diff --git a/surveys/2019.ipynb b/surveys/2019.ipynb index 6c01f527..e085536d 100644 --- a/surveys/2019.ipynb +++ b/surveys/2019.ipynb @@ -2,7 +2,6 @@ "cells": [ { "cell_type": "markdown", - "metadata": {}, "source": [ "# 2019 Dask User Survey Results\n", "\n", @@ -10,6 +9,10 @@ "which ran earlier this summer. Thanks to everyone who took the time to fill out the survey!\n", "These results help us better understand the Dask community and will guide future development efforts.\n", "\n", + "The raw data, as well as the start of an analysis, can be found in this binder:\n", + "\n", + "[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/dask/dask-examples/main?urlpath=%2Ftree%2Fsurveys%2F2019.ipynb)\n", + "\n", "Let us know if you find anything in the data.\n", "\n", "## Highlights\n", @@ -17,13 +20,12 @@ "We had 259 responses to the survey. Overall, we found that the survey respondents really care about improved documentation, and ease of use (including ease of deployment), and scaling. While Dask brings together many different communities (big arrays versus big dataframes, traditional HPC users versus cloud-native resource managers), there was general agreement in what is most important for Dask.\n", "\n", "Now we'll go through some individual items questions, highlighting particularly interesting results." - ] + ], + "metadata": {} }, { "cell_type": "code", "execution_count": null, - "metadata": {}, - "outputs": [], "source": [ "%matplotlib inline\n", "\n", @@ -57,27 +59,27 @@ " 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", ")" - ] + ], + "outputs": [], + "metadata": {} }, { "cell_type": "markdown", - "metadata": {}, "source": [ "## How do you use Dask?" - ] + ], + "metadata": {} }, { "cell_type": "markdown", - "metadata": {}, "source": [ "For learning resources, almost every respondent uses the documentation." - ] + ], + "metadata": {} }, { "cell_type": "code", "execution_count": null, - "metadata": {}, - "outputs": [], "source": [ "ax = (\n", " df['What Dask resources have you used for support in the last six months?']\n", @@ -86,20 +88,20 @@ " .div(len(df)).mul(100).plot.barh()\n", ");\n", "fmt_percent(ax).set(title=\"Support Resource Usage\");" - ] + ], + "outputs": [], + "metadata": {} }, { "cell_type": "markdown", - "metadata": {}, "source": [ "Most respondents use Dask at least occasionally. Fortunately we had a decent number of respondents who are just looking into Dask, yet still spent the time to take the survey." - ] + ], + "metadata": {} }, { "cell_type": "code", "execution_count": null, - "metadata": {}, - "outputs": [], "source": [ "usage_order = [\n", " 'Every day',\n", @@ -108,20 +110,20 @@ "]\n", "ax = df['How often do you use Dask?'].value_counts().loc[usage_order].div(len(df)).mul(100).plot.barh()\n", "fmt_percent(ax).set(title=\"How often do you use Dask?\");" - ] + ], + "outputs": [], + "metadata": {} }, { "cell_type": "markdown", - "metadata": {}, "source": [ "I'm curiuos about how learning resource usage changes as users become more experienced. We might expect those just looking into Dask to start with `examples.dask.org`, where they can try out Dask without installing anything." - ] + ], + "metadata": {} }, { "cell_type": "code", "execution_count": null, - "metadata": {}, - "outputs": [], "source": [ "resources = df['What Dask resources have you used for support in the last six months?'].str.split(\";\").explode()\n", "top = resources.value_counts().head(6).index\n", @@ -139,11 +141,12 @@ " order=usage_order,\n", " data=m, ax=ax)\n", "sns.despine()" - ] + ], + "outputs": [], + "metadata": {} }, { "cell_type": "markdown", - "metadata": {}, "source": [ "Overall, documentation is still the leader across user user groups.