlnvSQXTlDWFr0vZ4+1daSOo5N8E/huL/P4vu05STbq2+2b5B0j5V3eR7pm9X4c1vc5JsnyUx3oJIcm+VySU5NcleQ5SQ5JckWSQ0e2+1ySC5L8cOwc9OVzkny4j7ZflmT9JEsl+WmSR/Vtlkrys/Gjkb0fRyQ5pW//xqnOeV/+9t7fy5O8rS+bVr+TPL8f84v6cV5h3Podgc2BI9PuIjysr9pztH8jbT8oyXeBw5Osk+TkXv/JSdYeOb47jtRx28gx+a9+PE9M8u3R7Sapc4GuB2A/4Am9L/uP6+vYMTu4b39kku2TnNnPxZYLcB53T/LZkf4emOSsfj3t2JevnuT03pbLk2yTZD/gYX3ZkaPHp7d9m75u79E6+nYnpv1MT1pGmgX6XTCuX38ZGU2yWpI5/fUGSc7rdc5Osl5f/tqR5f+TZOnxZY6qqj8B7wLWTrJxL+P4JBf26+JNfdnS/biO9WPvce1cKu3a/5ep6pMkLV7TCbdjf6CuBA4GPgotkADrAVsCmwCbJXk28AVgt77NUsDOwJG0cLoJsDGwPbB/ktV7HZsCbwOeCjwe2DrJcsDngb8GtgEeO0UbN6SNJm0JfAz4Q1VtCpwN7FpVPwduSbJJ334P4NAJyvki8Oaq2gq4e9y6rYDdqmo74MPAxX2UZx/g8CnaNubJwEF9n98zvZG7RwLbAXsD3wQOADYAnjbSl/dV1ea00abnjAWr7saqejrwOeAdVXUP8CVgl75+e+DSqrpxgro3Al7S+/3BJGtMds6TbEY7ps8Angm8Mcmm0+l3D2TvB7bvbb0AePvoNlV1TF++S7+LcMdE/RvZZTNgh6p6DfBZ4PBe/5HAgRP0ddTf0kYnnwa8ofd/1ER1Luj18B7g570v75xg/ROBT9POwfq0a/tZvb59FvA8jlq9l/NSWkill31SVW1C+9m8pKrew9w7NruMK+M9wA/6ugMmq2g+ZSzQ74L59GnUm4FP975sDlyb5CnATsDWffndzD1uk6qqu4FLaccf4PVVtVkvd68kq/Y+rFlVG1bV02i/P8YsQ7veflJV71+APkiSFtGCTEtYH3ghbTQswPP7fxcDF9H+CKxXVXOAm3q4eT7tj/5NtD+qX66qu6vqOuD7wBa9jvOq6tr+R/sSWrhYH7i6qn5aVUX7Yz6ZU6vq1qq6AbiFFgQBLutlQQvme/RRm52Ao0YLSJtft2JVjc0LnGc98L2q+m1//SzgCICqOgVYNclKU7QP4JqqOrO//lIvY36+2ft+GXBdVV3Wj9EPR/r1qrRR6YtpwfepI/sf1/+9cGT7Q4Bd++vXM+8f5FHfqKo7emA6lRZoJzznvS9fr6rbq+q2Xu820+z3M3ubz0xyCe2D0TpTHJNRE/UP4ISRALwVc8/lERPUP96zgKOr6p6q+g2t7/Orc2Guh6lcPe5cnzxyHYzVOd3zOOr43q8fAY/py86n/VzsCzytqm5dhHZP14L+Lpius4F9krwbWKdfA8+jfdg5v19fz6OF5ukYHTXeK8mlwDnAWrTr/irg8Uk+k+SFtA9vY/4HuLyqPjZhwcmb0u64XPDn2/48/R5KkuZrgeYkVtXZfaTtUbRf/J+oqv+ZYNODaXMkH0v7Iwzz/qEY786R13ePtKum2bTR/e8ZeX/PSFnHAh8CTgEu7IF71FTtA7h9PtsWcBfzfmBYbtz68dvPz2g/xvdxmSTr0kbztqiqm9OmKyw3wf5/OaZVdU2S65JsRxtpnWwUa6L2TnjO06chLEA58+xO++Dw6inKmMy9+tfdPsG24+v/y7nqH9aWHWnPgta5MNfDdOqASa7nBTiPk5WbXs7p/Y7LS4AjkuxfVdO5EzFmYfq4ML8LJqvzL/VV1VFJzqX15aQkb+h1HVZV751Gu+Y2sH0IfhpwRZJtaSPMW1XVH5KcBizXf+Y2Bl4A/BPwKtoHDYCzgOcm+feq+uP48qvqIOAggBXWXmG6v+ckSdOwQHNu0+YYLg3cBJwEvD59fmSSNZM8um/6ddoo7xZ9O4DTgZ36PLVHAc8GzpuiuiuBdZM8ob9fmPDzF/0PzEm028n3GuWqqpuBW5M8sy/aeYriTqeHif6H78aq+j0wB3h6X/50YN2RfdZOMnaL+9XAGX27TyT5m4XqVJsDfTttysVjgBdNc7+DaaOoX+u3XyeyQ5Ll+u3XbWkjfJOd89OBlydZPsnDgb8BftDLmbDfI86hTUN5Yi9z+SRPmqA9twIrTrN/o85i7rncZaT+ObQRPYAdgIf012cAr+jzJR9D6/v8LOj1sLB9GW8653FKSdYBrq+qz9OmFD29r/pzkodMsMv4ts8BNunHay3aCP+YycpY0N8F481h7rkbnTf9eOCqqjoQOIE2reNkYMex301p86OnvDPQ2/wJ2l2H2cBKwM092K5Pu9swNqVmqao6FvgAc48dtGP5beDo3H8fbJSkQVqQObeXAF+lzTu9u6q+S7vde3aSy4Bj6H/0+gMZpzLvH92vA7Np89hOAd7Vb/tOqIfRNwHfSnug7BcL08FxjqSNqH13kvV/BxyU5GzaiM8tk2y3L7B5ktm0uYu79eXHAqv0Y/UPwE9G9rkC2K3vswotZEMbHZr0OEylqi6lTRH4IW2E/Myp9/iLE4AVmPpW9nnAt2jh86NV9avJznlVXUSbw3wecC5wcFVd3MuZrN9jfbiBNsr/5b7NOcyd5zjqUOC/M+8DZdOxF+22+2zgdcDYw46fp81RPo828jk22nsscC1wOe3W8rlMfh2M2ZcFuB76XYMz0x5E2v/exU3bdM7j/GwLXJLkYuAVtLm+0EYVZ6c/DDZiNnBX2lcD7k275q6mTZn4JG26CvMpY4F+F0zgk8A/pH212OhDdDsBl/fjvT5trvWPaHO6v9vPz/doc48ncmTf5nLg4bQPPQDfod0pmU175uCcvnxN4LRe36G0b5P5i6r6FO14HJH2/IEk6T6QNpVvMRfafpFfBLyyqn662CtYSGlPrq9UVR+YZP0Kfc4oad8PunpVvXWibRew3lnAiVW14QTrTqqqFyxqHQvYns2BA6pqm0nW7wvcVlWfXMR6ZjFJv+/Pxq6DPmp9Hu1hpIX6ALIkze886oFhhbVXqI3fufFMN+NB4cw9p/v5X9L9XZILqz1Qfy+L/XZZkqcCJ9IeMLo/BduvA0+gffvAZF6S5L204/IL2ojiEjUDwfY9tFHE6czRfLA6Me0Bw2Vpo9b3x2DreZQkaQJLZORWkjQ9jtzedxy5lYZjqpFb54FJkiRpMAy3kiRJGgzDrSRJkgbDcCtJkqTBMNxKkiRpMAy3kiRJGgzDrSRJkgbDcCtJkqTBMNxKkiRpMAy3kiRJGgzDrSRJkgbDcCtJkqTBMNxKkiRpMAy3kiRJGgzDrSRJkgbDcCtJkqTBMNxKkiRpMAy3kiRJGgzDrSRJkgbDcCtJkqTBMNxKkiRpMAy3kiRJGoxlZroBkvRgtv6j1+fMPc+c6WZI0mA4citJkqTBMNxKkiRpMAy3kiRJGgzDrSRJkgbDcCtJkqTBMNxKkiRpMFJVM90GSXrQSnIr8OOZbscSthpw40w3Ygmzj8NgHx841qmqR020wu+5laSZ9eOq2nymG7EkJbnAPj7w2cdheDD00WkJkiRJGgzDrSRJkgbDcCtJM+ugmW7AfcA+DoN9HIbB99EHyiRJkjQYjtxKkiRpMAy3kiRJGgzDrSTNkCQvTPLjJD9L8p6Zbs/ikGStJKcmuSLJD5O8tS9fJcn3kvy0//vImW7rokiydJKLk5zY3w+qfwBJVk5yTJIr+/ncakj9TLJ3v0YvT/LlJMsNoX9JDklyfZLLR5ZN2q8k7+2/g36c5AUz0+rFy3ArSTMgydLAfwIvAp4KvDrJU2e2VYvFXcA/V9VTgGcC/9T79R7g5KpaDzi5v38geytwxcj7ofUP4NPAd6pqfWBjWn8H0c8kawJ7AZtX1YbA0sDODKN/hwIvHLdswn71n82dgQ36Pv/Vfzc9oBluJWlmbAn8rKquqqo/AV8BdpjhNi2yqvp1VV3UX99KC0Rr0vp2WN/sMODlM9LAxSDJ44CXAAePLB5M/wCSPAJ4NvAFgKr6U1X9jmH1cxngYUmWAZYHfsUA+ldVpwO/Hbd4sn7tAHylqu6sqquBn9F+Nz2gGW4laWasCVwz8v7avmwwkswCNgXOBR5TVb+GFoCBR89g0xbVfwDvAu4ZWTak/gE8HrgB+GKffnFwkoczkH5W1S+BTwL/B/wauKWqvstA+jeByfo1yN9DhltJmhmZYNlgvpsxyQrAscDbqur3M92exSXJS4Hrq+rCmW7LErYM8HTgc1W1KXA7D8xb9BPqc053ANYF1gAenuS1M9uqGTHI30OGW0maGdcCa428fxzttugDXpKH0ILtkVV1XF98XZLV+/rVgetnqn2LaGvgZUnm0KaSbJfkSwynf2OuBa6tqnP7+2NoYXco/dweuLqqbqiqPwPHAf+P4fRvvMn6NcjfQ4ZbSZoZ5wPrJVk3ybK0hzpOmOE2LbIkoc3TvKKqPjWy6gRgt/56N+Ab93XbFoeqem9VPa6qZtHO2SlV9VoG0r8xVfUb4JokT+6Lngf8iOH08/+AZyZZvl+zz6PNDx9K/8abrF8nADsneWiSdYH1gPNmoH2Llf+HMkmaIUleTJu/uTRwSFV9bGZbtOiSPAv4AXAZc+ek7kObd/s1YG1asHhlVY1/6OUBJcm2wDuq6qVJVmV4/duE9tDcssBVwB60QbFB9DPJh4GdaN/wcTHwBmAFHuD9S/JlYFtgNeA64EPA8UzSryTvA15POw5vq6r/ve9bvXgZbiVJkjQYTkuQJEnSYBhuJUmSNBiGW0mSJA2G4VaSJEmDYbiVJEnSYBhuJUnSIknytiTLz3Q7JPCrwCRJ0iLq/8e2zavqxplui+TIrSRJDwJJdk0yO8mlSY5Isk6Sk/uyk5Os3bc7NMmOI/vd1v/dNslpSY5JcmWSI9PsBawBnJrk1JnpnTTXMjPdAEmStGQl2QB4H7B1Vd2YZBXgMODwqjosyeuBA4GXz6eoTYENgF8BZ/byDkzyduC5jtzq/sCRW0mShm874Jix8Nn/16tbAUf19UcAz5pGOedV1bVVdQ9wCTBr8TdVWjSGW0mShi/A/B6yGVt/Fz0fJAmw7Mg2d468vhvvAOt+yHArSdLwnQy8KsmqAH1awlnAzn39LsAZ/fUcYLP+egfgIdMo/1ZgxcXVWGlR+IlLkqSBq6ofJvkY8P0kdwMXA3sBhyR5J3ADsEff/PPAN5KcRwvFt0+jioOA/03y66p67uLvgTR9fhWYJEmSBsNpCZIkSRoMw60kSZIGw3ArSZKkwTDcSpIkaTAMt5IkSRoMw60kSZIGw3ArSZKkwfj/AUYAvlQZXqDsAAAAAElFTkSuQmCC\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "q = \"Do you use Dask as part of a larger group?\"\n", "order = [\n", " 'I use Dask mostly on my own',\n", " 'My team or research group also use Dask',\n", " 'Beyond my group, many people throughout my institution use Dask',\n", "]\n", "ax = sns.countplot(y=q, data=df2021[q].dropna().str.split(\";\").explode().to_frame(), order=order)\n", "ax.set(ylabel=\"\", title=q);" ] }, { "cell_type": "markdown", "id": "a4593c6a", "metadata": {}, "source": [ "In the last year, there has been an increase in the number of people who say that many people throughout their institution use Dask (32 people said this in 2021, compared to 19 in 2020). Between 2019 and 2020, there was a drop in the number of people who said their immediate team also uses Dask (121 people said this in 2019, compared to 94 in 2020). It's not clear why we saw either of these changes, so it will be interesting to see what happens in future years." ] }, { "cell_type": "code", "execution_count": 5, "id": "afb24121", "metadata": { "execution": { "iopub.execute_input": "2022-07-27T19:24:36.497231Z", "iopub.status.busy": "2022-07-27T19:24:36.496166Z", "iopub.status.idle": "2022-07-27T19:24:36.648684Z", "shell.execute_reply": "2022-07-27T19:24:36.648192Z" } }, "outputs": [ { "data": { "image/png": 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Ly8R6fo7Xn7VmZsuJP3CtOf4EHC6pA9ATeAwgIj4HbgIG5XJ7Ac9ExFs1G0ZENfAb4LKI6BUR/wCuyO93AAYA1+XiLwBfi4jewDnAhSUxbAMcCewIXAD8J5d7FBhcJuargZER0RO4GbiyZN3mwF4R8X9lttsZGBIRewJnAvfnOPcALpG0GilZvyIiegF9gVmSegADgV3y8oUl++XMiOib993XJfUsae/jiNgVmAD8HhiQRxO/XVJmS2Dv3PefSlqpNGBJXYCzgZ1II+tb1upTaX9HAqfl/TIVKJus1rJj7ksvUhJebppBfX0kb7tBRGwTEdsCf8zLmxNPjSOBv+X9vR3wtNIXq7NI/e0DPAmc0sj6nmLxvvtCf/KXqIOBrXO8Py/dWNIvgE7AMflnw8zMlgNflrQmi4hnlUZgjwD+Umv19cA44HLgOyxOWuqzF2k0sub9GpI6AmsCI/JIaAClSdwDEfEB8IGk94C78/KppASktp2BQ/LrG4FflKwbHREL64jtvoh4O7/+BnCgFs957QB0IyXUZ0rqCtwRES9J6g9sDzyR+7UK8Ebe7jBJx5N+/qqArYBn87rb8v87AQ9FxCsAJTEA/DkiPgE+kfQG0BmYVbJ+R+DvNdtIGk1KaJfor6Q1gbUi4u95+QhgdB37ofY+mZfrvgPYlZQ0lqqvjwAzgK9Iugr4M2lkvLnx1HgCuD4n+2Mj4mlJX89tT8zHoT3peDWGSl6X68/zwMfAdZL+DJTOOz8beCwiji9bcarreIAN1lypXBEzM2smJ7fWXHcBl5Lmz65bszAiZkqaK2lPoB+LRyvr0wbYOSI+Kl2YE58HIuLgnEw/WLL6k5LXn5e8/5zGnddR8vrDesqVrhNpJPWftcpMl/QYaarG3yQdl8uOiIjTSwtK2hj4MbBDRLwj6QZSkly7PdWKsVRp3xfyxf6K+tXX3xqfsfjKToda62rHtcT7RvSRvHw70gj0/wKHAT9qRFxLxKaUsbbPdT4k6Wuk43CjpEuAd0jJ+BGNrLtUb2BCXf2JiM8k7Qj0Bw4HTgD2zNs+AWwvaZ1aX0zIsf4O+B1Azw1Wqes4m5lZM3hagjXX9cDPIqLcH9C+jjQ9YVQdI6IfAB1L3o8nJQZAmneZX67J4pvVhi5lvI+QEhBICffDzajjb8CJOaFCUu/8/1eAGRFxJSnp70maVnCopE65zDqSNgLWICWX70nqTJ7TWcajpMvfG9ds34Q4H8/brq1009iAcoUi4j3gnZq5qcDRQM2oaTVp5Bmg9p3//537swrwLWBirfUN9jFPF2gTEWNIo5x9GoinVGlsB5FH9PP+fSMifg/8AegDTAJ2kbRpLrOqpM2/UOOSsUlpLnMV8Ne6+pPn7q4ZEX8BfkiaalHjr8Bw4M/5KoSZmS0nHrm1ZomIWaS5suXcRZqOUNeUhLuB25VuyDoROAm4RtKzpHPyIdI81l+QpiWcAty/lCGfRLpkfSrwJnBMM+o4nzTd4tmc4FYD+5Pm1h4laQHpJqSfRcTbks4iXW5vAywA/jciJkmaAjxHujRfOzEEICLezJeu78jbv0GaP9ugiJgt6ULSXOjXSJfP36uj+BDgN5JWzfHU7JdLgVGSjuaL+/5h0tSOTYFbImKJKQkR8Uwj+rgB8MeSG61qRrjriqfU74Fxkh4nfYmoGYneHTg1H4f5wOC8H4cCt0paOZc7C3ixTL2XSDobWJWUFO8REZ8CdfWnY46jA2m0fImR54gYnRPbuyTtW/vKhJmZLRuK8BUxa1n5BqPLImK3BgvbMiFp9YiYn0du7wSuj4g7W6DeoUDfiDihobLWOD03WCXu+d6mlQ7DzFpQt3PKXdS0liRpcr7R9ws8LcFalKRhwBgWj8RZZZwr6WlgGvAKMLai0ZiZmS0nnpZgLSoihpPmGloFRcQy+StmEXEDcMOyqNvMzKwleOTWzMzMzArDya2ZmZmZFYanJZiZVdCMtm05Yu01Kh2GmS2liSeWffiNVYBHbs3MzMysMJzcmpmZmVlhOLk1MzMzs8JwcmtmZmZmheHk1szMzMwKw8mtmZmZmRWGk1szMzMzKwwnt2ZmZmZWGE5uzczMzKwwnNyamZmZWWE4uTUzMzOzwnBya2ZmZmaF4eTWzMzMzArDya2ZmZmZFYaTWzMzMzMrDCe3ZmZmZlYYTm7NzMzMrDCc3JqZmZlZYTi5NTMzM7PCaFfpAMzMvsy27LQlE0+cWOkwzMwKwyO3ZmZmZlYYTm7NzMzMrDCc3JqZmZlZYTi5NTMzM7PCcHJrZmZmZoXh5NbMzMzMCsPJrZmZmZkVhpNbMzMzMysMJ7dmZmZmVhhObs3MzMysMJzcmpmZmVlhOLk1MzMzs8JwcmtmZmZmhdGu0gGYmX2ZTZ81j+1PHVnpMMzMmm3yJYMrHcISPHJrZmZmZoXh5NbMzMzMCsPJrZmZmZkVhpNbMzMzMysMJ7dmZmZmVhhObs3MzMysMJzcmpmZmVlhOLk1MzMzs8JwcmtmZmZmheHk1szMzMwKw8mtmZmZmRWGk1szMzMzKwwnt2ZmZmZWGE5uzczMzKwwnNyamZmZWWE4uTUzMzOzwnBya2ZmZmaF4eTWzMzMzApDEVHpGMzMvrR6brBK3PO9TSsdhpnZctXtnKlLtb2kyRHRt9w6j9yamZmZWWE4uTUzMzOzwnBya2ZmZmaF4eTWzMzMzArDya2ZmZmZFYaTWzMzMzMrDCe3Zg2QNH85tdNd0keSpkiaLulxSUOWoq5pLR1jI9rtJWnfkvdDJV29vOMwM7Mvr3aVDsDMlvCviOgNIOkrwB2S2kTEHyscV2P1AvoCf6lwHGZm9iXlkVuzZqg9Mirpx5LOza9PkvS8pGcl/SkvW03S9ZKeyCOzBzXURkTMAE4BTsp17Cjpkbz9I5K2yMu3zqO8T+c2N6sV61fyNjvUWr67pL9LGiXpRUnDJQ3KdU2VtEkut5GkCbnuCZK65eXfljRN0jOSHpLUHvgZMDDHMrCkrY6SXpG0Un6/hqTqmvcl5epq6wZJV+Z+z5B0aB3H5AVJ1+W4bpa0l6SJkl7K+69Nfr1+3qaNpJclrVerrnUkjc1xTJLUMy+fKmktJfMkDc7Lb8xtDZV0h6S/5nZ+0dBxNjOzluXk1qzlDQN6R0RP4Pt52ZnA/RGxA7AHcImk1RpR11PAlvn1C8DX8sjuOcCFefn3gSsiohdp1HRWzcY5AR4DHBMRT5SpfzvgZGBb4Ghg84jYEbgOODGXuRoYmftzM3BlXn4OsHdEbAccGBGf5mW3RUSviLitppGI+AB4ENgvLzocGBMRC2rFU1dbAFXArsD+wPCyews2Ba4AepL225F5mx8DZ0TE58BNwKBcfi/gmYh4q1Y95wFTchxnACPz8onALsDWwAxgt7x8J2BSft0LGEjapwMlbVg7SEnHS3pS0pNvf7iwjq6YmVlzOLk1a3nPAjdLOgr4LC/7BjBM0tOkJK8D0K0Rdank9ZrA6DxifBkpwQJ4FDhD0mnARhHxUV6+PjAOOCoinq6j/iciYk5EfAL8Cxifl08FuufXOwO35Nc3kpJFSIneDZK+C7RtRF+uA47Jr48Byk21qKstgLER8XlEPA90rqONVyJiak5inwMmRPob46X9uR4YnF9/p444ds3tExH3A+tKWhP4B/C1/O9aYFtJGwBvR0TN3OwJEfFeRHwMPA9sVLvyiPhdRPSNiL7rrNaYXWdmZo3l5NaseT5jyZ+fDiWv9wOuAbYHJktqR0pSB+QRzV4R0S0ipjeind5ATbnzgQciYhvggJo2I+IW4EDgI+BvkvbM5d8DZpJGGuvyScnrz0vef07dc/Ijt/t94CxgQ+BpSevW15GImAh0l/R1oG1ENOaGt6gjVtUuWKZM2f5ExExgbt5P/YB7y9RTrv4AHiKN1u5G+pLyJnAoKektF8NCfG+Dmdly5eTWrHnmAp0krStpZdKlciS1ATaMiAeAnwBrAasDfwNOlKRcrndDDUjqDlwKXJUXrQnMzq+HlpT7CjAjIq4E7iJdkgf4FPgWMFjSkc3sJ8AjpGkEkC7nP5zb3SQiHouIc4C3SEnuB0DHeuoaCdxK+dHSOttaBq4jTU8YFRHl5gU8lNtH0u7AWxHxfk6M1wM2y3OiHyZNefhHmTrMzKwCnNyaNUOeK/oz4DHgHtJ8WEiX52+SNBWYAlwWEe+SRl1XAp7N0wrOr6PqTfLNX9OBUcBVJU9K+AVwkaSJLDkNYCAwLU952JLF80OJiA9JifePGnMTWx1OAo6R9CxpXu7Jefkl+QaraaRk8BngAWCr2jeUlbgZWJuU4DalrZZ2F+lLR11J9rlA3xzHcKD0kWyPAS/m1/8ANmDZJeFmZtZEStPRzMyWvfyUg4Mi4ugKx9GX9MVjtwYLL2M9N1gl7vneppUOw8xsuep2ztSl2l7S5IjoW26d54KZ2XIh6SpgH2Dfhsou4ziGAf/D4icmmJlZgTi5NbPlIiJObLjUshcRw6n7UWJmZtbKec6tmZmZmRWGk1szMzMzKwxPSzAzq6AZbdtyxNprVDoMMzMAJp44sdIhLDWP3JqZmZlZYTi5NTMzM7PCcHJrZmZmZoXh5NbMzMzMCsPJrZmZmZkVhpNbMzMzMysMJ7dmZmZmVhhObs3MzMysMJzcmpmZmVlhOLk1MzMzs8JwcmtmZmZmheHk1szMzMwKw8mtmZmZmRWGk1szMzMzKwwnt2ZmZmZWGE5uzczMzKwwnNyamZmZWWE4uTUzMzOzwmhX6QDMzL7Mtuy0JRNPnFjpMMzMCsMjt2ZmZmZWGE5uzczMzKwwnNyamZmZWWE4uTUzMzOzwnBya2ZmZmaF4eTWzMzMzArDya2ZmZmZFYaTWzMzMzMrDCe3ZmZmZlYYTm7NzMzMrDCc3JqZmZlZYbSrdABmZmZm1jgLFixg1qxZfPzxx5UOZbno0KEDXbt2ZaWVVmr0Nk5uzczMzFqJWbNm0bFjR7p3746kSoezTEUE8+bNY9asWWy88caN3s7TEszMzMxaiY8//ph111238IktgCTWXXfdJo9Se+TWzKyCps+ax/anjqx0GM0y+ZLBlQ7B7Evpy5DY1mhOXz1ya2ZmZmaF4eTWzMzM7EsqIth111259957Fy0bNWoU3/zmNysY1dLxtAQzMzOzLylJ/OY3v+Hb3/42e+yxBwsXLuTMM8/kr3/9a7PqW7hwIW3btm3hKJvGI7dmZmZmX2LbbLMNBxxwABdffDHnnXceRx11FBdccAE77LADvXv3Zty4cQBUV1ez22670adPH/r06cMjjzwCwIMPPsgee+zBkUceybbbblvJrgAeuTUzMzP70vvpT39Knz59aN++Pfvvvz977rkn119/Pe+++y477rgje+21F506deK+++6jQ4cOvPTSSxxxxBE8+eSTADz++ONMmzatSY/sWlac3JqZmZl9ya222moMHDiQ1VdfnVGjRnH33Xdz6aWXAunxY6+++ipdunThhBNO4Omnn6Zt27a8+OKLi7bfcccdV4jEFpzcmpmZmRnQpk0b2rRpQ0QwZswYtthiiyXWn3vuuXTu3JlnnnmGzz//nA4dOixat9pqqy3vcOvkObdmZmZmtsjee+/NVVddRUQAMGXKFADee+89qqqqaNOmDTfeeCMLFy6sZJh1cnJrZmZmZoucffbZLFiwgJ49e7LNNttw9tlnA/CDH/yAESNGsNNOO/Hiiy+uUKO1pVSTlZuZ2fK32n9tHFsefV6lw2gW/4Uys+Vv+vTp9OjRo9JhLFfl+ixpckT0LVfeI7dmZmZmVhhObs3MzMysMJzcmpmZmVlhOLk1MzMzs8JwcmtmZmZmheHk1szMzMwKw3+hzMzMzKyV2v7UkS1aX0OP+Js5cyaDBw/m9ddfp02bNhx//PGcfPLJvP322wwcOJDq6mq6d+/OqFGjWHvttZk3bx6HHnooTzzxBEOHDuXqq69eVNdtt93GBRdcwMKFC9lvv/34xS9+0SJ98MitmZmZmTVKu3bt+OUvf8n06dOZNGkS11xzDc8//zzDhw+nf//+vPTSS/Tv35/hw4cD0KFDB84//3wuvfTSJeqZN28ep556KhMmTOC5555j7ty5TJgwoWVibJFazMysWTZp+zp3dryk0mE0y6s/Wxx3t3OmVjASM1teqqqqqKqqAqBjx4706NGD2bNnM27cOB588EEAhgwZwu67787FF1/Maqutxq677srLL7+8RD0zZsxg8803Z/311wdgr732YsyYMfTv33+pY/TIrZmZmZk1WXV1NVOmTKFfv37MnTt3UdJbVVXFG2+8Ue+2m266KS+88ALV1dV89tlnjB07lpkzZ7ZIXB65NTMzM7MmmT9/PgMGDODyyy9njTXWaPL2a6+9Ntdeey0DBw6kTZs2fPWrX2XGjBktEptHbs3MzMys0RYsWMCAAQMYNGgQhxxyCACdO3dmzpw5AMyZM4dOnTo1WM8BBxzAY489xqOPPsoWW2zBZptt1iLxObk1MzMzs0aJCI499lh69OjBKaecsmj5gQceyIgRIwAYMWIEBx10UIN11UxdeOedd/j1r3/Ncccd1yIxelqCmZmZWSvV0KO7WtrEiRO58cYb2XbbbenVqxcAF154IcOGDeOwww7jD3/4A926dWP06NGLtunevTvvv/8+n376KWPHjmX8+PFstdVWnHzyyTzzzDMAnHPOOWy++eYtEmODya2khcBUQMBC4ISIeKRFWm8CSbsDP46I/Zd329byJD1IOp5PNrL8UGB8RLyW31cDfSPirWUVY5kYWqRNSWsBR0bEr1sirnraORDYKiKGN2PbMyLiwpL3j0TEVyV1B74aEbc0t46mxrI85POxCvgEaA/8P+CsiHi3mXU1+tw2M2tNdt11VyKi7Lq6HuVVXV1ddvmtt97aUmEtoTHTEj6KiF4RsR1wOnDRMomklZDk0e7KGAp0acoGK/CxWgv4wbJuJCLuak5im51Rq66apLQ7cORS1rGiGhQRPYGepCR3XIXjMTOzZmjqnNs1gHdq3kg6VdITkp6VdF5edr6kk0vKXCDpJCWXSJomaaqkgXn97pIelHS7pBck3SxJed0387KHgUPKBSRpqKSxku6W9IqkEySdImmKpEmS1pG0iaSnSrbZTNLkMnXtkPvyaE2sJW2MlnQ3MD7XOTaXnSSpZy53rqQfl9Q3TVL3/O8FSSPyNrdLWrW+HS3pBknXSnpA0gxJX5d0vaTpkm4oKXetpCclPVdzDPLyaknnSXoq7+8tJbWR9JKk9XOZNpJelrRerbbPlXSjpPtz+e/Wd8zz8lNyf6dJ+mFe1qh+S/pG3udP5f28eq31hwJ9gZslPS1plbzqxNL+lcT+O0njgZGSNpI0Ibc/QVK3kv17aEkb80v2ya/z/rxH0l9Ky9XRZpPOB2A4sEnuyxIPOC3ZZ9fl8jdL2kvSxHwsdmzCcRwq6eqS/l4p6ZF8Ph2al1dJeijHMk3SbpKGA6vkZTeX7p8c+2553Y9K28jl7lH6ma6zDiVN+iyo1a8HJfXNr9dTGlFH0taSHs9tPitps7z8qJLlv5XUtnadpSLiU+AnQDdJ2+U6xkqanM+L4/Oytnm/1vTjR7XibKN07v+8vvbMzKxlNSa5rfkF9QJwHXA+pIQE2AzYEegFbC/pa8AfgCG5TBvgcOBmUnLaC9gO2Au4RFJVbqM38ENgK+ArwC6SOgC/Bw4AdgP+q54YtyGNJu0IXAD8JyJ6A48CgyPiX8B7knrl8scAN5Sp54/A9yNiZ9IUjFI7A0MiYk/gPGBKHuU5A2jM377bAvhd3uZ9GjdytzawJ/Aj4G7gMmBrYNuSvpwZEX1Jo01fr0mssrciog9wLeky6efATcCgvH4v4Jk6LrP3BPbL/T5HUpe6jrmk7Un7tB+wE/BdSb0b0++ckJ0F7JVjfRI4pbRMRNyelw/KVxE+Kte/kk22Bw6KiCOBq4GRuf2bgSvL9LXUIaTRyW2B43L/S5Vrs6nnwzDgX7kvp5ZZvylwBekYbEk6t3fN7Z3RxONYqirXsz8pSSXX/beI6EX62Xw6Ioax+IrNoFp1DAP+kdddVldDDdTRpM+CBvpU6vvAFbkvfYFZknoAA4Fd8vKFLN5vdYqIhcAzpP0P8J2I2D7Xe5KkdXMfNoiIbSJiW9LnR412pPPtxYg4qwl9MDOzpdSUaQlbAt8kjYYJ+Eb+NwV4ivRLYLOIqAbm5eTmG6Rf+vNIv1RvjYiFETEX+DuwQ27j8YiYlX9pP01KLrYEXomIlyJN7ripnhgfiIgPIuJN4D1SIghprnD3/Po64Jg8ajMQWGLOoNI8yI4l84lrzym8LyLezq93BW4EiIj7gXUlrVlPfAAzI2Jifn1TrqMhd+e+TwXmRsTUvI+eK+nXYUqj0lNIie9WJdvfkf+fXFL+eqBm9vl3WPIXcqlxEfFRTpgeICW0ZY957sudEfFhRMzP7e7WyH7vlGOeKOlp0hejjerZJ6XK9Q/grpIEeGcWH8sby7Rf267A6Ij4PCJeJ/W9oTabcz7U55Vax3pCyXlQ02Zjj2OpsblfzwOd87InSD8X5wLbRsQHSxF3YzX1s6CxHgXOkHQasFE+B/qTvuw8kc+v/qSkuTFKR41PkvQMMAnYkHTezwC+IukqSd8kfXmr8VtgWkRcULZi6XilKy5Pvv1h7e/RZma2NJo0LSEiHgXWA9YnffBflBPfXhGxaUT8IRe9jjRH8hjSL2FY8hdFbZ+UvF7I4hvdys9Yrn/7z0vef15S1xhgH9Ko1eSccJeqLz6ADxsoG8BnLLlPO9RaX7t8Q0r7UbuP7SRtTBrN659HDf9cq82abRbt04iYCcyVtCdppPXeOtouF29dx7y+fddQv0X64lBT51YRcWw99ZX6Qv+yD8uUrd3+omOVv6y1L4mnqW0253xoTBtQx/nchONYV73K9TwEfA2YDdwoqam33Tanj835LKirzUXt5ZvcDgQ+Av6W942AESXn1xYRcW6DAaYvwdsC05VuZt0L2DnfezAF6BAR75BGnx8E/pf0uVfjEWCPfAXqCyLidxHRNyL6rrNavbMkzMysiZqU3CrNMWwLzAP+BnxHeX6kpA0k1Tyx907SKO8OuRzAQ8DAPE9tfdIv1Mfrae4FYGNJm+T3RzQl1toi4uMcy7WUGeXKv6g+kLRTXnR4PdU9RL60mX/xvRUR7wPVQJ+8vA+wcck23STVXOI+Ang4l7tI0sHN6lSaA/0hacpFZ1Ly3hjXkUZRR+XLr+UcJKlDvvy6O2mEr65j/hDwLUmrSloNOBj4R66nbL9LTCJNQ9k017mqpHLPAvkA6NjI/pV6hMXHclBJ+9WkET2Ag4CV8uuHgQF5vmRnUt8b0tTzobl9qa0xx7FekjYC3oiI35OmFPXJqxZIWqnMJrVjrwZ65f21IWmEv0ZddTT1s6C2ahYfu9J5018BZkTElcBdpGkdE4BDaz6blOZH13tlIMd8Eemqw7PAmsA7EfGf/Bm4Uy63HtAmIsYAZ7N430Hal38BRmvFvbHRzKyQGvOhu0q+nAdpFGRI/kU6Ps9nezQNfDEfOIr0i/JTSQ8A75b80r2TdIn4GdKo1k8i4vX8y+ILIuLjfOPGnyW9RUo6tmlWLxermfs7vo71xwK/l/QhaTTmvTrKnQv8UdKzwH/Ic4xJo8OD8/56AnixZJvpwBBJvwVeIiXZkEaH7mpGX4iIZyRNIV26ngFMbGCTGneREvz6LmU/ThoJ7gacH+kRXK+VO+YR8ZTSTW41Ccp1ETFF6eapuvpd04c3lR7zdauklfPis1hy30GaI/0bSR/xxXmw9TkJuF7SqcCbpKsJkOZzj5P0OCkBqhntHUO6dD0tx/AYdZ8HNc6lCedDRMxTukFsGnBvHfNuG6Mxx7EhuwOnSlpAOp41I7e/A56V9FStObPPAp/lS/Q3AJcDr5CmTEwjTVehgTqa9FlQxqXAKElHA/eXLB8IHJX78jrws4h4W9JZpM+rNsAC0ijrv8vUe7OkT4CVSY8Cq3kC+V+B7+fj+0/SFzKADUjHvWaQ4PTSyiLiV3l6yo2SBuWpFmZmLerVn23bovV1O2dqvetnzpzJ4MGDef3112nTpg3HH388J598Mm+//TYDBw6kurqa7t27M2rUKNZee23uu+8+hg0bxqeffkr79u255JJL2HPPPQGYPHkyQ4cO5aOPPmLffffliiuuQF+8j7jJFHU8q2ypKk0f9k8B346Il1q8gWZSunN9zYg4u471q+c5o0gaBlRFxMnlyjax3e7APRHxheRc0t8iYu+lbaOJ8fQFLouI3epYfy4wPyIuXcp2ulNHv1dkNedBHrV+nHQz0uuVjqu2ho6jtQ49N1gl7vneppUOY6k19AvRzFrG9OnT6dGjx6L3yzu5nTNnDnPmzKFPnz588MEHbL/99owdO5YbbriBddZZh2HDhjF8+HDeeecdLr74YqZMmULnzp3p0qUL06ZNY++992b27NkA7LjjjlxxxRXstNNO7Lvvvpx00knss88XL0LX7jOApMmRbqj/ghb/87uStgJeJt0EsyIltneSRqWuqKfYfsqPRCLdELXMH+FTgcR2GGlE8fSGyn6J3ZNHW/9BGrVeERNbH0czM1vuqqqq6NMnzcLq2LEjPXr0YPbs2YwbN44hQ9KFyyFDhjB27FgAevfuTZcu6TH1W2+9NR9//DGffPIJc+bM4f3332fnnXdGEoMHD160zdJq8blg+U7sxt6NvNxERIPzWiPiNuC2ZdB2NUs/paJFRHqof70P9m/MDTeNbKuaFaTfTRERu1c6hoY05jiamZktS9XV1UyZMoV+/foxd+5cqqrSUx2rqqp44403vlB+zJgx9O7dm5VXXpnZs2fTtWvXReu6du26aER3aflGBzMzMzNrkvnz5zNgwAAuv/xy1lhjjQbLP/fcc5x22mmMH59ueyo3LbYl5tvCMpiWYGZmZmbFtWDBAgYMGMCgQYM45JD0B2Q7d+7MnDlzgDQvt1OnTovKz5o1i4MPPpiRI0eyySbpIVhdu3Zl1qxZS5Spmb6wtDxya2ZWQTPatuWItRse9VjhXdWUPya37Ew8sbEPjTGz5ogIjj32WHr06MEppyz+g6IHHnggI0aMYNiwYYwYMYKDDkoPnHn33XfZb7/9uOiii9hll8WfE1VVVXTs2JFJkybRr18/Ro4cyYknntgiMS6TpyWYmVnjrN5t9dju1O0qHUZhOLm1oiv35IDl6eGHH2a33XZj2223pU2bNAHgwgsvpF+/fhx22GG8+uqrdOvWjdGjR7POOuvw85//nIsuuojNNttsUR3jx4+nU6dOPPnkk4seBbbPPvtw1VVXlZ2a0NSnJTi5NTOrICe3LcvJrRVdpZPbSqj4o8DMzMzMzCrFya2ZmZmZFYaTWzMzMzMrDCe3ZmZmZlYYTm7NzMzMrDCc3JqZmZlZYfiPOJiZmZm1Uru08B9QaehxejNnzmTw4MG8/vrrtGnThuOPP56TTz6Zt99+m4EDB1JdXU337t0ZNWoUa6+9Nvfddx/Dhg3j008/pX379lxyySXsueeeAJx55pmMHDmSd955h/nz57dYHzxya2ZmZmaN0q5dO375y18yffp0Jk2axDXXXMPzzz/P8OHD6d+/Py+99BL9+/dn+PDhAKy33nrcfffdTJ06lREjRnD00UcvquuAAw7g8ccfb/EYndyamZmZWaNUVVXRp08fADp27EiPHj2YPXs248aNY8iQIQAMGTKEsWPHAtC7d2+6dOkCwNZbb83HH3/MJ598AsBOO+1EVVVVi8fo5NbMzMzMmqy6upopU6bQr18/5s6duyhRraqq4o033vhC+TFjxtC7d29WXnnlZRqX59yamZmZWZPMnz+fAQMGcPnll7PGGms0WP65557jtNNOY/z48cs8No/cmpmZmVmjLViwgAEDBjBo0CAOOeQQADp37sycOXMAmDNnDp06dVpUftasWRx88MGMHDmSTTbZZJnH5+TWzMzMzBolIjj22GPp0aMHp5xyyqLlBx54ICNGjABgxIgRHHTQQQC8++677Lffflx00UXsskvLPtmhLoqI5dKQmZl90erdVo/tTt2u0mEURkOPMTJr7aZPn06PHj0q1v7DDz/MbrvtxrbbbkubNmmM9MILL6Rfv34cdthhvPrqq3Tr1o3Ro0ezzjrr8POf/5yLLrqIzTbbbFEd48ePp1OnTvzkJz/hlltu4bXXXqNLly4cd9xxnHvuuV9os1yfJU2OiL7lYnRya2ZWQU5uW5aTWyu6Sie3ldDU5NbTEszMzMysMJzcmpmZmVlh+FFgZmYVtGWnLX0p3cyaJCKQVOkwlovmTJ/1yK2ZmZlZK9GhQwfmzZvXrKSvtYkI5s2bR4cOHZq0nUduzczMzFqJrl27MmvWLN58881Kh7JcdOjQga5duzZpGye3ZmZmZq3ESiutxMYbb1zpMFZonpZgZmZmZoXh5NbMzMzMCsPJrZmZmZkVhv9CmZlZBUn6APhnpeNoYesBb1U6iBbk/qzYitYfKF6flkV/NoqI9cut8A1lZmaV9c+6/oRkayXpySL1yf1ZsRWtP1C8Pi3v/nhagpmZmZkVhpNbMzMzMysMJ7dmZpX1u0oHsAwUrU/uz4qtaP2B4vVpufbHN5SZmZmZWWF45NbMzMzMCsPJrZmZmZkVhpNbM7MKkfRNSf+U9LKkYZWOp6kkbSjpAUnTJT0n6eS8fB1J90l6Kf+/dqVjbQpJbSVNkXRPft/a+7OWpNslvZCP1c6tuU+SfpTPt2mSbpXUoTX1R9L1kt6QNK1kWZ3xSzo9f0b8U9LelYm6fnX06ZJ8zj0r6U5Ja5WsW6Z9cnJrZlYBktoC1wD7AFsBR0jaqrJRNdlnwP9FRA9gJ+B/cx+GARMiYjNgQn7fmpwMTC9539r7cwXw14jYEtiO1LdW2SdJGwAnAX0jYhugLXA4ras/NwDfrLWsbPz55+lwYOu8za/zZ8eK5ga+2Kf7gG0ioifwInA6