\n", "\n", @@ -151,13 +154,12 @@ "\n", "From StackOverflow questions and GitHub issues, we have a vague idea about which parts of the library are used.\n", "The survey shows that (for our respondents at least) DataFrame and Delayed are the most commonly used APIs." - ] + ], + "metadata": {} }, { "cell_type": "code", "execution_count": null, - "metadata": {}, - "outputs": [], "source": [ "api_counts = (\n", " df['Dask APIs'].str.split(\";\").explode().value_counts()\n", @@ -166,32 +168,32 @@ "ax = api_counts.sort_values().nlargest(8).plot.barh()\n", "fmt_percent(ax).set(xlabel=\"Percent\")\n", "sns.despine();" - ] + ], + "outputs": [], + "metadata": {} }, { "cell_type": "code", "execution_count": null, - "metadata": {}, - "outputs": [], "source": [ "print(\"About {:0.2%} of our respondests are using Dask on a Cluster.\".format(df['Local machine or Cluster?'].str.contains(\"Cluster\").mean()))" - ] + ], + "outputs": [], + "metadata": {} }, { "cell_type": "markdown", - "metadata": {}, "source": [ "But the majority of respondents *also* use Dask on their laptop.\n", "This highlights the importance of Dask scaling down, either for\n", "prototyping with a `LocalCluster`, or for out-of-core analysis\n", "using `LocalCluster` or one of the single-machine schedulers." - ] + ], + "metadata": {} }, { "cell_type": "code", "execution_count": null, - "metadata": {}, - "outputs": [], "source": [ "order = [\n", " 'Personal laptop',\n", @@ -202,20 +204,20 @@ "]\n", "df['Local machine or Cluster?'].str.split(\";\").explode().value_counts().loc[order].plot.barh();\n", "sns.despine()" - ] + ], + "outputs": [], + "metadata": {} }, { "cell_type": "markdown", - "metadata": {}, "source": [ "Most respondents use Dask interactively, at least some of the time." - ] + ], + "metadata": {} }, { "cell_type": "code", "execution_count": null, - "metadata": {}, - "outputs": [], "source": [ "mapper = {\n", " \"Interactive: I use Dask with Jupyter or IPython when playing with data;Batch: I submit scripts that run in the future\": \"Both\",\n", @@ -228,20 +230,20 @@ "sns.despine()\n", "fmt_percent(ax)\n", "ax.set(title='Interactive or Batch?');" - ] + ], + "outputs": [], + "metadata": {} }, { "cell_type": "markdown", - "metadata": {}, "source": [ "Most repondents thought that more documentation and examples would be the most valuable improvements to the project. This is especially pronounced among new users. But even among those using Dask everyday more people thought that \"More examples\" is more valuable than \"New features\" or \"Performance improvements\"." - ] + ], + "metadata": {} }, { "cell_type": "code", "execution_count": null, - "metadata": {}, - "outputs": [], "source": [ "help_by_use = (\n", " df.groupby(\"How often do you use Dask?\")['Which would help you most right now?']\n", @@ -257,20 +259,20 @@ " \"users with that usage frequency prefer that priority.\")\n", ")\n", "s" - ] + ], + "outputs": [], + "metadata": {} }, { "cell_type": "markdown", - "metadata": {}, "source": [ "Perhaps users of certain dask APIs feel differenlty from the group as a whole? We perform a similar analysis grouped by API use, rather than frequency of use." - ] + ], + "metadata": {} }, { "cell_type": "code", "execution_count": null, - "metadata": {}, - "outputs": [], "source": [ "help_by_api = (\n", " pd.merge(\n", @@ -289,29 +291,29 @@ " .set_caption(\"Normalized by row. Darker means that a higher proporiton of \"\n", " \"users of that API prefer that priority.