LJ8+Obk1M6uMHYGXI2JGRHwK/Ak4qMIxNUlEzImIp/LrD0hJ0wakfozIxUYA36pIgM0gqSuwH3BdyeLW3J81gK8BfwCIiE8j4l1acZ9If4BqFUntgFWB12hF/YmIh4C3ay2uK/6DgD9FxCcR8QrwMumzY4VSrk8RMT4iPstvJwFd8+tl3icnt2ZmlbEBMLPk/ay8rFWS1B3oDTwGdI6IOZASYKBTBUNrqsuBnwCflyxrzf35CvAm8Mc81eI6SavRSvsUEbOBS4FXgTnAexExnlbanxJ1xV+Uz4nvAPfm18u8T05uzcwqQ2WWtcpnM0paHRgD/DAi3q90PM0laX/gjYiYXOlYWlA7oA9wbUT0Bj5kxb5kX688F/UgYGOgC7CapKMqG9Uy1eo/JySdSZrCdHPNojLFWrRPTm7NzCpjFrBhyfuupMurrYqklUiJ7c0RcUdePFdSVV5fBbxRqfiaaBfgQEnVpGkie0q6idbbH0jn2ayIeCy/v52U7LbWPu0FvBIRb0bEAuAO4Ku03v7UqCv+Vv05IWkIsD8wKBb/YYVl3icnt2ZmlfEEsJmkjSW1J91gcVeFY2oSSSLN5ZweEb8qWXUXMCS/HgKMW96xNUdEnB4RXSOiO+l43B8RR9FK+wMQEa8DMyVtkRf1B56n9fbpVWAnSavm868/aa53a+1Pjbrivws4XNLKkjYGNgMer0B8TSbpm8BpwIER8Z+SVcu8T/4LZWZmFSJpX9Icz7bA9RFxQWUjahpJuwL/AKayeI7qGaR5t6OAbqRk5NsRUfsGmhWapN2BH0fE/pLWpRX3R1Iv0g1y7YEZwDGkwa1W2SdJ5wEDSZe6pwDHAavTSvoj6VZgd2A9YC7wU2AsdcSfL+t/h9TfH0bEvV+stbLq6NPpwMrAvFxsUkR8P5dfpn1ycmtmZmZmheFpCWZmZmZWGE5uzczMzKwwnNyamZmZWWE4uTUzMzOzwnBya2ZmZmaF4eTWzMzMloqkH0patdJxmIEfBWZmZmZLKf9Vt74R8ValYzHzyK2ZmdmXgKTBkp6V9IykGyVtJGlCXjZBUrdc7gZJh5ZsNz//v7ukByXdLukFSTcrOQnoAjwg6YHK9M5ssXaVDsDMzMyWLUlbA2cCu0TEW5LWAUYAIyNihKTvAFcC32qgqt7A1sBrwMRc35WSTgH28MitrQg8cmtmZlZ8ewK31ySf+U+77gzcktffCOzaiHoej4hZEfE58DTQveVDNVs6Tm7NzMyKT0BDN9nUrP+MnB9IEtC+pMwnJa8X4ivAtgJycmtmZlZ8E4DDJK0LkKclPAIcntcPAh7Or6uB7fPrg4CVGlH/B0DHlgrWbGn4G5eZmVnBRcRzki4A/i5pITAFOAm4XtKpwJvAMbn474Fxkh4nJcUfNqKJ3wH3SpoTEXu0fA/MGs+PAjMzMzOzwvC0BDMzMzMrDCe3ZmZmZlYYTm7NzMzMrDCc3JqZmZlZYTi5NTMzM7PCcHJrZmZmZoXh5NbMzMzMCuP/A7zQGDpsXCe/AAAAAElFTkSuQmCC\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "q = 'Do you use Dask as part of a larger group?'\n", "ax = sns.countplot(y=q, hue=\"Year\", data=df.reset_index());\n", "ax.set(ylabel=\"\", title=q);" ] }, { "cell_type": "markdown", "id": "65654498-ff04-41b4-b1cb-5ae3a7308eaf", "metadata": {}, "source": [ "### What industry do you work in?\n", "\n", "There was a wide variety of industries represented in the survey.\n", "\n", "Almost half of responses were in an industry related to science, academia, or a governmant laboratory. Geoscicence had the most responses, while life sciences, physics, and astronomy were also popular fields.\n", "\n", "Around 30 percent of responses were from people in businesss and tech. Of these, there was a roughly even split between people in accounting/finance/insurance vs other tech workers.\n", "\n", "Around 10 percent of responses belonged to manufacturing, engineering, and other industry (energy, aerospace, etc). The remaining responses were difficult to categorise." ] }, { "cell_type": "code", "execution_count": 6, "id": "508967cd-4ac8-4773-bd80-861422625586", "metadata": { "execution": { "iopub.execute_input": "2022-07-27T19:24:36.653001Z", "iopub.status.busy": "2022-07-27T19:24:36.651957Z", "iopub.status.idle": "2022-07-27T19:24:36.831402Z", "shell.execute_reply": "2022-07-27T19:24:36.830910Z" } }, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "q = \"What industry do you work in?\" # New question in 2021\n", "data = df2021[q].dropna().str.split(\";\").explode().to_frame()\n", "order = data.value_counts()[data.value_counts() > 1].keys().get_level_values(0)\n", "ax = sns.countplot(y=q, data=data, order=order);\n", "ax.set(ylabel=\"\", title=q);" ] }, { "cell_type": "markdown", "id": "b74e6612-9eea-4d02-8323-22636c445e73", "metadata": {}, "source": [ "### How easy is it for you to upgrade to newer versions of Python libraries?\n", "\n", "The majority of users are able to easily upgrade to newer versoins of python libraries when they want." ] }, { "cell_type": "code", "execution_count": 7, "id": "079e6d4c-a41e-480c-bd78-9d25e0ade2fb", "metadata": { "execution": { "iopub.execute_input": "2022-07-27T19:24:36.834672Z", "iopub.status.busy": "2022-07-27T19:24:36.834225Z", "iopub.status.idle": "2022-07-27T19:24:36.935543Z", "shell.execute_reply": "2022-07-27T19:24:36.935063Z" } }, "outputs": [ { "data": { "image/png": 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RVV9NsguwQ1Vt6ja0uW26+mouespTx/HVkjQ2T/36RZ1du83CNP8ROBv4+6ZoGfDpziKSJPWqTdfQycDhwK0AVfVDYN8ug5Ik9adNIvh1Vd05s5NkBwbzCCRJE6BNIrgoyV8CuyT5feCTDJarlCRNgDaJ4LXAjcD3gP8EfAF4fZdBSZL6s+Cooaq6F3hf85IkTZhRTx/9HiPuBVTVwZ1EJEnq1agWwXN6i0KSNDbzJoKquqbPQCRJ49FmQtlhSb6V5LYkdya5J8mtfQQnSepem1FD7waOBX4I7AL8KfC3XQYlSepPq2cNVdX6JNtX1T3AB5P8Y8dxSZJ60iYR3JFkJ+A7Sd4KbAR26zYsSVJf2nQNHd+c9zLgdmB/4N91GZQkqT9tWgQ3AXdW1a+ANybZHnhAt2FJkvrSpkVwPrDr0P4uwFe7CUeS1Lc2iWDnqrptZqfZ3nXE+ZKkRaRNIrg9ySEzO0kOBX7Z9guSbJ/k20k+N8exJDktyfoklw9/jySpH23uEbwK+GSS65v9pcALNuM7XgmsAx44x7EjgRXN63eB9zbvkqSetHn66LeSPBJ4BBDgqqq6q83FkywDng28CXj1HKccA6yuqgIuSbIkydKq2ti6BpKkrTJv11CSJyZ5CEDzw38I8N+BtyfZq+X13wm8Brh3nuP7AdcN7W9oyiRJPRl1j+DvgTsBkjwFeAuwGrgFWLXQhZM8B7ihqtaOOm2Osvs8+jrJSUnWJFlzy12tGiOSpJZGJYLtq+rmZvsFwKqqOqeq/gp4eItrHw4cneQnwMeBI5J8eNY5GxhMUJuxDLh+1jlU1aqqWllVKx+0444tvlqS1NbIRNAsVA/wDOCCoWNt7i2cWlXLqmo58ELggqo6btZp5wEnNKOHDgNu8f6AJPVr1A/6xxgsXH8Tg+Gi/xsgycMZdA9tkSQvBaiq0xmsf3wUsB64AzhxS68rSdoyoxameVOS8xkMF/2HZmQPDFoRL9+cL6mqC4ELm+3Th8oLOHnzQpYkbUsju3iq6pI5yn7QXTiSpL61mVksSZpgJgJJmnImAkmaciYCSZpyJgJJmnImAkmaciYCSZpyJgJJmnImAkmaciYCSZpyJgJJmnImAkmaciYCSZpyJgJJmnImAkmacgsuOXl/s8cjHsFTv37RuMOQpIlhi0CSppyJQJKmnIlAkqaciUCSppyJQJKmXKpq3DFsliSbgKvHHccY7A3cNO4gemadp8M01hn6r/dDq2qfuQ4suuGjwNVVtXLcQfQtyZppq7d1ng7TWGe4f9XbriFJmnImAkmacosxEawadwBjMo31ts7TYRrrDPejei+6m8WSpG1rMbYIJEnbkIlAkqbcokoESZ6V5Ook65O8dtzxdCHJ/km+lmRdkiuTvLIp3yvJV5L8sHnfc9yxbmtJtk/y7SSfa/anoc5Lkpyd5Krm3/xJk17vJH/e/Ld9RZKPJdl50uqc5IwkNyS5Yqhs3jomObX5Xbs6yb/pO95FkwiSbA+8BzgSeDRwbJJHjzeqTtwN/EVVPQo4DDi5qedrgfOragVwfrM/aV4JrBvan4Y6vwv4UlU9Engcg/pPbL2T7Ae8AlhZVY8FtgdeyOTV+UPAs2aVzVnH5v/vFwKPaT7zd83vXW8WTSIA/hWwvqr+uaruBD4OHDPmmLa5qtpYVZc125sY/DDsx6CuZzannQn827EE2JEky4BnA+8fKp70Oj8QeArwAYCqurOqfsGE15vBRNZdkuwA7Apcz4TVuaq+Dtw8q3i+Oh4DfLyqfl1VPwbWM/i9681iSgT7AdcN7W9oyiZWkuXAE4BvAr9VVRthkCyAfccYWhfeCbwGuHeobNLrfBBwI/DBpkvs/Ul2Y4LrXVX/AvwNcC2wEbilqv6BCa7zkPnqOPbftsWUCDJH2cSOfU2yO3AO8KqqunXc8XQpyXOAG6pq7bhj6dkOwCHAe6vqCcDtLP4ukZGafvFjgAOB3wZ2S3LceKMau7H/ti2mRLAB2H9ofxmDJuXESbIjgyTwkao6tyn+WZKlzfGlwA3jiq8DhwNHJ/kJgy6/I5J8mMmuMwz+m95QVd9s9s9mkBgmud7PBH5cVTdW1V3AucDvMdl1njFfHcf+27aYEsG3gBVJDkyyE4ObK+eNOaZtLkkY9Bmvq6p3DB06D3hxs/1i4DN9x9aVqjq1qpZV1XIG/64XVNVxTHCdAarqp8B1SR7RFD0D+D6TXe9rgcOS7Nr8t/4MBvfBJrnOM+ar43nAC5M8IMmBwArg0l4jq6pF8wKOAn4A/Ah43bjj6aiOT2bQLLwc+E7zOgp4MIORBj9s3vcad6wd1f9pwOea7YmvM/B4YE3z7/1pYM9JrzfwRuAq4ArgLOABk1Zn4GMM7oHcxeAv/j8ZVUfgdc3v2tXAkX3H6yMmJGnKLaauIUlSB0wEkjTlTASSNOVMBJI05UwEkjTlTATSGCR5VZJdxx2HBK5QJo1FM4t6ZVXdNO5YJFsE0jySnJDk8iTfTXJWkocmOb8pOz/JAc15H0ryvKHP3da8Py3JhUPrDXwkA69g8JydryX52nhqJ/3GDuMOQLo/SvIYBrM9D6+qm5LsxeDRwaur6swkLwFOY+HHJT+BwXPmrwcubq53WpJXA0+3RaD7A1sE0tyOAM6e+aGuqpuBJwEfbY6fxeBxIAu5tKo2VNW9DB4XsnzbhyptHROBNLew8KOAZ47fTfP/UvMgtZ2Gzvn10PY92ArX/ZCJQJrb+cDzkzwYBuvNAv/I4OmoAC8CvtFs/wQ4tNk+BtixxfU3AXtsq2ClreFfJ9IcqurKJG8CLkpyD/BtBmvtnpHkFAYri53YnP4+4DNJLmWQQG5v8RWrgC8m2VhVT9/2NZDac/ioJE05u4YkacqZCCRpypkIJGnKmQgkacqZCCRpypkIJGnKmQgkacr9X7uzZCehQGRxAAAAAElFTkSuQmCC\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "q = \"How easy is it for you to upgrade to newer versions of Python libraries\"\n", "sns.countplot(y=q, data=df2021[q].dropna().explode().to_frame()).set_ylabel('Scale from 1 (Difficult) to 4 (Easy)');" ] }, { "cell_type": "markdown", "id": "0f26cc8f-7efa-4320-9f38-5e364416a51e", "metadata": {}, "source": [ "## How people like to use Dask " ] }, { "cell_type": "markdown", "id": "f8936f7a-f788-483f-a640-892deed37895", "metadata": {}, "source": [ "\n", "People like to use Dask in conjunction with numpy and pandas, along with a range of other python libraries.\n", "The most popular Dask APIs are [Dask Dataframes](https://docs.dask.org/en/latest/dataframe.html), [Dask Delayed](https://docs.dask.org/en/latest/delayed.html), and [Dask Arrays](https://docs.dask.org/en/latest/array.html).\n", "\n", "The vast majority of people like to use Dask interactively with Jupyter or IPython at least part of the time, and most people view the [Dask Dashboard](https://docs.dask.org/en/latest/diagnostics-distributed.html) with a web browser.\n" ] }, { "cell_type": "markdown", "id": "5bd6b0f8-5b46-4a61-b283-2fe3cac4453d", "metadata": {}, "source": [ "### What are some other libraries that you often use with Dask?\"\n", "\n", "The ten most common libraries people use with Dask are: `numpy`, `pandas`, `xarray`, `scikit-learn`, `scipy`, `statsmodels`, `matplotlib`, `xgboost`, `numba`, and `joblib`.\n" ] }, { "cell_type": "code", "execution_count": 8, "id": "91878b91-2fa0-404e-8e7f-9c089f20defc", "metadata": { "execution": { "iopub.execute_input": "2022-07-27T19:24:36.939159Z", "iopub.status.busy": "2022-07-27T19:24:36.937916Z", "iopub.status.idle": "2022-07-27T19:24:37.080612Z", "shell.execute_reply": "2022-07-27T19:24:37.080113Z" } }, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "q = \"What are some other libraries that you often use with Dask?\"\n", "data = df2021[q].dropna().str.lower().str.split(\", \").explode().to_frame()\n", "labels = pd.value_counts(data[q]).iloc[:10].index\n", "sns.countplot(y=q, data=data, order=labels).set_ylabel('');" ] }, { "cell_type": "markdown", "id": "80679b24-b6ec-462c-9ac1-03f1d283ee72", "metadata": {}, "source": [ "## Dask APIs\n", "\n", "The three most popular Dask APIs people use are:\n", "1. [Dask Dataframes](https://docs.dask.org/en/latest/dataframe.html)\n", "2. [Dask Delayed](https://docs.dask.org/en/latest/delayed.html)\n", "3. [Dask Arrays](https://docs.dask.org/en/latest/array.html)\n", "\n", "In 2021, we saw a small increase in the number of people who use [dask delayed](https://docs.dask.org/en/latest/delayed.html), compared with previous years. This might be a good thing, it's possible that as people develop experience and confidence with Dask, they are more likely to start using more advanced features such as [delayed](https://docs.dask.org/en/latest/delayed.html). Besides this change, preferences were pretty simliar to the results from previous years." ] }, { "cell_type": "code", "execution_count": 9, "id": "8c49e423-23a9-40cc-9e99-cc5d7bac36f7", "metadata": { "execution": { "iopub.execute_input": "2022-07-27T19:24:37.084974Z", "iopub.status.busy": "2022-07-27T19:24:37.083925Z", "iopub.status.idle": "2022-07-27T19:24:37.241116Z", "shell.execute_reply": "2022-07-27T19:24:37.240619Z" } }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "apis = df2021['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\", data=apis);" ] }, { "cell_type": "markdown", "id": "bc24feb8-aa37-44a5-b5ff-5440b1f84d1e", "metadata": {}, "source": [ "### Interactive or Batch?