\")\n", ")" - ] + ], + "outputs": [], + "metadata": {} }, { "cell_type": "markdown", - "metadata": {}, "source": [ "Nothing really stands out. The \"futures\" users (who we expect to be relatively advanced) may prioritize features and performance over documentation. But everyone agrees that more examples are the highest priority." - ] + ], + "metadata": {} }, { "cell_type": "markdown", - "metadata": {}, "source": [ "## Common Feature Requests\n", "\n", "For specific features, we made a list of things that we (as developers) thought might be important." - ] + ], + "metadata": {} }, { "cell_type": "code", "execution_count": null, - "metadata": {}, - "outputs": [], "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", @@ -327,11 +329,12 @@ " sns.FacetGrid(counts, col=\"Question\", col_wrap=2, aspect=1.5, sharex=False, height=3)\n", " .map(sns.barplot, \"Importance\", \"count\", order=order)\n", ")" - ] + ], + "outputs": [], + "metadata": {} }, { "cell_type": "markdown", - "metadata": {}, "source": [ "The clearest standout is how many people thought \"Better NumPy/Pandas support\" was \"most critical\". In hindsight, it'd be good to have a followup fill-in field to undertand what each respondent meant by that. The parsimonious interpretion is \"cover more of the NumPy / pandas API\".\n", "\n", @@ -340,54 +343,53 @@ "Relatively few respondents care about things like \"Managing many users\", though we expect that this would be relatively popular among system administartors, who are a smaller population.\n", "\n", "And of course, we have people pushing Dask to its limits for whom \"Improving scaling\" is critically important." - ] + ], + "metadata": {} }, { "cell_type": "markdown", - "metadata": {}, "source": [ "## What other systems do you use?\n", "\n", "A relatively high proportion of respondents use Python 3 (97% compared to 84% in the most recent [Python Developers Survey](https://www.jetbrains.com/research/python-developers-survey-2018/))." - ] + ], + "metadata": {} }, { "cell_type": "code", "execution_count": null, - "metadata": {}, - "outputs": [], "source": [ "df['Python 2 or 3?'].dropna().astype(int).value_counts(normalize=True).apply(\"{:0.2%}\".format)" - ] + ], + "outputs": [], + "metadata": {} }, { "cell_type": "markdown", - "metadata": {}, "source": [ "We were a bit surprised to see that SSH is the most popular \"cluster resource manager\"." - ] + ], + "metadata": {} }, { "cell_type": "code", "execution_count": null, - "metadata": {}, - "outputs": [], "source": [ "df['If you use a cluster, how do you launch Dask? '].dropna().str.split(\";\").explode().value_counts().head(6)" - ] + ], + "outputs": [], + "metadata": {} }, { "cell_type": "markdown", - "metadata": {}, "source": [ "How does cluster-resource manager compare with API usage?" - ] + ], + "metadata": {} }, { "cell_type": "code", "execution_count": null, - "metadata": {}, - "outputs": [], "source": [ "managers = (\n", " df['If you use a cluster, how do you launch Dask? '].str.split(\";\").explode().dropna()\n", @@ -403,37 +405,38 @@ "\n", "x = wm.groupby(\"Dask APIs\")[\"If you use a cluster, how do you launch Dask? \"].value_counts().unstack().T\n", "x.style.background_gradient(axis=\"columns\")" - ] + ], + "outputs": [], + "metadata": {} }, { "cell_type": "markdown", - "metadata": {}, "source": [ "HPC users are relatively heavy users of `dask.array` and xarray." - ] + ], + "metadata": {} }, { "cell_type": "markdown", - "metadata": {}, "source": [ "Somewhat surprisingly, Dask's heaviest users find dask stable enough. Perhaps they've pushed past the bugs and found workarounds (percentages are normalized by row)." - ] + ], + "metadata": {} }, { "cell_type": "code", "execution_count": null, - "metadata": {}, - "outputs": [], "source": [ "fig, ax = plt.subplots(figsize=(9, 6))\n", "sns.countplot(x=\"How often do you use Dask?\", hue=\"Is Dask stable enough for you?\", data=df, ax=ax,\n", " order=reversed(usage_order));\n", "sns.despine()" - ] + ], + "outputs": [], + "metadata": {} }, { "cell_type": "markdown", - "metadata": {}, "source": [ "## Takeaways\n", "\n", @@ -446,7 +449,8 @@ "4. Dask's various sub-communities are more similar than they are different.\n", "\n", "Thanks again to all the respondents. We look forward to repeating this process to identify trends over time." - ] + ], + "metadata": {} } ], "metadata": { @@ -470,4 +474,4 @@ }, "nbformat": 4, "nbformat_minor": 2 -} +} \ No newline at end of file diff --git a/surveys/2020.ipynb b/surveys/2020.ipynb index 83b35372..6ed487cb 100644 --- a/surveys/2020.ipynb +++ b/surveys/2020.ipynb @@ -2,7 +2,6 @@ "cells": [ { "cell_type": "markdown", - "metadata": {}, "source": [ "# 2020 Dask User Survey Results\n", "\n", @@ -12,20 +11,19 @@ "\n", "The raw data, as well as the start of an analysis, can be found in this binder:\n", "\n", - "[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/dask/dask-examples/main?filepath=surveys/2020.ipynb)\n", + "[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/dask/dask-examples/main?urlpath=%2Ftree%2Fsurveys%2F2020.ipynb)\n", "\n", "Let us know if you find anything in the data.\n", "\n", "## Highlights\n", "\n", "We had 240 responses to the survey (slightly fewer than last year, which had about 260). Overall things were similar to last year's. The biggest shift in the community is a stronger demand for better performance." - ] + ], + "metadata": {} }, { "cell_type": "code", "execution_count": 1, - "metadata": {}, - "outputs": [], "source": [ "%matplotlib inline\n", "\n", @@ -55,99 +53,86 @@ "df = pd.concat([df2019, df2020])\n", "df['Year'] = df.Timestamp.dt.year\n", "df = df.set_index(['Year', 'Timestamp']).sort_index()" - ] + ], + "outputs": [], + "metadata": {} }, { "cell_type": "markdown", - "metadata": {}, "source": [ "Most of the questions are the same as in 2019. We added a couple questions about deployment and dashboard usage. Let's look at those first.\n", "\n", "Among respondents who use a Dask package to deploy a cluster (about 53% of respondents), there's a wide spread of methods." - ] + ], + "metadata": {} }, { "cell_type": "code", "execution_count": 2, - "metadata": {}, + "source": [ + "k = 'Do you use Dask projects to deploy?'\n", + "d = df2020['Do you use Dask projects to deploy?'].dropna().str.split(\";\").explode()\n", + "top = d.value_counts()\n", + "top = top[top > 10].index\n", + "sns.countplot(y=k, data=d[d.isin(top)].to_frame(), order=top);" + ], "outputs": [ { + "output_type": "display_data", "data": { - "image/png": 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\n", 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", 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" ] }, "metadata": { "needs_background": "light" - }, - "output_type": "display_data" + } } ], - "source": [ - "k = 'Do you use Dask projects to deploy?'