\n", "\n", "The vast majority of people like to use Dask interactively with Jupyter or IPython at least part of the time. Less than 15% of Dask users only use Dask in batch mode (submitting scripts that run in the future)." ] }, { "cell_type": "code", "execution_count": 10, "id": "e7e0d37f-ac0d-4045-9012-ac79e86328ff", "metadata": { "execution": { "iopub.execute_input": "2022-07-27T19:24:37.245489Z", "iopub.status.busy": "2022-07-27T19:24:37.244418Z", "iopub.status.idle": "2022-07-27T19:24:37.340656Z", "shell.execute_reply": "2022-07-27T19:24:37.340160Z" } }, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "q = 'Interactive or Batch?'\n", "data = df2021[q].dropna()\n", "data = data.str.replace('Interactive: I use Dask with Jupyter or IPython when playing with data, Batch: I submit scripts that run in the future', \"Interactive and Batch\")\n", "data = data.str.replace('Interactive: I use Dask with Jupyter or IPython when playing with data', \"Interactive\")\n", "data = data.str.replace('Batch: I submit scripts that run in the future', \"Batch\")\n", "order = [\"Interactive and Batch\", \"Interactive\", \"Batch\"]\n", "sns.countplot(y=q, data=data.explode().to_frame(), order=order).set_ylabel('');" ] }, { "cell_type": "markdown", "id": "beaafc3f-cd93-4087-8d4e-cf08305a3576", "metadata": {}, "source": [ "### How do you view Dask's dashboard?\n", "\n", "Most people look at the Dask dashboard using a web browser. A smaller group use the [dask jupyterlab extension](https://github.com/dask/dask-labextension).\n", "\n", "A few people are still not sure what the dashboard is all about. If that's you too, you might like to watch [this 20 minute video](https://youtu.be/N_GqzcuGLCY) that explains why the dashboard is super useful, or see the rest of the docs [here](https://docs.dask.org/en/latest/diagnostics-distributed.html)." ] }, { "cell_type": "code", "execution_count": 11, "id": "4bbdccc2-2a75-419a-aed5-2199ddefcc29", "metadata": { "execution": { "iopub.execute_input": "2022-07-27T19:24:37.344982Z", "iopub.status.busy": "2022-07-27T19:24:37.343934Z", "iopub.status.idle": "2022-07-27T19:24:37.536454Z", "shell.execute_reply": "2022-07-27T19:24:37.535946Z" } }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "q = \"How do you view Dask's dashboard?\"\n", "ax = sns.countplot(y=q, data=df2021[q].dropna().str.split(\", \").explode().to_frame());\n", "ax.set(ylabel=\"\", title=q);" ] }, { "cell_type": "markdown", "id": "4113e0cc-f26b-4b68-81d6-7e991347bce5", "metadata": {}, "source": [ "### Local machine or Cluster?\n", "\n", "Roughly two thirds of respondants use a computing cluster at least part of the time." ] }, { "cell_type": "code", "execution_count": 12, "id": "69da5136-23bc-449a-b0b8-1937ae2c7e74", "metadata": { "execution": { "iopub.execute_input": "2022-07-27T19:24:37.540802Z", "iopub.status.busy": "2022-07-27T19:24:37.539754Z", "iopub.status.idle": "2022-07-27T19:24:37.549999Z", "shell.execute_reply": "2022-07-27T19:24:37.549547Z" } }, "outputs": [ { "data": { "text/plain": [ "Year\n", "2019 0.654902\n", "2020 0.666667\n", "2021 0.630081\n", "Name: Local machine or Cluster?, dtype: float64" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "q = 'Local machine or Cluster?'\n", "df[q].dropna().str.contains(\"Cluster\").astype(int).groupby(\"Year\").mean()" ] }, { "cell_type": "code", "execution_count": 13, "id": "b7aeb59a-147d-495f-bf2e-318bbb2025d7", "metadata": { "execution": { "iopub.execute_input": "2022-07-27T19:24:37.554059Z", "iopub.status.busy": "2022-07-27T19:24:37.553007Z", "iopub.status.idle": "2022-07-27T19:24:37.677406Z", "shell.execute_reply": "2022-07-27T19:24:37.676866Z" } }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "q = 'Local machine or Cluster?'\n", "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", "ax = sns.countplot(y=q, data=df2021[q].dropna().str.split(\", \").explode().to_frame(), order=order);\n", "ax.set(ylabel=\"\", title=q);" ] }, { "cell_type": "markdown", "id": "4e59c698-8438-496a-ad77-9a1be33d649c", "metadata": {}, "source": [ "#### If you use a cluster, how do you launch Dask?\n", "\n", "SSH is the most common way to launch Dask on a compute cluster, followed by a HPC resource manager, then Kubernetes." ] }, { "cell_type": "code", "execution_count": 14, "id": "ee6c2ea8-2ef5-44c2-96e5-658d2de0927f", "metadata": { "execution": { "iopub.execute_input": "2022-07-27T19:24:37.681878Z", "iopub.status.busy": "2022-07-27T19:24:37.680804Z", "iopub.status.idle": "2022-07-27T19:24:37.838541Z", "shell.execute_reply": "2022-07-27T19:24:37.838035Z" } }, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "q = \"If you use a cluster, how do you launch Dask? \"\n", "data = df2021[q].dropna()\n", "data = data.str.replace(\"HPC resource manager (SLURM, PBS, SGE, LSF or similar)\", \"HPC resource manager (SLURM PBS SGE LSF or similar)\", regex=False)\n", "data = data.str.replace(\"I don't know, someone else does this for me\", \"I don't know someone else does this for me\", regex=False)\n", "data = data.str.split(\", \").explode().to_frame()\n", "order = data.value_counts()[data.value_counts() > 1].keys().get_level_values(0)\n", "ax = sns.countplot(y=q, data=data, order=order);\n", "ax.set(ylabel=\"\", title=q);" ] }, { "cell_type": "markdown", "id": "b4757457-e1e3-47de-a238-1788b54dbe1c", "metadata": {}, "source": [ "#### If you use a cluster, do you have a need for multiple worker types in the same cluster?\n", "\n", "Of the people who use compute clusters, a little less than half have a need for multiple worker types in the same cluster. Examples of this might include mixed workers with GPU vs no GPU, mixed workers with low or high memory allocations, etc." ] }, { "cell_type": "code", "execution_count": 15, "id": "254dcecf-6100-4174-ae68-58e0274cb486", "metadata": { "execution": { "iopub.execute_input": "2022-07-27T19:24:37.842921Z", "iopub.status.busy": "2022-07-27T19:24:37.841875Z", "iopub.status.idle": "2022-07-27T19:24:37.932570Z", "shell.execute_reply": "2022-07-27T19:24:37.932078Z" } }, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "q = \"If you use a cluster, do you have a need for multiple worker / machine types (e.g. GPU / no GPU, low / high memory) in the same cluster?\" # New question in 2021\n", "ax = sns.countplot(y=q, data=df2021[q].dropna().str.split(\";\").explode().to_frame());\n", "ax.set(ylabel=\"\", title=\"Do you need multiple worker/machine types on a cluster?\");" ] }, { "cell_type": "markdown", "id": "31c12bba-39c7-49eb-aba6-836bcc07d6aa", "metadata": {}, "source": [ "### Datasets\n", "\n", "#### How large are your datasets typically?\n", "\n", "Dask users most commonly work with gigabyte sized datasets. Very few users work with petabyte sized datasets." ] }, { "cell_type": "code", "execution_count": 16, "id": "e14743e9-9636-4ccd-a8f6-85575d6aa2f5", "metadata": { "execution": { "iopub.execute_input": "2022-07-27T19:24:37.936843Z", "iopub.status.busy": "2022-07-27T19:24:37.935811Z", "iopub.status.idle": "2022-07-27T19:24:38.042479Z", "shell.execute_reply": "2022-07-27T19:24:38.041977Z" } }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "q = \"How large are your datasets typically?\" # New question in 2021\n", "ax = sns.countplot(y=q, data=df2021[q].dropna().str.split(\", \").explode().to_frame());\n", "ax.set(ylabel=\"\", title=q);" ] }, { "cell_type": "markdown", "id": "fc99643e-f7fc-4a86-a325-4bca5cc3a464", "metadata": {}, "source": [ "#### Where are your datasets typically stored?\n", "\n", "Most people store their data on a local filesystem." ] }, { "cell_type": "code", "execution_count": 17, "id": "cf7c38be-0f9b-4f0b-83a7-3a46981149fb", "metadata": { "execution": { "iopub.execute_input": "2022-07-27T19:24:38.046846Z", "iopub.status.busy": "2022-07-27T19:24:38.045802Z", "iopub.status.idle": "2022-07-27T19:24:38.172138Z", "shell.execute_reply": "2022-07-27T19:24:38.171618Z" } }, "outputs": [ { "data": { "image/png": 