\n", - "d = df2020['Do you use Dask projects to deploy?'].dropna().str.split(\";\").explode()\n", - "top = d.value_counts()\n", - "top = top[top > 10].index\n", - "sns.countplot(y=k, data=d[d.isin(top)].to_frame(), order=top);" - ] + "metadata": {} }, { "cell_type": "markdown", - "metadata": {}, "source": [ "Most people access the dashboard through a web browser. Those not using the dashboard are likely (hopefully) just using Dask on a single machine with the threaded scheduler (though the dashboard works fine on a single machine as well)." - ] + ], + "metadata": {} }, { "cell_type": "code", "execution_count": 3, - "metadata": {}, + "source": [ + "k = \"How do you view Dask's dashboard?\"\n", + "sns.countplot(y=k, data=df2020[k].dropna().str.split(\";\").explode().to_frame());" + ], "outputs": [ { + "output_type": "display_data", "data": { - "image/png": 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\n", 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", 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" ] }, "metadata": { "needs_background": "light" - }, - "output_type": "display_data" + } } ], - "source": [ - "k = \"How do you view Dask's dashboard?\"\n", - "sns.countplot(y=k, data=df2020[k].dropna().str.split(\";\").explode().to_frame());" - ] + "metadata": {} }, { "cell_type": "markdown", - "metadata": {}, "source": [ "Dask's learning materials are farily similar to last year. The most notable differences are from\n", "our survey form providing more options (our [YouTube channel](https://www.youtube.com/channel/UCj9eavqmvwaCyKhIlu2GaoA) and \"Gitter chat\"). Other than that, https://examples.dask.org might be relatively more popular." - ] + ], + "metadata": {} }, { "cell_type": "code", "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], "source": [ "k = 'What Dask resources have you used for support in the last six months?'\n", "\n", @@ -164,40 +149,40 @@ "fig, ax = plt.subplots(figsize=(8, 8))\n", "ax = sns.countplot(y=k, hue=\"Year\", data=d.reset_index(), ax=ax);\n", "ax.set(ylabel=\"\", title=k);" - ] + ], + "outputs": [ + { + "output_type": "display_data", + "data": { + "image/png": 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", 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\n", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], "source": [ "resource_palette = (\n", " df['What Dask resources have you used for support in the last six months?'].str.split(\";\").explode().replace(resource_map).replace(re.compile(\"GitHub.*\"), \"GitHub\").value_counts()[:6].index\n", @@ -235,11 +220,25 @@ "ax2 = resource_plot(df, 2020, axes[1])\n", "ax1.set_title(\"2019\")\n", "ax2.set_title(\"2020\");" - ] + ], + "outputs": [ + { + "output_type": "display_data", + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + } + } + ], + "metadata": {} }, { "cell_type": "markdown", - "metadata": {}, "source": [ "A few observations\n", "\n", @@ -249,47 +248,51 @@ "* In response to last year's survey, we invested time in making https://tutorial.dask.org better, which we previously felt was lacking. Its usage is still about the same as last year's (pretty popular), so it's unclear whether we should dedicate additional focus there.