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dSrqw54f1kDTNzKzl1dNUbZsXEVeRvkJjZmbtlEecZmZmJThxmpmZleDEaWZmVoITp5mZWQlOnGZmZiU4cZqZmZXgxGlmZlaCE6eZmVkJTpxmZmYl+JeD2rmN116FsUv4m41mZvYxjzjNzMxKcOI0MzMrwYnTzMysBCdOMzOzEpw4zczMSnDiNDMzK8GJ08zMrAQnTjMzsxL8Awjt3H9mPM6/fvbZWodhZktJrzMm1zqEds8jTjMzsxKcOM3MzEpw4jQzMyvBidPMzKwEJ04zM7MSnDjNzMxKcOI0MzMrwYnTzMysBCdOMzOzEpw4zczMSnDiNDMzK8GJ08zMrAQnTjMzsxJaLHFKCknnFdZPkTR0EfvsLGnbloqh0O4QSRctok4XSX+XNEHSQZIuk7RJ3vaCpJ4tHVfF8Qc1HM/MzNqOlhxxzgf+u2TC2Rlo0cQpqbn/Km1LoHNE9I+IP0XENyPiiZaMZREGAU6cZmZtTEsmzgXAMODEyg2SVpV0s6RH8207Sb2BY4AT86hvJ0nPK+kh6UNJO+b975PUV9LKkm6TNEnSQ5I2z9uHShomaSRwVcWx95H0z2JCl7QacDXQPx+7j6R7JQ2sEvshkh7J9S6V1DHfhkuaImmypBNzG+ML+20gaVxePlvSEznuc/Moez/gnMLx+0i6U9K43N9+ed/hkn4v6Z58/+wk6XJJT0oavkSPmJmZldbS/8j6d8AkSf9bUX4hcEFE3C+pF3BXRGws6RJgXkScCyDpadIobD1gHLCDpIeBtSPiWUm/BR6LiEGSdiUlyf75GFsB20fEu5KG5Pa+DJwE7B0RbzYEExEzJX0TOCUi9s11F+qMpI2Bg4DtIuJ9SRcDg4HHgbUiYrNcr0dEvCVptqT+ETEBOBwYLmll4MtAv4iIQt0RwO0RcVNuYxRwTEQ8I+nzwMXArjmUlfLyfsBfgO2AbwKPFo5nZmZLQYsmzoiYI+kq4Hjg3cKm3YFNCslpBUndqzRxH7AjKXGeBRwFjAYezdu3B76Sj/UPSatIWjFvGxERxWPuAgwE9oiIOYvZpd1ICfnRHHtXYCYpea2fE/lfgZG5/mXA4ZJOIiXczwFzgPeAyyT9Fbi98iCSupGmrG8s3EddClX+kpPuZODViJic93sc6A1MqGjvaOBogLVW7LyYXTczs2pa46raXwNHAstXHGebfD6xf0SsFRFzq+x7H7ADKeH8DehBOg86Jm9feFgIkf++XVH+PNAd2LB8Fz4i4MpC3BtFxNA8et0CuBf4DilhAtwM7AXsC4yLiNcjYkHuz82k85p3VjlOB+CtwnH6R8TGhe3z898PC8sN6wt9+ImIYRExMCIGrrx8x8XruZmZVdXiiTMi3gBuICXPBiOB7zasSOqfF+eSkluDh0kjrw8j4j3SSOpbpIQKKYEOzm3sDLzWxGjyReC/gaskbbqY3RkFHJDPiZLPsa6bz5d2iIibgR8DAwByzHcBvweuyPt0A1aMiL8BJ/Dx1PJHfc99mCbpwLyPJG2xmDGbmVkraq3vcZ4HFK+uPR4YmC+OeYJ0URCkKc8v5wtkdoiI+cBLwEN5+32k5DI5rw9taAc4GzisqSAiYiop0d4oqU/ZTuSrbH8EjMzHvBtYA1gLuFfSBGA4cHpht2tIo+CG6dvuwO15/9F8fPHU9cCpkh7LsQ0GjpQ0kXQOdf+y8ZqZWetTRCy6ljWbpFNII8wf1zoWgM3X6hq3f6tvrcMws6Wk1xmTF13JFknSuIhY6JsW0PJX1X6qSboV6MPHV8OamVk748TZgiLiy7WOwczMWpd/q9bMzKwEJ04zM7MSnDjNzMxKcOI0MzMrwYnTzMysBCdOMzOzEpw4zczMSnDiNDMzK8GJ08zMrAQnTjMzsxL8k3vt3DJrbEqvM8bWOgwzs3bDI04zM7MSnDjNzMxKcOI0MzMrwYnTzMysBCdOMzOzEpw4zczMSnDiNDMzK8GJ08zMrAT/AEI799TMp9jut9vVOgyzuvHAcQ/UOgRr4zziNDMzK8GJ08zMrAQnTjMzsxKcOM3MzEpw4jQzMyvBidPMzKwEJ04zM7MSnDjNzMxKcOI0MzMrwYnTzMysBCdOMzOzEpw4zczMSnDiNDMzK2GRiVPSB5ImSJooabykbXN5b0lTFrHvEEkXNScQSadLGlylfJCkSZKekjRZ0qDCtnslDayyz36STmvOcavs+4Mmth2RY5gkaYqk/XP5EElrLs7xzMysbWnOvxV7NyL6A0j6InAWsFMrxLIH8NVigaQtgHOBL0TENEnrAXdLej4iJjXWUESMAEYsZhw/AM6sLJS0NvBDYEBEzJbUDVg1bx4CTAFebu5BJHWMiA8WM0YzM6uRslO1KwBvVhZKWlbSFXk09pikXQqb15F0p6Spkn5SrVFJKwDLRMSsik2nAGdGxDSA/Pcs4NRCnUMkPZhHgJ/L7X000pW0qqSbJT2ab9vl8m6FmCdJ+oqks4GueYR9TUUsqwFzgXk5lnk5mR8ADASuyft1lbRbvh8mS7pcUpd8zBcknSHpfuBASUflmCbmGJfL9fpIeihv+5mkeYX76tRcPknSTxt5nMzMrJU0J3E2JJKngMuAn1ep8x2AiPgs8HXgSknL5m2fAwYD/UnJYqGpVWB3YFSV8k2BcRVlY3N5g+UjYlvg28DlVdq4ELggIrYGvpL7APBjYHZEfDYiNgf+ERGnkUfYEVE5bTwReBWYlhPul3Kfb8oxDc4j8wCGAwfl+6MTcGyhnfciYvuIuB64JSK2jogtgCeBIwsxX5hj/mgUK2kPYAPSfdof2ErSjpUdlnS0pLGSxr4/7/0qd4mZmS2u5iTOhkTSD9gTuEqSKupsD/wRICKeAl4ENszb7o6I1yPiXeCWXLfSnsAdVcpFSkRNlV2XjzsGWEFSj4r6uwMXSZpAmr5dQVL3XP67hkoRsdBIuihPq+4JHAA8DVwgaWiVqhsB0yLi6bx+JVBMbn8qLG8m6T5Jk0kfLho+EGwD3JiXry3U3yPfHgPGA/1IibQy1mERMTAiBnbu1rmpbpmZWUnNOcf5kYj4p6SefHxur0FlIv3EbotYhzSCOrZK+eOkadDi+cwBwBMl2u8AbJMT90dy8q8WS6MiIoBHgEck3Q1cAQytqNbUfQHwdmF5ODAoIiZKGgLsvIh9BZwVEZc2M2QzM2thpc5xSuoHdARer9g0hjRiQtKGQC9gat72BUkrS+oKDAIeqGhzU+CpRi6UORc4XVLvXLc36eKd8wp1DsrbtidNvc6uaGMk8N3C8fo3Ur5SXnxf0kLDNElrShpQKOpPGllDOvfZPS8/BfSW1DevfwMYXaVv5H1m5OMVp4YfIk0rA3ytUH4XcES+MAlJa0larZG2zcysFTRnxNk1T3NCGvEcFhEfVMzWXgxckqccFwBDImJ+rnM/aRq3L3BtRIytaH8v4M5qB46ICZK+D/wlJ5f3gf+JiAmFam9KepB04dIRxd3z3+OB30malPs7BjgG+EUunwJ8APyUNJU8DJgkaXzFec7OwLn5ayfvAbNyO5BGjpdIepc0zXo4cKOkTsCjwCXV+kc6z/owKQFP5uPkewJwtaSTgb8Cs/P9MVLSxsA/8307DzgEmNlI+2Zm1sKUZh9rGECa8jw0Ima0YJsnAytERNWreOtdvrr23YgISV8Dvh4R+y9OW916dYstTt2iZQM0a8MeOO6BRVeyTz1J4yKi2sWs5c5xtoaI+EJLtifpGNL3Kv+7JdtdyrYiXdAk4C0+OZI2M7MaqnnibGkRcQmNT422CRFxH+BhoplZHfJv1ZqZmZXgxGlmZlaCE6eZmVkJTpxmZmYlOHGamZmV4MRpZmZWghOnmZlZCU6cZmZmJThxmpmZldDufjnIPqnfav3825xmZi3II04zM7MSnDjNzMxKcOI0MzMrwYnTzMysBCdOMzOzEpw4zczMSnDiNDMzK8GJ08zMrAT/AEI7N3fqVEbvuFOtw7BF2GnM6FqHYGbN5BGnmZlZCU6cZmZmJThxmpmZleDEaWZmVoITp5mZWQlOnGZmZiU4cZqZmZXgxGlmZlaCE6eZmVkJTpxmZmYlOHGamZmV4MRpZmZWghOnmZlZCW0ycUr6oaTHJU2SNEHS53P5MpJ+Lek5Sc9Kul1Sr8J+80oe5wVJPRdR5wfNbKvUsc3MrD61ucQpaRtgX2BARGwO7A68lDefCXQHNoyIvsDNwJ8ltWY/m5U4zcysfWhziRNYA3gtIuYDRMRrEfGypOWAw4ETI+KDvO0KYB4puS6SpFUkjZT0mKRLARW23SZpXB7pHp3Lzga65lHvNY3VK7RxnqTxkkZJWjWXHSXpUUkTJd2c+4GkAyVNyeVjcllHSefk+pMkfWsJ7kczM1sMbTFxjgTWkfS0pIslNfyX5r7AvyJiTkX9scAmzWz7J8D9EbElMALoVdh2RERsBQwEjpe0SkScBrwbEf0jYnBj9XL58sD4iBgAjM7HArglIraOiC2AJ4Ejc/kZwBdz+X657EhgdkRsDWwNHCVpvWb2zczMWkCbS5wRMQ/YCjgamAX8SdIQ0ugwquyiKmWN2RG4Oh/nr8CbhW3HS5oIPASsA2zQSBuN1fsQ+FNevhrYPi9vJuk+SZOBwcCmufwBYLiko4COuWwP4FBJE4CHgVWqxSHpaEljJY2d/f77ze27mZk1Q6daB7A48lTsvcC9OeEcBtwIrCupe0TMLVQfANxUpvnKAkk7k6Z7t4mIdyTdCyy7uPUqjjMcGBQRE/MHgJ0BIuKYfNHTPsAESf1JHwKOi4i7muxAxDBgGMBG3btX+zBhZmaLqc2NOCVtJKk4yuoPvBgRbwNXAudL6pjrHgq8Rxq9NccY0qgPSXsBK+XyFYE3czLsB/xXYZ/3JXVuRr0OwAF5+WDg/rzcHZiR22iY7kVSn4h4OCLOAF4jjV7vAo5tOJ6kDSUt38y+mZlZC2iLI85uwG8l9QAWAM+Spm0BTgfOAaZK6kqayt0mIhpGXctJml5o6/yIOL+w/lPgOknjSech/5XL7wSOkTQJmEqahm0wDJiU9zmiiXpvA5tKGgfMBg7K5T8mTbu+CEwmJVKAc/IHBAGjgInAJKA3MF6Scv8GLeoOMzOzlqOPc0r7Iml1UsK7OE9dfipt1L17DNtyQK3DsEXYaczoWodgZgWSxkXEwGrb2uKIs1ki4hXSNK6ZmVmLaXPnOM3MzGrJidPMzKwEJ04zM7MSnDjNzMxKcOI0MzMrwYnTzMysBCdOMzOzEpw4zczMSnDiNDMzK8GJ08zMrAQnTjMzsxLa7W/VWtJ9o438A+JmZi3II04zM7MSnDjNzMxKcOI0MzMrwYnTzMysBCdOMzOzEpw4zczMSnDiNDMzK8GJ08zMrAT/AEI7N3P6bC46+S+1DqPFffe8L9U6BDP7lPKI08zMrAQnTjMzsxKcOM3MzEpw4jQzMyvBidPMzKwEJ04zM7MSnDjNzMxKcOI0MzMrwYnTzMysBCdOMzOzEpw4zczMSnDiNDMzK8GJ08zMrAQnzlYkaV7F+hBJF+XloZL+LWmCpGck3SJpk0LdeyVNzdsnSDpAUgdJv5E0RdJkSY9KWm9p98vM7NPM/1asti6IiHMBJB0E/EPSZyNiVt4+OCLGNlSW9HVgTWDziPhQ0trA20s9ajOzTzGPOOtERPwJGAkc3ES1NYAZEfFh3md6RLy5NOIzM7PEI87W1VXShML6ysCIJuqPB/oV1q+R9G5e3g24Abhf0g7AKODqiHisshFJRwNHA6zUfdXFj97MzBbixNm63o2I/g0rkoYAA5uor4r1T0zV5jY2AnbNt1GSDoyIUcU6ETEMGAbQa/UNYrGjNzOzhThx1pctgbFNVYiI+cAdwB2SXgUGkUafZma2FPgcZ52Q9BVgD+C6JuoMkLRmXu4AbA68uHQiNDMz8Iiz1k6UdAiwPDAF2LVwRW01qwF/kNQlrz8CXNTKMZqZWYETZyuKiG4V68OB4Xl5KDC0iX13rlJ2J3Bny0VoZmZlearWzMysBCdOMzOzEpw4zczMSnDiNDMzK8GJ08zMrAQnTjMzsxKcOM3MzEpw4jQzMyvBidPMzKwEJ04zM7MSnDjNzMxK8G/VtnOrrb0i3z3vS7UOw8ys3fCI08zMrAQnTjMzsxKcOM3MzEpw4jQzMytBEVHrGKwVSZoLTK11HE3oCbxW6yCa4PiWTD3HV8+xgeNbUksa37oRsWq1Db6qtv2bGhEDax1EYySNdXyLz/EtvnqODRzfkmrN+DxVa2ZmVoITp5mZWQlOnO3fsFoHsAiOb8k4vsVXz7GB41tSrRafLw4yMzMrwSNOMzOzEpw4zczMSnDibMck7SlpqqRnJZ1W41jWkXSPpCclPS7pe7l8ZUl3S3om/12pxnF2lPSYpNvrLT5JPSTdJOmpfD9uU2fxnZgf2ymSrpO0bC3jk3S5pJmSphTKGo1H0un5tTJV0hdrFN85+fGdJOlWST3qKb7CtlMkhaSe9RafpONyDI9L+t9WiS8ifGuHN6Aj8BywPrAMMBHYpIbxrAEMyMvdgaeBTYD/BU7L5acBv6rx/XYScC1we16vm/iAK4Fv5uVlgB71Eh+wFjAN6JrXbwCG1DI+YEdgADClUFY1nvxcnAh0AdbLr52ONYhvD6BTXv5VvcWXy9cB7gJeBHrWU3zALsDfgS55fbXWiM8jzvbrc8CzEfF8RPwHuB7Yv1bBRMSMiBifl+cCT5LebPcnJQTy30E1CRCQtDawD3BZobgu4pO0AumN4v8AIuI/EfFWvcSXdQK6SuoELAe8TA3ji4gxwBsVxY3Fsz9wfUTMj4hpwLOk19BSjS8iRkbEgrz6ELB2PcWXXQD8D1C8srRe4jsWODsi5uc6M1sjPifO9mst4KXC+vRcVnOSegNbAg8Dn4mIGZCSK7BaDUP7NekN4cNCWb3Etz4wC7giTyVfJmn5eokvIv4NnAv8C5gBzI6IkfUSX0Fj8dTj6+UI4I68XBfxSdoP+HdETKzYVBfxARsCO0h6WNJoSVvn8haNz4mz/VKVspp/90hSN+Bm4ISImFPreBpI2heYGRHjah1LIzqRpqV+HxFbAm+TphrrQj5XuD9pGmxNYHlJh9Q2qlLq6vUi6YfAAuCahqIq1ZZqfJKWA34InFFtc5WyWtx/nYCVgP8CTgVukCRaOD4nzvZrOulcRIO1SVNnNSOpMylpXhMRt+TiVyWtkbevAcxsbP9Wth2wn6QXSNPau0q6uo7imw5Mj4iH8/pNpERaL/HtDkyLiFkR8T5wC7BtHcXXoLF46ub1IukwYF9gcOQTdNRHfH1IH4wm5tfJ2sB4SavXSXzkOG6J5BHS7FHPlo7PibP9ehTYQNJ6kpYBvgaMqFUw+VPf/wFPRsT5hU0jgMPy8mHAn5d2bAARcXpErB0RvUn31T8i4pA6iu8V4CVJG+Wi3YAnqJP4SFO0/yVpufxY70Y6j10v8TVoLJ4RwNckdZG0HrAB8MjSDk7SnsD3gf0i4p3CpprHFxGTI2K1iOidXyfTSRf8vVIP8WW3AbsCSNqQdBHday0eX2te9eRbbW/A3qSrV58DfljjWLYnTY1MAibk297AKsAo4Jn8d+U6uN925uOrausmPqA/MDbfh7eRpqTqKb6fAk8BU4A/kq5grFl8wHWk863vk97kj2wqHtI05HOkf8O3V43ie5Z0Lq7hNXJJPcVXsf0F8lW19RIfKVFenZ+D44FdWyM+/+SemZlZCZ6qNTMzK8GJ08zMrAQnTjMzsxKcOM3MzEpw4jQzMyvBidPM6p6kE/Iv15jVnL+OYmZ1L/9SzcCIeK3WsZh5xGlmLULSofn/SE6U9EdJ60oalctGSeqV6w2XdEBhv3n5786S7tXH/3P0GiXHk37/9h5J99Smd2Yf61TrAMys7ZO0KemXWbaLiNckrUz6t11XRcSVko4AfsOi/63YlsCmpN8RfSC39xtJJwG7eMRp9cAjTjNrCbsCNzUktoh4A9iG9E/BIf0E3/bNaOeRiJgeER+SfnKud8uHarZknDjNrCWIRf+bpobtC8jvPfkH4Zcp1JlfWP4Az4pZHXLiNLOWMAr4qqRVAPJU7YOk/zQDMBi4Py+/AGyVl/cHOjej/blA95YK1mxJ+NOcmS2xiHhc0i+B0ZI+AB4Djgcul3QqMAs4PFf/A/BnSY+QEu7bzTjEMOAOSTMiYpeW74FZ8/nrKGZmZiV4qtbMzKwEJ04zM7MSnDjNzMxKcOI0MzMrwYnTzMysBCdOMzOzEpw4zczMSvh/Sx7hggwvcBYAAAAASUVORK5CYII=\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "q = \"Where are your datasets typically stored?\" # New question in 2021\n", "data = df2021[q].dropna().str.split(\", \").explode().to_frame()\n", "order = data.value_counts()[data.value_counts() > 1].keys().get_level_values(0)\n", "ax = sns.countplot(y=q, data=data, order=order);\n", "ax.set(ylabel=\"\", title=q);" ] }, { "cell_type": "markdown", "id": "1dbf9da0-3eef-4e8f-8319-fb37fcd62583", "metadata": {}, "source": [ "#### What file formats do you typically work with?\n", "\n", "The two most common file formats (`csv` and `parquet`) are popular among Dask Dataframe users. The `JSON` file format is also very commonly used with Dask. The fourth and fifth most common filetypes (`HDF5` and `zarr`) are popular among Dask Array users. This fits with what we know about the Dask Dataframe API being the most popular, with Dask Arrays close behind." ] }, { "cell_type": "code", "execution_count": 18, "id": "d1c7ccd5-c191-4ebe-9bb6-099a31fe30c4", "metadata": { "execution": { "iopub.execute_input": "2022-07-27T19:24:38.176646Z", "iopub.status.busy": "2022-07-27T19:24:38.175569Z", "iopub.status.idle": "2022-07-27T19:24:38.344308Z", "shell.execute_reply": "2022-07-27T19:24:38.343785Z" } }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "q = \"What file formats do you typically work with?\" # New question in 2021\n", "data = df2021[q].dropna().str.split(\", \").explode().to_frame()\n", "order = data.value_counts()[data.value_counts() > 1].keys().get_level_values(0)\n", "ax = sns.countplot(y=q, data=data, order=order);\n", "ax.set(ylabel=\"\", title=q);" ] }, { "cell_type": "markdown", "id": "cdcd7f32-6a64-4c04-9293-c97844a1ff4a", "metadata": {}, "source": [ "This survey question had a long tail: a very wide variety of specialized file formats were reported, most only being used by one or two individuals who replied to the survey.\n", "\n", "A lot of these specialized file formats store image data, specific to particular fields (astronomy, geoscience, microscopy, etc.)." ] }, { "cell_type": "code", "execution_count": 19, "id": "facb7865-c1da-44b8-830f-dead75027c8b", "metadata": { "execution": { "iopub.execute_input": "2022-07-27T19:24:38.348791Z", "iopub.status.busy": "2022-07-27T19:24:38.347739Z", "iopub.status.idle": "2022-07-27T19:24:38.358725Z", "shell.execute_reply": "2022-07-27T19:24:38.357968Z" } }, "outputs": [ { "data": { "text/plain": [ "['proprietary measurement format',\n", " 'netCDF3',\n", " 'czi',\n", " 'specifically NetCDF4',\n", " 'grib2',\n", " 'in-house npy-like array format',\n", " 'jpeg2000',\n", " 'netCDF4 (based on HDF5)',\n", " 'proprietary microscopy file types. Often I convert to Zarr with a loss of metadata.',\n", " 'sas7bdat',\n", " 'npy',\n", " 'npy and pickle',\n", " 'root with uproot',\n", " 'root',\n", " 'regular GeoTiff',\n", " '.npy',\n", " 'Text',\n", " 'VCF BAM CRAM',\n", " 'UM',\n", " 'CASA measurement sets',\n", " 'Casa Tables (Radio Astronomy specific)',\n", " 'Custom binary',\n", " 'FITS',\n", " 'FITS (astronomical images)',\n", " 'FITS and a custom semi-relational table specification that I want to kill and replace with something better',\n", " 'Feather (Arrow)',\n", " 'GPKG',\n", " 'GeoTIFF',\n", " 'NetCDF4',\n", " 'Netcdf',\n", " 'Netcdf4',\n", " 'PP',\n", " 'SQL',\n", " 'SQL query to remote DB',\n", " 'SQL to Dataframe',\n", " 'Seismic data (miniSEED)',\n", " 'TFRecords',\n", " 'TIFF',\n", " 'Testing with all file formats. Just want it as a replacement for spark. ',\n", " '.raw image files',\n", " 'ugh']" ] }, "execution_count": 19, "metadata": {}, "output_type": "execute_result" } ], "source": [ "list(data.value_counts()[data.value_counts() == 1].keys().get_level_values(0))" ] }, { "cell_type": "markdown", "id": "9e22bae2-c0bd-49ea-9fa3-42842e98e1d8", "metadata": {}, "source": [ "\"XKCD \n", "\n", "XKCD comic \"Standards\" https://xkcd.com/927/" ] }, { "cell_type": "markdown", "id": "f448af9c-ea64-4bfa-a918-8dfab3a01f50", "metadata": {}, "source": [ "### Preferred Cloud?\n", "\n", "The most popular cloud solution is Amazon Web Services (AWS), followed by Google Cloud Platform (GCP) and Microsoft Azure. " ] }, { "cell_type": "code", "execution_count": 20, "id": "afd29942-516e-4ec9-89e1-977b1e862e8a", "metadata": { "execution": { "iopub.execute_input": "2022-07-27T19:24:38.361772Z", "iopub.status.busy": "2022-07-27T19:24:38.361578Z", "iopub.status.idle": "2022-07-27T19:24:38.468482Z", "shell.execute_reply": "2022-07-27T19:24:38.467876Z" } }, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "q = \"Preferred Cloud?\"\n", "order = [\n", " \"Amazon Web Services (AWS)\",\n", " \"Google Cloud Platform (GCP)\",\n", " \"Microsoft Azure\",\n", " \"Digital Ocean\", \n", "]\n", "ax = sns.countplot(y=q, data=df2021[q].dropna().str.split(\", \").explode().to_frame(), order=order);\n", "ax.set(ylabel=\"\", title=q);" ] }, { "cell_type": "markdown", "id": "40407f57-01a6-4a22-888a-8daa49182bcd", "metadata": {}, "source": [ "### Do you use Dask projects to deploy?\n", "\n", "Among those who use dask projects to deploy, [dask-jobqueue](https://github.com/dask/dask-jobqueue)\n", "and [dask helm chart](https://github.com/dask/helm-chart) are the two most popular options.\n", "There was a wide variety of projects people used for deployment.\n" ] }, { "cell_type": "code", "execution_count": 21, "id": "ead01452-e559-46aa-804b-9e3fd04e28bd", "metadata": { "execution": { "iopub.execute_input": "2022-07-27T19:24:38.471553Z", "iopub.status.busy": "2022-07-27T19:24:38.471355Z", "iopub.status.idle": "2022-07-27T19:24:38.616875Z", "shell.execute_reply": "2022-07-27T19:24:38.616304Z" } }, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "q = \"Do you use Dask projects to deploy?\"\n", "order = [\n", " \"dask-jobqueue\",\n", " \"dask's helm chart\",\n", " \"dask-kubernetes\",\n", " \"dask's docker image at daskdev/dask\",\n", " \"dask-gateway\",\n", " \"dask-ssh\",\n", " \"dask-cloudprovider\",\n", " \"dask-yarn\",\n", " \"qhub\",\n", " \"dask-mpi\",\n", "]\n", "ax = sns.countplot(y=q, data=df2021[q].dropna().str.lower().str.split(\", \").explode().to_frame(), order=order);\n", "ax.set(ylabel=\"\", title=q);" ] }, { "cell_type": "markdown", "id": "da08aacf-260f-46d4-8004-dd8a1ecce9d0", "metadata": {}, "source": [ "## Diagnostics \n", "\n", "We saw earlier that most people like to view the Dask Dashboard using their web browser.\n", "\n", "In the dashboard, people said the most useful diagnostics plots were:\n", "\n", "1. The task stream plot\n", "2. The progress plot, and\n", "3. The memory useage per worker plot\n" ] }, { "cell_type": "code", "execution_count": 22, "id": "b4f82846-03d0-4f91-bf75-6e443a10dd44", "metadata": { "execution": { "iopub.execute_input": "2022-07-27T19:24:38.619785Z", "iopub.status.busy": "2022-07-27T19:24:38.619587Z", "iopub.status.idle": "2022-07-27T19:24:38.768617Z", "shell.execute_reply": "2022-07-27T19:24:38.768136Z" } }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "q = \"Which Diagnostic plots are most useful?\" # New question in 2021\n", "ax = sns.countplot(y=q, data=df2021[q].dropna().str.split(', ').explode().to_frame());\n", "ax.set(ylabel=\"\", title=q);" ] }, { "cell_type": "markdown", "id": "4559feb5-33dd-4f35-882c-9c8b92a3b466", "metadata": {}, "source": [ "We also asked some new questions about diagnostics in 2021.\n", "\n", "We found that most people (65 percent) do not use [Dask performance reports](https://distributed.dask.org/en/latest/diagnosing-performance.html#performance-reports), which is a way to save the diagnostic dashboard to static HTML plots for later review." ] }, { "cell_type": "code", "execution_count": 23, "id": "f2e741b8-c1f4-4f3c-9006-c49ebb3bd52c", "metadata": { "execution": { "iopub.execute_input": "2022-07-27T19:24:38.771588Z", "iopub.status.busy": "2022-07-27T19:24:38.771206Z", "iopub.status.idle": "2022-07-27T19:24:38.864104Z", "shell.execute_reply": "2022-07-27T19:24:38.863628Z" } }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "q = \"Do you use Dask's Performance reports?\" # New question in 2021\n", "ax = sns.countplot(y=q, data=df2021[q].explode().to_frame(), order=[\"Yes\", \"No\"]);\n", "ax.set(ylabel=\"\", title=q);" ] }, { "cell_type": "markdown", "id": "a9e43043-5032-44ea-a434-886a9d122354", "metadata": {}, "source": [ "Very few people use Dask's [Prometheus metrics](https://docs.dask.org/en/latest/setup/prometheus.html). Jacob Tomlinson has an excellent article on [Monitoring Dask + RAPIDS with Prometheus + Grafana](https://medium.com/rapids-ai/monitoring-dask-rapids-with-prometheus-grafana-96eaf6b8f3a0), if you're interested in learning more about how to use this feature." ] }, { "cell_type": "code", "execution_count": 24, "id": "cce4bd07-456f-4d70-ac83-30455c43f865", "metadata": { "execution": { "iopub.execute_input": "2022-07-27T19:24:38.866881Z", "iopub.status.busy": "2022-07-27T19:24:38.866546Z", "iopub.status.idle": "2022-07-27T19:24:38.964329Z", "shell.execute_reply": "2022-07-27T19:24:38.963761Z" } }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "q = \"Do you use Dask's Prometheus Metrics?\" # New question in 2021\n", "ax = sns.countplot(y=q, data=df2021[q].explode().to_frame(), order=[\"Yes\", \"No\"]);\n", "ax.set(ylabel=\"\", title=q);" ] }, { "cell_type": "markdown", "id": "d10f4c88-55d7-4b14-95c7-64220bcd18b9", "metadata": {}, "source": [ "## Stability \n", "\n", "We asked a number of questions around the stability of Dask, many of them new questions in 2021.\n", "\n", "The majority of people said Dask was resiliant enough for them (eg: computations complete).\n", "However this is an area we could improve in, as 36 percent of people are not satisfied.\n", "This was a new question 2021, so we can't say how people opinion of Dask's resiliancy has changed over time.\n", "\n" ] }, { "cell_type": "code", "execution_count": 25, "id": "c4bcefbe-694c-4efb-8016-eb9c84ae33c9", "metadata": { "execution": { "iopub.execute_input": "2022-07-27T19:24:38.967114Z", "iopub.status.busy": "2022-07-27T19:24:38.966850Z", "iopub.status.idle": "2022-07-27T19:24:39.059780Z", "shell.execute_reply": "2022-07-27T19:24:39.059293Z" } }, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "q = \"Is Dask resilient enough for you? (e.g. computations complete).\" # new question in 2021\n", "ax = sns.countplot(y=q, data=df2021[q].dropna().explode().to_frame(), order=[\"Yes\", \"No\"]);\n", "ax.set(ylabel=\"\", title=\"Is Dask resilient enough for you?\");" ] }, { "cell_type": "markdown", "id": "3609dd15-c9d7-4e7f-ae8d-8f69205d6d82", "metadata": {}, "source": [ "Most people say Dask in general is stable enough for them (eg: between different version releases). This is similar to the survey results from previous years." ] }, { "cell_type": "code", "execution_count": 26, "id": "2521b81e-b3bb-499d-a2f6-f17a40f45c86", "metadata": { "execution": { "iopub.execute_input": "2022-07-27T19:24:39.062535Z", "iopub.status.busy": "2022-07-27T19:24:39.062196Z", "iopub.status.idle": "2022-07-27T19:24:39.155970Z", "shell.execute_reply": "2022-07-27T19:24:39.155386Z" } }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "q = \"Is Dask stable enough for you?\"\n", "ax = sns.countplot(y=q, data=df2021[q].dropna().explode().to_frame(), order=[\"Yes\", \"No\"]);\n", "ax.set(ylabel=\"\", title=q);" ] }, { "cell_type": "markdown", "id": "1043d415-065e-42b7-be9e-cd11fc6dc7de", "metadata": {}, "source": [ "People also say that the API of Dask is stable enough for them too." ] }, { "cell_type": "code", "execution_count": 27, "id": "481266a1-ecdd-42f2-b6b8-c8a5c1d6dcdd", "metadata": { "execution": { "iopub.execute_input": "2022-07-27T19:24:39.158725Z", "iopub.status.busy": "2022-07-27T19:24:39.158460Z", "iopub.status.idle": "2022-07-27T19:24:39.246380Z", "shell.execute_reply": "2022-07-27T19:24:39.245781Z" } }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "q = \"Is Dask's API stable enough for you?\"\n", "ax = sns.countplot(y=q, data=df2021[q].dropna().explode().to_frame(), order=[\"Yes\", \"No\"]);\n", "ax.set(ylabel=\"\", title=q);" ] }, { "cell_type": "markdown", "id": "ab1eec67-48e5-44cb-a423-cdf8f8d9c3e0", "metadata": {}, "source": [ "The vast majority of people are satisfied with the current release frequency (roughly once every two weeks)." ] }, { "cell_type": "code", "execution_count": 28, "id": "a1a97e9d-ad6a-4c01-8a92-b320587482c0", "metadata": { "execution": { "iopub.execute_input": "2022-07-27T19:24:39.249475Z", "iopub.status.busy": "2022-07-27T19:24:39.249150Z", "iopub.status.idle": "2022-07-27T19:24:39.457808Z", "shell.execute_reply": "2022-07-27T19:24:39.457203Z" } }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "q = \"How is Dask's release frequency?