\n", "\n", "API usage remains about the same as last year (recall that about 20 fewer people took the survey and people can select multiple, so relative differences are most interesting). We added new choices for RAPIDS, Prefect, and XGBoost, each of which are somewhat popular (in the neighborhood of `dask.Bag`)." - ] + ], + "metadata": {} }, { "cell_type": "code", "execution_count": 6, - "metadata": {}, + "source": [ + "apis = df['Dask APIs'].str.split(\";\").explode()\n", + "top = apis.value_counts().loc[lambda x: x > 10]\n", + "apis = apis[apis.isin(top.index)].reset_index()\n", + "\n", + "sns.countplot(y=\"Dask APIs\", hue=\"Year\", data=apis);" + ], "outputs": [ { + "output_type": "display_data", "data": { - "image/png": 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\n", 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", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" - }, - "output_type": "display_data" + } } ], - "source": [ - "apis = df['Dask APIs'].str.split(\";\").explode()\n", - "top = apis.value_counts().loc[lambda x: x > 10]\n", - "apis = apis[apis.isin(top.index)].reset_index()\n", - "\n", - "sns.countplot(y=\"Dask APIs\", hue=\"Year\", data=apis);" - ] + "metadata": {} }, { "cell_type": "markdown", - "metadata": {}, "source": [ "Just like last year, about 65% of our users are using Dask on a cluster at least some of the time." - ] + ], + "metadata": {} }, { "cell_type": "code", "execution_count": 7, - "metadata": {}, + "source": [ + "df['Local machine or Cluster?'].dropna().str.contains(\"Cluster\").astype(int).groupby(\"Year\").mean()" + ], "outputs": [ { + "output_type": "execute_result", "data": { "text/plain": [ "Year\n", @@ -298,70 +301,86 @@ "Name: Local machine or Cluster?, dtype: float64" ] }, - "execution_count": 7, "metadata": {}, - "output_type": "execute_result" + "execution_count": 7 } ], - "source": [ - "df['Local machine or Cluster?'].dropna().str.contains(\"Cluster\").astype(int).groupby(\"Year\").mean()" - ] + "metadata": {} }, { "cell_type": "markdown", - "metadata": {}, "source": [ "But the majority of respondents *also* use Dask on their laptop.\n", "This highlights the importance of Dask scaling down, either for\n", "prototyping with a `LocalCluster`, or for out-of-core analysis\n", "using `LocalCluster` or one of the single-machine schedulers." - ] + ], + "metadata": {} }, { "cell_type": "code", "execution_count": 8, - "metadata": {}, + "source": [ + "order = [\n", + " 'Personal laptop',\n", + " 'Large workstation',\n", + " 'Cluster of 2-10 machines',\n", + " 'Cluster with 10-100 machines',\n", + " 'Cluster with 100+ machines'\n", + "]\n", + "d = df['Local machine or Cluster?'].str.split(\";\").explode().reset_index()\n", + "sns.countplot(y=\"Local machine or Cluster?\", data=d, hue=\"Year\", order=order);" + ], "outputs": [ { + "output_type": "display_data", "data": { - "image/png": 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2cBzwVKUYdge+B3QHvgP8l6SmecZVFBExJSLOLWUMZmZWPLUmEBFxDXAfcD+wK3BZRFxX7MBqcTCwMiJGVBRExIyImJS7UmpRuD7n+ThJB0lqKmmUpNmSZkm6QNIJQB/gjtRK0EpSb0lPphaOv0nqmOqZKGm4pClkNxrL3WcHSQ+m1oTJknpI2pps3EjfVPc3c7eJiEcjYlV6OhnoXNVBR8S8iHi5ipcGAndFxIqIeAN4FehXeSVJy1Nrx5zUGtIvHcvr6Y6rpBacSZJeTI/9c7a/JJ2vGekmaxVOlPS8pFck9U/rHiRpXFoeKumWnH2dm1PnD9O20yX9d3pvvvb+VHU+zMysdPK9kNQEsl/J5WIPYOp6bN8T6BQRewBIahcRH0k6B7goIqZIag5cBwyMiPdSt8OVwBmpjhYR8bWme+A3wLSIOEbSIcBtEdFT0lmp7qNqie0MoHILRW06kSUeFRamsspaA49HxMWSHgB+B3wb2B0YTXaxsHeBb0fEF5J2Bu4E+kg6kixR2SciPpPUIafeZhHRT9J3gcuBw6rY925kiV8b4GVJNwI7AScD34qIlZL+CzgFmEOl96eqg5Y0GBgM0Kltcx5oc3WNJ8msnL15Rf1+fre/bFa91mdWWa0JhKTjgKuArcnuhSEgImLzIsdWTK8DO0q6DngYeLSKdXYlS1QmZD0mNAUW57xe3Zf8AcDxABHxuKQtJOV1riRdCqwC7shn/Tr4EhiflmcBK9IX9yygSypvDlwvqSewGtgllR8G3BoRnwFExAc59Y5J/07NqaeyhyNiBbBC0rtk3U2HAr2BF9I5bkWWwPyV2t8fIuIm4CaAHp1aRe2Hb2Zm9SWfFog/AEdHxLxiB1OAOcAJeay3inW7aVoCRMSHkvYCjgDOBk7iq5aFCgLmRMR+1dT9aUER10LSacBRwKFp0CqSbiUbO/F2RHy3hs0XAdvlPO+cyipbWVE3sAZYARARa3LGclwALAH2Ijt3X+QR/or072qq/0ytyFmuWE/A6Ij42piPPN4fMzMroXwGUS4ps+QB4HFgk9SEDUAaa9C/0noLgJ6SmkjajjQuQNKWQJOIuB/4FdArrb+Mr6aovgxsJWm/tE1zSd3ziG0SWTM8kg4C3o+IT2raQNJ3gF8AAyp+4QNExOlp0GVNyQNkXQ/fUzbToyuwM/B8HrFWpS2wOCLWAD8ia3mBrAvrdEmbppg7VLN9IR4DTkhjRCrGj+xQw/tjZmZlIp8WiCmS7gYeJOdXZESMqXaLIouIkHQsMFzSJWS/khcA51da9RngDWAuMA94MZV3Am6VVJFAVfwCHgWMkPQ5sB9ZK8e1ktqSnavhZK0fNRkK3CJpJvAZcGoeh3Q9sAlfdZdMjoizK6+Ujvk6YCvgYUnTI+KIiJgj6Z50nKuAn0XE6jz2W5X/Au6XNIisu6Pi+h/jU7fGFElfAo8A/1bHfZDqnCvpV8Cj6b1YCfwM+Jyq3x8zMysT+qpFu5oVsmb0yiIi3KRsZaNHp1Yx7ic7lToMs7LhQZSWD0lTq5kQUKtaWyAi4vS6VGxmZmYbrmoTCEm/iIg/pJHwX2um8EWCzMzMNl41tUBUDJyc0hCBmJmZWeNRbQIREX9N/45uuHDMzMysMcjnQlK7ABeRXSBo7foRcUjxwjIzM7Nyls80znuBEcCfyS4AZGZmZhu5fBKIVRFxY9EjMTMzs0ajplkYFVca/Kukn5LdPjv3QlIfVLmhmZmZbfBqaoGYSjZ9U+n5xTmvBbBjsYIyMzOz8lbTLIyuDRmImZmZNR613kxL0s8ktct53j51aZiZmdlGKp97YUyPiJ6VyqZFxN7FDMysEH369IkpU3zNMzOzQqzPvTDyuZ13U6VbRKadNQVa1GVnZmZmtmHIZxrneOBuSf+dnv8klZmZmdlGKp8E4hKypOFf0vMJZBeVMjMzs41UPrfzXgPcmB5mZmZmed0LY2fg98DuQMuK8ojwdSDMzMw2UvkMoryVrPVhFXAwcBvwl2IGZWZmZuUtnwSiVUQ8Rjbl8x8RMRT45+KGZWZmZuUsn0GUKyQ1AeZLOgdYBGxW3LDMzMysnOWTQJwHbAqcC/wWOAQ4tZhBmRVq3sKl9L74tlKHYfVo6tWDSh2CmdUgn1kYL6TF5cDpxQ3HzMzMGoN8ZmH0AS4FdshdPyJ6FDEuMzMzK2P5dGHcQXYr71nAmuKGY2ZmZo1BPgnEexHxUNEjMTMzs0YjnwTickl/Bh4DVlQURsSYokVlZmZmZS2fBOJ0YDegOV91YQTgBMLMzGwjlU8C0Tcidi16JGZmZtZo5HMlymcl7V70SMzMzKzRyKcFYl9guqQ3yMZACAhP4zQzM9t45ZNAfKfoUZiZmVmjks+VKP/REIGYmZlZ45HPGAgzMzOzdTiBMDMzs4IVLYGQtK2kuyS9JmmqpEck7SKpi6TZdazzNEnfqO9YK+2jj6Rr0/JBkvbPeW2UpBPyqOMWSe9WPk5JHSRNkDQ//du+mu3PkfSqpJC0ZU65JF2bXpspqVfOa6emeudLarC7pVZ3TiR9Q9J9DRWHmZk1rGoTCEnLJH1SxWOZpE9qqlSSgAeAiRHxzYjoDfwS2GY94z0NKCiBkJTPQNG1ImJKRJybnh4E7F/D6tUZRdWDT4cAj0XEzmRX9hxSzfbPAIcBlcefHAnsnB6DgRshS0yAy4F9gH5kVw+tMjlpKBHxdkTUmmyZmVnjVG0CERFtImLzKh5tImLzWuo9GFgZESNy6psREZNyV0otCtfnPB+XfvU3Tb9sZ0uaJemC9Cu3D3CHpOmSWknqLenJ1MLxN0kdUz0TJQ2XNAU4r9I+Z0lql37NL5U0KJXfJunbaf/jJHUBzgYuSPvrn6o4UNKzkl6vrjUiIp4CPqjipYHA6LQ8Gjimmu2nRcSCara/LTKTgXbpmI8AJkTEBxHxITCBKhIYSQsk/T4dzxRJvdJ5e03S2WmdzSQ9JunFdK4G5mw/KLV8zJB0e07VXzsnuS1N6X0eI2l8aiH5Q06dh0v6v7S/eyVtlsqHSZqb9ndNVefJzMxKJ+9f55K2BlpWPI+IN2tYfQ9g6nrE1RPoFBF7pH23i4iPJJ0DXBQRUyQ1B64DBkbEe5JOBq4Ezkh1tIiIPlXU/QzwLbJf968D/YHbgP2AfwH6puNbIGkEsDwirklxnAl0BA4gu7z3Q0AhzfTbRMTitPwOhbfIdALeynm+MJVVV16VNyOip6T/JGsp+RbZ+zobGAF8ARwbEZ+k7pPJkh4Cdgd+BewfEe+nVo8K+ZyTnsDeZNcSeVnSdcDnqc7DIuJTSZcAF0q6ATgW2C0iQlK7Ws+MmZk1qFoTCEkDgD+SdR28C+wAzAO6FzGu14Ed05fMw8CjVayzK1miMiHrMaEpsDjn9burqXsScCBZAnEjMFhSJ+DD9CVWW2wPRsQaYK6kOnfJpC/GqOv266HizqqzgM0iYhmwTNKK9EX9KfDvkg4ku/dJJ7JE5xDg3oh4HyAicltY8jknj0XExwCS5pJ9jtqRJSbPpPPeAvg/4GOyRGakpHHAuKoqlDSYrCuHTm2b80Cbqws8FVZq2182q9QhmFkd5TOI8rdkV6N8JSK6AocCk2vZZg7QO4+6V1WKoSVAaobfC5hI1o3w5yq2FTAnInqmx54RcXjO659Ws8+nyFod+qf63wNOIEss8rEiZ7nWbKOSJTndLB3JEjJSN8J0ZXc9rckiYLuc551TWXXlVamIfw3rHssasoTyFGAroHdE9ASWkNPyVEudUP05yV1nddqXyLpeKt7D3SPizIhYRTaW4z7gKGB8VRVGxE0R0Sci+nRo3bSWEM3MrD7lk0CsjIilQBNJTSLiCbKxCDV5HNgk/UIEQFKPnHEEFRYAPSU1kbQd2ZcGqem8SUTcT9bEXTHbYBnQJi2/DGwlab+0TXNJtbaKRMRbwJbAzhHxOvA0cBFZYlFZ7v7qw0NAxQyJU4