\" # New question in 2021\n", "ax = sns.countplot(y=q, data=df2021[q].dropna().explode().to_frame());\n", "ax.set(ylabel=\"\", title=q);" ] }, { "cell_type": "markdown", "id": "20514ffd-88cc-4b0b-921f-e83484010e31", "metadata": {}, "source": [ "Most people say they would pin their code to a long term support release, if one was available for Dask." ] }, { "cell_type": "code", "execution_count": 29, "id": "076d6737-c6e3-42f6-b5cc-fac45a461675", "metadata": { "execution": { "iopub.execute_input": "2022-07-27T19:24:39.460862Z", "iopub.status.busy": "2022-07-27T19:24:39.460350Z", "iopub.status.idle": "2022-07-27T19:24:39.558134Z", "shell.execute_reply": "2022-07-27T19:24:39.557535Z" } }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "q = \"If Dask had Long-term support (LTS) releases, would you pin your code to use them?\" # New question in 2021\n", "ax = sns.countplot(y=q, data=df2021[q].dropna().explode().to_frame(), order=[\"Yes\", \"No\"]);\n", "ax.set(ylabel=\"\", title=\"Would you pin to a long term support release?\");" ] }, { "cell_type": "markdown", "id": "0053422e-0f23-4662-a2ae-4d102c0c17f0", "metadata": {}, "source": [ "## User satisfaction, support, and documentation \n", "\n", "We asked a bunch of new questions about user satisfaction in the 2021 survey." ] }, { "cell_type": "markdown", "id": "24e2d6fc-84a3-4295-958f-f08d619d2a0c", "metadata": {}, "source": [ "### How easy is Dask to use?\n", "\n", "The majority of people say that Dask is moderately easy to use, the same as in previous surveys." ] }, { "cell_type": "code", "execution_count": 30, "id": "d461469e-4262-441a-9a7c-7566afa88fff", "metadata": { "execution": { "iopub.execute_input": "2022-07-27T19:24:39.561156Z", "iopub.status.busy": "2022-07-27T19:24:39.560652Z", "iopub.status.idle": "2022-07-27T19:24:39.668367Z", "shell.execute_reply": "2022-07-27T19:24:39.667774Z" } }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "q = \"On a scale of 1 - 5 (1 being hardest, 5 being easiest) how easy is Dask to use?\"\n", "ax = sns.countplot(y=q, data=df2021[q].dropna().explode().to_frame());\n", "ax.set(ylabel=\"1 = Difficult, 5 = Easy\", title=\"How easy is Dask to use?\");" ] }, { "cell_type": "markdown", "id": "227a7864-9f89-4ec9-8cc3-38ee8c2fb268", "metadata": {}, "source": [ "### How is Dask's documentation?\n", "\n", "Most people think that Dask's documentation is pretty good." ] }, { "cell_type": "code", "execution_count": 31, "id": "85699dad-f6fd-40df-ab32-2753acd8aafd", "metadata": { "execution": { "iopub.execute_input": "2022-07-27T19:24:39.671677Z", "iopub.status.busy": "2022-07-27T19:24:39.671162Z", "iopub.status.idle": "2022-07-27T19:24:39.781040Z", "shell.execute_reply": "2022-07-27T19:24:39.780443Z" } }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "q = \"How is Dask's documentation?\" # New question in 2021\n", "ax = sns.countplot(y=q, data=df2021[q].dropna().explode().to_frame());\n", "ax.set(ylabel=\"1 = Not good, 5 = Great\", title=q);" ] }, { "cell_type": "markdown", "id": "e3e3559f-4222-45b8-9d33-12a44a121343", "metadata": {}, "source": [ "### How satisfied are you with maintainer responsiveness on GitHub?\n", "\n", "Almost everybody who responded feels positively about Dask's maintainer responsiveness on GitHub .\n" ] }, { "cell_type": "code", "execution_count": 32, "id": "4b1e4373-cc44-4494-8611-0937469c55c8", "metadata": { "execution": { "iopub.execute_input": "2022-07-27T19:24:39.784052Z", "iopub.status.busy": "2022-07-27T19:24:39.783618Z", "iopub.status.idle": "2022-07-27T19:24:39.885101Z", "shell.execute_reply": "2022-07-27T19:24:39.884621Z" } }, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "q = \"How satisfied are you with maintainer responsiveness on GitHub?\" # New question in 2021\n", "ax = sns.countplot(y=q, data=df2021[q].dropna().explode().to_frame());\n", "ax.set(ylabel=\"1 = Not satisfied, 5 = Thrilled\", title=q);" ] }, { "cell_type": "markdown", "id": "842c2163-db17-4d42-8ad8-b09df3952542", "metadata": {}, "source": [ "### What Dask resources have you used for support in the last six months?\n", "\n", "The documentation at [dask.org](https://dask.org/) is the first place most users look for help.\n", "\n", "The breakdown of responses to this question in 2021 was very similar to previous years, with the exception that no-one seemed to know that the [Dask YouTube channel](https://www.youtube.com/c/Dask-dev/videos) or Gitter chat existed in 2019." ] }, { "cell_type": "code", "execution_count": 33, "id": "2191162b-ecce-4239-ae8e-6f7e8bf2c1be", "metadata": { "execution": { "iopub.execute_input": "2022-07-27T19:24:39.887984Z", "iopub.status.busy": "2022-07-27T19:24:39.887536Z", "iopub.status.idle": "2022-07-27T19:24:40.109405Z", "shell.execute_reply": "2022-07-27T19:24:40.108770Z" } }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "q = '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", "df[q] = df[q].str.replace(';',', ') # Make separator values consistent\n", "d = df[q].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=q, hue=\"Year\", data=d.reset_index(), ax=ax);\n", "ax.set(ylabel=\"\", title=q);" ] }, { "cell_type": "markdown", "id": "94d96e9b-f927-40ec-9bf1-8de704da74f6", "metadata": {}, "source": [ "## Suggestions for improvement " ] }, { "cell_type": "markdown", "id": "1a65e94b-6ead-4ffa-bf1c-ba45c377d924", "metadata": {}, "source": [ "### Which would help you most right now?\n", "\n", "The two top priorities people said would help most right now are both related to documentation. People want more documentation, and more examples in their field. Performance improvements were also commonly mentioned as something that would help the most right now." ] }, { "cell_type": "code", "execution_count": 34, "id": "034fac9f-e810-49bf-aa80-ff91c7876e9b", "metadata": { "execution": { "iopub.execute_input": "2022-07-27T19:24:40.112136Z", "iopub.status.busy": "2022-07-27T19:24:40.111940Z", "iopub.status.idle": "2022-07-27T19:24:40.233907Z", "shell.execute_reply": "2022-07-27T19:24:40.233299Z" } }, "outputs": [ { "data": { "image/png": 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UVn5mr5mZLecet5mZWYE4uM3MzArEwW1mZlYgDm4zM7MCcXCbmZkViIPbzMysQBzcZmZmBeLgNjMzKxB/AIu1q/dfnMM/zt251mWYmQHQ46xZtS6h1dzjNjMzKxAHt5mZWYE4uM3MzArEwW1mZlYgDm4zM7MCcXCbmZkViIPbzMysQBzcZmZmBeLgNjMzKxAHt5mZWYE4uM3MzArEwW1mZlYgDm4zM7MCaVVwSwpJN+Sm15D0qqS7W19afZI0TNKv2mA7j7VFPS3c98mSnpY0UtJBkn7YRPsGj1nSkvap0szMKmnt13q+Dewkaa2IWAp8HnihORuQtEZEfNjKOgonIj5bw91/BzggIuan6dE1rMXMzJqhLYbK7wW+kB4fCYwqLZC0vqQ7JM2U9Lik3mn+2ZJGSBoDXC9pQ0m3Snoi/Qwq34mk1SVdlJbPlHRcmn+qpGvS450lzZa0tqQBkh6TND393ja1GZZqukvSfEknpm1MTzWun9qNlXR5Wne2pAEVaqpYt6S9Jc1IP9Mldamw7pL0e0ja1y2S5qZesCq0HyvpMknjU295N0m3SXpG0k9Sm/MkfTe3zk8lnVy2nd8CWwOjJX0v35uu8nnYStLEtPy88uVmZta+2iK4bwSOkNQR6A1Myi07B5geEb2BHwPX55btCnw5Ir4GXAFcFhG7AYcAV1fYzzeBxanNbsC3JG0FXA5sI+lg4A/AcRHxDjAXGBwRfYGzgJ/ltrUT8DVgAPBT4J3UbiJwdK5dp9Qz/g5wTYWaGqr7NOCEiOgD7AUsrbBuXl/gFGAHslBdKTCT9yNiMPBb4E7ghHQswyRtAPweOAZA0mrAEcDI/AYi4nhgEbBPRFxW5fGUt7kytXmpieMyM7M21tqhciJipqSeZL3tv5Qt3pMsAIiIhyRtIKlrWjY6Da8DDAV2yHU015HUJSLeym1rP6C3pEPTdFegV0TMlzQMmAlcFRETcsuvk9QLCKBDblsPp22/JWkxcFeaP4vs4qNkVKp9vKR1JK1bdnwV6wYmAJdKGgncFhELadzkUhtJM4CewKMV2pWGtGcBcyLixbTOs8AWETFD0j8l9QU2Jrto+mcT+67mePIGkZ5T4AbgwvKNSBoODAfYrGuH8sVmZtYKrQ7uZDRwMTAE2CA3f6UhX7IQhez+eMlqwMBckFci4KSIuL/Csl7AEqB7bt55ZAF9cLqwGJtb9l7u8Ue56Y9Y8ZwEKyqfbqjuCyTdAxwIPC5paETMrXhUK9ezjIafl3yd5cdQWudqYBiwCZVHCRpT8XgqjNyXn4cVF0aMAEYA9N5srUbbmplZ87TVn4NdA5wbEbPK5o8HjoLsXi7wWkS8WWH9McCJpQlJfSq0uR/4tqQOqc1nJHVKPfgrgMHABmU98tIb5YY1/5AAODzta0+yYfrF1dQt6dMRMSsiLgSmANu1cP8tcTuwP9nthEoXOY2p5nmYQDYED+m5NTOzj0+bBHdELIyIKyosOhvoL2kmcAHp/msFJ5faSXoKOL5Cm6uBp4BpkmYDV5H1Mi8DfhMRfyO7D36BpI2AnwPnS5oArN7CQ3tD2Z9t/TZtu9q6T0lvaHuS7P72vS3cf7NFxPvAw8DNEbGsmatX8zx8FzhB0hNkF0dmZvYxUoRHMiuRNBY4LSKm1LqW5khvSpsG/GdEPFPrenpvtlbcfdw2tS7DzAyAHmeVDwzXJ0lTI6J/pWX+5LRViKQdgL8DD9ZDaJuZWdtrqzenrXIiYkita2iuiHiK7M/JzMxsFeUet5mZWYE4uM3MzArEwW1mZlYgDm4zM7MCcXCbmZkViIPbzMysQBzcZmZmBeLgNjMzKxAHt5mZWYE4uM3MzArEH3lq7WrNTXekx1mF+p4WM7O65h63mZlZgTi4zczMCsTBbWZmViAObjMzswJxcJuZmRWIg9vMzKxAHNxmZmYF4uA2MzMrEH8Ai7Wrua/MZdAvB9W6DLNCm3DShFqXYHXEPW4zM7MCcXCbmZkViIPbzMysQBzcZmZmBeLgNjMzKxAHt5mZWYE4uM3MzArEwW1mZlYgDm4zM7MCcXCbmZkViIPbzMysQBzcZmZmBeLgNjMzK5Amg1vSMkkzJM2W9GdJazdnB5IukjRH0kUtL7P2JJ0raWit66gFST+udQ1mZpappse9NCL6RMROwPvA8dVsWFLpK0OPA/pFxOnNXK+uRMRZEfHXtt6upNXbepvtwMFtZlYnmjtU/giwjaROkq6R9ISk6ZK+DCBpWOqV3wWMkTQa6ARMknS4pC0lPShpZvrdI613raRLJT0MXJimr5T0sKRnJe2d9ve0pGtLxaQ2U1KP/pzc/OcknSNpmqRZkrZL8ztL+kOaN1PSIWn+fpImpvZ/ltS5/MBTTYfmtv+ztM4USf0k3S/p/yQdn9oMkTRe0u2SnpL0W0mrpWVLUg9+EjBQ0qlpRGO2pFNSmwslfSe3/7MlfT89Pj2d+5ml45bUU9JcSVen7YyUNFTSBEnPSBqQ2jX23N0m6b7U/udp/gXAWmnUZWRa/x5JT6b9HN7M15CZmbVC1cGdesIHALOAM4CHImI3YB/gIkmdUtOBwDERsW9EHMTyHvtNwK+A6yOiNzAS+EVuF58BhkbE99P0esC+wPeAu4DLgB2BnSX1SW3OiIj+QG9gb0m9c9t7LSL6AVcCp6V5/wMsjoidUw0PSeoGnJn23Q+YApxaxSlZEBEDyS5mrgUOBfYAzs21GQB8H9gZ+DTw1TS/EzA7InYHlgLfAHZP639LUl/gRiAfiocBf5a0H9ArbbsPsKukwanNNsAV6XxsB3wN2DMdf6nX3Nhz1yftc2fgcElbRMQPWf4cHgXsDyyKiF3SKMx95SdG0vB0QTPlgyUfVHEqzcysWtUE91qSZpAF2j+A3wP7AT9M88cCHYEeqf0DEfF6A9saCPwpPb6BLFRK/hwRy3LTd0VEkF0ovBwRsyLiI2AO0DO1OUzSNGA6WajvkFv/tvR7aq79UODXpQYR8QZZWO4ATEjHcwywZQP1541Ov2cBkyLirYh4FXhX0rpp2eSIeDYd16jc8S4Dbk2P9wRuj4i3I2JJqnuviJgObCSpu6RdgDci4h9k536/dMzTyAK6V9rW/LLz9GDuHJbOQWPP3YMRsTgi3gWeauA8zAKGphGBvSJicXmDiBgREf0jon+Hzh2aPJFmZla9au4nL42IPvkZkgQcEhHzyubvDrzdjP1H7nH5eu+l3x/lHpem15C0FVlPcreIeCMNoXessP4ylh+nyvZZmvdARBzZjLqbrC89Lt9Xafrd3EWKGtnHLWQ9+U3IeuCl9udHxFX5hpJ6VqgjX2P+HDT03OXXz5+35QcQ8TdJuwIHAudLGhMR55a3MzOz9tHSPwe7HzgpBThpaLcajwFHpMdHAY+2cP8A65CF/WJJG5MN4zdlDHBiaULSesDjwCBJ26R5a0v6TCvqyhsgaat0b/twKh/veOArab+dgIPJht8hC+sjyML7ljTvfuDY0n14SZtJ2qgZNbXkuftAUofUvjvwTkT8EbgY6NeMfZuZWSu1NLjPAzoAMyXNTtPVOBn4hqSZwNeB77Zw/0TEk2TDxXOAa4AJVaz2E2C99KaqJ4F90vD2MGBUqutxsuHntjARuACYDcwHbi9vEBHTyO6RTwYmAVenYXIiYg7QBXghIl5M88aQ3W6YKGkWWaB3aUZNLXnuRqT2I8nuf09OQ+1nkJ1TMzP7mCi7BWptTdIQ4LSI+GKNS6mpzj06xy6n71LrMswKbcJJ1fRLbFUiaWp68/VK/MlpZmZmBVKXH3ayKoiIsWTv2jYzM2sz7nGbmZkViIPbzMysQBzcZmZmBeLgNjMzKxAHt5mZWYE4uM3MzArEwW1mZlYgDm4zM7MCcXCbmZkViD85zdrVdhtt589ZNjNrQ+5xm5mZFYiD28zMrEAc3GZmZgXi4DYzMysQB7eZmVmBOLjNzMwKxMFtZmZWIA5uMzOzAvEHsFi7emvePMYN3rvWZVgb23v8uFqXYPaJ5R63mZlZgTi4zczMCsTBbWZmViAObjMzswJxcJuZmRWIg9vMzKxAHNxmZmYF4uA2MzMrEAe3mZlZgTi4zczMCsTBbWZmViAObjMzswJxcJuZmRWIg7uVJIWkS3LTp0k6u433cZGkOZIuasG6fSQd2Jb1mJlZ7Ti4W+894KuSurXjPo4D+kXE6S1Ytw/QrOBWxq8NM7M65P+cW+9DYATwvfIFkjaUdKukJ9LPoDR/lqR1U0D+U9LRaf4NkoaWbWM00AmYJOnwRrY5QNJjkqan39tKWhM4Fzhc0oy0/tmSTsttf7aknunnaUm/AaYBW0g6Pe1jpqRzUvtOku6R9GRa9/D2OKlmZlaZg7tt/Bo4SlLXsvlXAJdFxG7AIcDVaf4EYBCwI/AssFeavwfweH4DEXEQsDQi+kTETY1scy4wOCL6AmcBP4uI99Pjm3LrN2Zb4Pq0jW2BXsAAsl77rpIGA/sDiyJil4jYCbiv6dNjZmZtZY1aF7AqiIg3JV0PnAwszS0aCuwgqTS9jqQuwCPAYOB54EpguKTNgNcjYkkTu2tom12B6yT1AgLo0IJDeT4iShcO+6Wf6Wm6M1mQPwJcLOlC4O6IeKR8I5KGA8MBNv7Up1pQhpmZNcTB3XYuJxti/kNu3mrAwIjIhzmSxgMnAD2AM4CDgUPJQrEpDW3zl8DDEXGwpJ7A2AbW/5AVR1o65h6/nd8kcH5EXFW+AUm7kt03P1/SmIg4N788IkaQ3T5g2y5doopjMjOzKnmovI1ExOvAzcA3c7PHACeWJiT1SW0XAN2AXhHxLPAocBrVBXfFbZL1uF9Ij4fl2r8FdMlNPwf0S+v2A7ZqYD/3A8dK6pzabiZpI0ndgXci4o/AxaVtmZnZx8PB3bYuIQvkkpOB/unNXU8Bx+eWTQL+lh4/AmxGFuBNaWibPyfrAU8AVs+1f5hsaH1GeiPZrcD6kmYA387VsIKIGAP8CZgoaRZwC9kFwM7A5LT+GcBPqqjZzMzaiCI8kmntZ9suXWJEX3fKVzV7jx9X6xLMVmmSpkZE/0rL3OM2MzMrEAe3mZlZgTi4zczMCsTBbWZmViAObjMzswJxcJuZmRWIg9vMzKxAHNxmZmYF4uA2MzMrEAe3mZlZgTi4zczMCsTBbWZmViD+Pm5rV1223dZfSGFm1obc4zYzMysQB7eZmVmBOLjNzMwKxMFtZmZWIA5uMzOzAnFwm5mZFYiD28zMrEAc3GZmZgXiD2CxdvXKwsX86vt31boMa8SJl3yp1iWYWTO4x21mZlYgDm4zM7MCcXCbmZkViIPbzMysQBzcZmZmBeLgNjMzKxAHt5mZWYE4uM3MzArEwW1mZlYgDm4zM7MCcXCbmZkViIPbzMysQBzcZmZmBeJvB6szkpYBswABy4ATI+KxNtr2KGBH4A/AesD4iPhrW2zbzMw+Hg7u+rM0IvoASPoP4Hxg79ZuVNImwGcjYsvWbsvMzGrHQ+X1bR3gDQBJQyTdXVog6VeShqXHB0qaK+lRSb/It8sZA2wkaYakvSRdK+lQSV0lzZO0bdrWKEnfSo9Pl/SEpJmSzknzOkm6R9KTkmZLOrx9T4GZmeW5x11/1pI0A+gIbArs21hjSR2Bq4DBETE/DYdXchBwd643/02AiFgs6UTgWklXAOtFxO8k7Qf0AgaQDduPljQY2BBYFBFfSNvpWqGm4cBwgPW6bNicYzczsya4x11/lkZEn4jYDtgfuF6SGmm/HfBsRMxP0w0Fd4Mi4gGy++q/Bv47zd4v/UwHpqX99Erthkq6UNJeEbG4wvZGRET/iOjfee2Vct3MzFrBPe46FhETJXUj6+V+yIoXWh3T78ZCvSqSVgO2B5YC6wML03bPj4irKrTfFTgQOF/SmIg4t7U1mJlZddzjrmOStgNWB/4JPA/sIOlTaXj6c6nZXGBrST3TdEvuOX8PeBo4ErhGUgfgfuBYSZ1TLZtJ2khSd+CdiPgjcDHQr2VHZ2ZmLeEed/0p3eOGrNd7TEQsAxZIuhmYCTxDNoRNRCyV9B3gPkmvAZObszNJnyEbHh8QEW9JGg+cGRH/K2l7YGIaqV8C/BewDXCRpI+AD4Bvt+5wzcysORQRta7BWklS54hYku6F/xp4JiIuq3VdAD026RU/OOrSWpdhjTjxki/VugQzKyNpakT0r7TMQ+Wrhm+lXvocoCvZu8zNzGwV5KHyVUDqXddFD9vMzNqXe9xmZmYF4uA2MzMrEAe3mZlZgTi4zczMCsTBbWZmViAObjMzswJxcJuZmRWIg9vMzKxAHNxmZmYF4k9Os3a10eZd/VnYZmZtyD1uMzOzAnFwm5mZFYiD28zMrEAc3GZmZgWiiKh1DbYKk/QWMK/WdTRDN+C1WhfRDEWqt0i1guttb0Wqtxa1bhkRG1Za4HeVW3ubFxH9a11EtSRNcb3to0i1guttb0Wqt95q9VC5mZlZgTi4zczMCsTBbe1tRK0LaCbX236KVCu43vZWpHrrqla/Oc3MzKxA3OM2MzMrEAe3mZlZgTi4rd1I2l/SPEl/l/TDWtdTTtI1kl6RNDs3b31JD0h6Jv1er5Y1lkjaQtLDkp6WNEfSd9P8eq23o6TJkp5M9Z6T5tdlvQCSVpc0XdLdabqea31O0ixJMyRNSfPqud51Jd0iaW56DQ+s13olbZvOa+nnTUmn1FO9Dm5rF5JWB34NHADsABwpaYfaVrWSa4H9y+b9EHgwInoBD6bpevAh8P2I2B7YAzghnc96rfc9YN+I2AXoA+wvaQ/qt16A7wJP56bruVaAfSKiT+7vi+u53iuA+yJiO2AXsvNcl/VGxLx0XvsAuwLvALdTT/VGhH/80+Y/wEDg/tz0j4Af1bquCnX2BGbnpucBm6bHm5J9gEzN66xQ953A54tQL7A2MA3YvV7rBTYn+894X+Duen8tAM8B3crm1WW9wDrAfNKboeu93rIa9wMm1Fu97nFbe9kMWJCbXpjm1buNI+JFgPR7oxrXsxJJPYG+wCTquN409DwDeAV4ICLqud7LgR8AH+Xm1WutAAGMkTRV0vA0r17r3Rp4FfhDuhVxtaRO1G+9eUcAo9LjuqnXwW3tRRXm+W8PW0lSZ+BW4JSIeLPW9TQmIpZFNty4OTBA0k41LqkiSV8EXomIqbWupRkGRUQ/sltRJ0gaXOuCGrEG0A+4MiL6Am9TJ8PijZG0JnAQ8Oda11LOwW3tZSGwRW56c2BRjWppjpclbQqQfr9S43r+TVIHstAeGRG3pdl1W29JRPwLGEv2foJ6rHcQcJCk54AbgX0l/ZH6rBWAiFiUfr9Cdv91APVb70JgYRpxAbiFLMjrtd6SA4BpEfFymq6beh3c1l6eAHpJ2ipduR4BjK5xTdUYDRyTHh9Ddi+55iQJ+D3wdERcmltUr/VuKGnd9HgtYCgwlzqsNyJ+FBGbR0RPstfpQxHxX9RhrQCSOknqUnpMdh92NnVab0S8BCyQtG2a9TngKeq03pwjWT5MDnVUrz85zdqNpAPJ7h2uDlwTET+tbUUrkjQKGEL2lX0vA/8L3AHcDPQA/gH8Z0S8XqMS/03SnsAjwCyW34f9Mdl97nqstzdwHdlzvxpwc0ScK2kD6rDeEklDgNMi4ov1Wqukrcl62ZANQ/8pIn5ar/UCSOoDXA2sCTwLfIP0uqA+612b7D06W0fE4jSvbs6vg9vMzKxAPFRuZmZWIA5uMzOzAnFwm5mZFYiD28zMrEAc3GZmZgXi4DYza0L6dqi1a12HGfjPwczMmpQ+Va1/RLxW61rM3OM2s1WCpKMlzUzfAX6DpC0lPZjmPSipR2p3raRDc+stSb+HSBqb+97okcqcDHQHHpb0cG2Ozmy5NWpdgJlZa0naETiD7Ms3XpO0Ptknt10fEddJOhb4BfCVJjbVF9iR7HP1J6Tt/ULSqWTff+0et9Wce9xmtirYF7ilFKzpoygHAn9Ky28A9qxiO5MjYmFEfATMIPu+drO64uA2s1WBaPprY0vLPyT935e+vGXNXJv3co+X4VFJq0MObjNbFTwIHJa+CII0VP4Y2bd9ARwFPJoePwfsmh5/GehQxfbfArq0VbFmreGrSTMrvIiYI+mnwDhJy4DpwMnANZJOB14l+0YqgN8Bd0qaTBb4b1exixHAvZJejIh92v4IzKrnPwczMzMrEA+Vm5mZFYiD28zMrEAc3GZmZgXi4DYzMysQB7eZmVmBOLjNzMwKxMFtZmZWIP8fS+A7P1/gcyIAAAAASUVORK5CYII=\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "q = \"Which would help you most right now?\"\n", "order = [\n", " \"More documentation\",\n", " \"More examples in my field\",\n", " \"Performance improvements\",\n", " \"New features\",\n", " \"Bug fixes\",\n", "] \n", "ax = sns.countplot(y=q, data=df2021[q].explode().to_frame(), order=order)\n", "ax.set(ylabel=\"\", title=q);" ] }, { "cell_type": "markdown", "id": "16d42bfb-fd54-43ca-b162-e9e37e4a5dee", "metadata": {}, "source": [ "### How can Dask improve?\n", "\n", "We also gave people the opportunity for a free text response to the question \"How can Dask imporove?\"\n", "\n", "Matt has previously written an [early anecdotes blogpost](https://blog.dask.org/2021/06/18/early-survey)\n", "that dives into the responses to this question in more detail.\n", "\n", "He found these recurring themes:\n", "\n", "- Intermediate Documentation\n", "- Documentation Organization\n", "- Functionality\n", "- High Level Optimization\n", "- Runtime Stability and Advanced Troubleshooting\n", "\n", "Since more documentation and examples were the two most requested improvements, I'll summarize some of the steps forward in that area here:\n", "\n", "- Regarding more intermediate documentation, Matt says:\n", " > There is a lot of good potential material that advanced users have around performance and debugging that could be fun to publish.\n", "\n", "- Matt points out that Dask has excellent *reference documentation*, but lacks a lot of good *narrative documentation*. To address this, Julia Signell is currently investigating how we could improve the organization of Dask's documentation (you can subscribe to [this issue thread](https://github.com/dask/community/issues/170) if you want to follow that discussion)\n", "\n", "- Matt comments that it's hard to have good *narrative documentation* when there are so many different *user narratives* (i.e. Dask is used by people from many different industries). This year, we added a new question to the survey asking for the industry people work in. We added this because *\"More examples in my field\"* has been one of the top two requests for the last three years. Now we can use that information to better target narrative documentation to the areas that need it most (geoscience, life science, and finance)." ] }, { "cell_type": "code", "execution_count": 35, "id": "0d3d8960-64b7-474d-859d-41e64317439b", "metadata": { "execution": { "iopub.execute_input": "2022-07-27T19:24:40.237181Z", "iopub.status.busy": "2022-07-27T19:24:40.236847Z", "iopub.status.idle": "2022-07-27T19:24:40.386329Z", "shell.execute_reply": "2022-07-27T19:24:40.385740Z" } }, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "q = 'What industry do you work in?'\n", "data = df2021[df2021[\"Which would help you most right now?\"] == \"More examples in my field\"]\n", "order = data[q].value_counts()[data[q].value_counts() > 1].keys()\n", "ax = sns.countplot(y=q, data=data[q].dropna().str.split(', ').explode().to_frame(), order=order);\n", "ax.set(ylabel=\"\", title=\"What field do you want more documentation examples for?\");" ] }, { "cell_type": "markdown", "id": "3d377cfb-2127-4f9d-87a8-b99f2794c64b", "metadata": {}, "source": [ "### What common feature requests do you care about most?\n", "\n", "Good support for numpy and pandas is critical for most users.\n", "Users also value:\n", "\n", "- Improved scaling\n", "- Ease of deployment\n", "- Resiliancy of Dask\n", "- Better scikit-learn & machine learning support\n", "\n", "Most feature requests are similar to the survey results from previous years, although there was an increase in the number of people who say better scikit-learn/ML support is critical to them. We also added a new question about Dask's resiliancy in 2021.\n", "\n", "In the figure below you can see how people rated the importance of each feature request, for each of the three years we've run this survey." ] }, { "cell_type": "code", "execution_count": 36, "id": "f32b754c-fbf1-4f8d-877e-8fe9f94e53dc", "metadata": { "execution": { "iopub.execute_input": "2022-07-27T19:24:40.389911Z", "iopub.status.busy": "2022-07-27T19:24:40.389438Z", "iopub.status.idle": "2022-07-27T19:24:44.790384Z", "shell.execute_reply": "2022-07-27T19:24:44.789832Z" } }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "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", "c = common.loc[2021].apply(pd.value_counts).T.stack().reset_index().rename(columns={'level_0': 'Question', 'level_1': \"Importance\", 0: \"count\"}).assign(Year=2021)\n", "\n", "counts = pd.concat([a, b, c], 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(x='Importance', row=\"Feature\", kind=\"count\", col=\"Year\", data=d, sharex=False, order=order);" ] }, { "cell_type": "markdown", "id": "139409e8-7938-44dc-bf4e-6629605bb466", "metadata": {}, "source": [ "## Previous survey results \n", "\n", "Thanks to everyone who took the survey!\n", "\n", "If you want to read more about the 2021 Dask survey, the blogpost on early anecdotes from the Dask 2021 survey [is available here](https://blog.dask.org/2021/06/18/early-survey).\n", "\n", "You can read the survey results from previous years here: \n", "\n", "- [2020 survey results](https://blog.dask.org/2020/09/22/user_survey)\n", "- [2019 survey results](https://blog.dask.org/2019/08/05/user-survey).\n" ] } ], "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": 5 }