GxKaYj0hfoWXlsPyiN39gX+Dh1ifwNOFxSe2WDJw9PZXXRFng3IlZKOpispQCy9/RESVvA2oGb62sy8C1JO6U6WyubqbMZ0DYiHgEuIEsmzcysjOSTQHyU/qA/RTaA8U9U/+seyJrnyfqwD0sD9OYAvyfr98/1DPAGMBe4FngxlXcCJkqaDvyFbAYHZH32I1J5U7KWg6skzQCmk/+MieeAV9LypLS/p6tY76/AsZUGUdZK0p1kTfG7SlqYxk4ADAO+LWk+2SyLYdVsf66khWQtCTNzWiYeIeveeRW4GfgprO1O+C3wQnpcUamLoRB3AH0kzQIGAS+lfcwhG2PyZDrf/1HH+teKiPfIZtbcKWkm2TnbjSxpG5fKngYuXN99mZlZ/VL2XV/DClJrssFuTciat9sCd6RWCbOy0KNTqxj3k51KHYYVyGMgzEpL0tRqJhzUKp9ZGFsDiyPiC2C0pFZkg+qcQJiZmW2k8unCuJdsgF2F1anMzMzMNlL5JBDNIuLLiidpuUXxQjIzM7Nyl08C8V66FgQA6cqE7xcvJDMzMyt3+YyBOJts9sUN6flbwI+KF5KZmZmVu1oTiIh4Ddi34h4FEbG86FGZmZlZWau1C0NSW0n/QXbVxomS/iipbdEjMzMzs7KVTxfGLWQ3WjopPf8RcCtwXLGCMjMzK5aVK1eycOFCvvjii1KH0mBatmxJ586dad68eb3VmU8C8c2IOD7n+W/SlSDNzMwanYULF9KmTRu6dOlCHjdQbPQigqVLl7Jw4UK6du1ab/XmMwvjc0kHVDyR9C2yK1OamZk1Ol988QVbbLHFRpE8AEhiiy22qPcWl3xnYdyWM+7hQ766IZSZmVmjs7EkDxWKcbz5zMKYAewlafP0/BNJ5wMz6z0aMzMzaxTyaYEAssQh5+mFwPB6j8asjlp07M72l00pdRhmthGKCPr378+ll17KkUceCcC9997LyJEjGT9+fImjK568E4hKNq62HzMzs2pIYsSIEZx44okcfPDBrFq1in/7t3+rc/KwatUqmjWr69dzw8lnEGVVar4HuJmZ2UZkjz324Oijj+aqq67iiiuu4Ic//CFXXnkl/fr1Y++992bs2LEALFiwgP79+9OrVy969erFs88+C8DEiRPp378/AwYMYPfddy/loeSt2hRH0jKqThQEtCpaRGZmZo3Q5ZdfTq9evWjRogVHHXUUhxxyCLfccgsfffQR/fr147DDDmPrrbdmwoQJtGzZkvnz5/P973+fKVOy7tcXX3yR2bNn1+tUy2KqNoGIiDYNGYiZmVlj1rp1a04++WQ222wz7rnnHv76179yzTXXANnU0TfffJNvfOMbnHPOOUyfPp2mTZvyyiuvrN2+X79+jSZ5gLqPgTAzM7NKmjRpQpMmTYgI7r//fnbdddd1Xh86dCjbbLMNM2bMYM2aNbRs2XLta61bt27ocNdLXcdAmJmZWTWOOOIIrrvuOiKykQDTpk0D4OOPP6Zjx440adKE22+/ndWrV5cyzPXiBMLMzKye/frXv2blypX06NGD7t278+tf/xqAn/70p4wePZq99tqLl156qdG1OuRSRXZk1pj16dMnKgYimZnVZN68eXTr1q3UYTS4qo5b0tSI6FOX+jwGwjYI8xYupffFt5U6jEZr6tWDSh2CmTUy7sIwMzOzgjmBMDMzs4I5gTAzM7OCOYEwMzOzgjmBMDMzs4J5FoaZmW3U6nsGVz6zmt566y0GDRrEkiVLkMTgwYM577zz+OCDDzj55JNZsGABXbp04Z577qF9+/a89NJLnH766bz44otceeWVXHTRRWvr+tOf/sTNN99MRPDjH/+Y888/v16PpzpugTAzM2tgzZo1449//CNz585l8uTJ3HDDDcydO5dhw4Zx6KGHMn/+fA499FCGDRsGQIcOHbj22mvXSRwAZs+ezc0338zzzz/PjBkzGDduHK+++mqDHIMTCDMzswbWsWNHevXqBUCbNm3o1q0bixYtYuzYsZx66qkAnHrqqTz44IMAbL311vTt25fmzZuvU8+8efPYZ5992HTTTWnWrBn/9E//xJgxYxrkGJxAmJmZldCCBQuYNm0a++yzD0uWLKFjx44AbLvttixZsqTGbffYYw8mTZrE0qVL+eyzz3jkkUd46623GiJsj4EwMzMrleXLl3P88cczfPhwNt9883Vek4SkGrfv1q0bl1xyCYcffjitW7emZ8+eNG3atJghr+UWCDMzsxJYuXIlxx9/PKeccgrHHXccANtssw2LFy8GYPHixWy99da11nPmmWcydepUnnrqKdq3b88uu+xS1LgrOIEwMzNrYBHBmWeeSbdu3bjwwgvXlg8YMIDRo0cDMHr0aAYOHFhrXe+++y4Ab775JmPGjOEHP/hBcYKuxF0YZma2USvFzeSeeeYZbr/9dvbcc0969uwJwL//+78zZMgQTjrpJEaOHMkOO+zAPffcA8A777xDnz59+OSTT2jSpAnDhw9n7ty5bL755hx//PEsXbqU5s2bc8MNN9CuXbsGOYaSJRCStgWGA32Bj4AlwPnAl8C4iNijDnWeBjwaEW/XV5xV7KMPMCgizpV0EPBlRDybXhtFFvt9tdRxC3AU8G7ucUrqANwNdAEWACdFxIfKOsH+BHwX+Aw4LSJerN8jqxtJQ4HlEXFNFa89GxH7N3xUZmbl7YADDiAiqnztscce+1rZtttuy8KFC6tcf9KkSfUaW75K0oWRvhAfACZGxDcjojfwS2Cb9az6NOAbBcZSUBIVEVMi4tz09CCgLl+Qo4DvVFE+BHgsInYGHkvPAY4Edk6PwcCNlTeUdFr6Mi8bTh7MzDZcpRoDcTCwMiJGVBRExIyIWCeNSl+K1+c8HyfpIElNJY2SNFvSLEkXSDoB6APcIWm6pFaSekt6UtJUSX+T1DHVM1HScElTgPMq7XOWpHbKLJU0KJXfJunbaf/jJHUBzgYuSPvrn6o4UNKzkl5PMX1NRDwFfFDFSwOB0Wl5NHBMTvltkZkMtKs4lkKk4/5PSVMkzZPUV9IYSfMl/S5nvQfTOZsjaXBO+XckvShphqTcFHn3VPfrks7NWX95+veg9Pp9kl6SdEdKIqnhPTpX0lxJMyXdVeixmplZcZWqC2MPYOp6bN8T6FTR/C+pXUR8JOkc4KKImCKpOXAdMDAi3pN0MnAlcEaqo0VE9Kmi7meAbwH/AF4H+gO3AfsB/0LW5UJELJA0gpzme0lnAh2BA4DdgIeAGrszKtkmIhan5Xf4qkWmE5A7sXdhKltM4b6MiD6SzgPGAr3JkpnXJP1nRCwFzoiIDyS1Al6QdD9ZsnkzcGBEvJG6WyrsRpYUtgFelnRjRKystN+9ge7A26RzLOk5qn+PhgBdI2KFpHZVHUhKbgYDdGrbnAfaXF2H09Hwtr9sVqlDMDNbb411EOXrwI6SrgMeBh6tYp1dyRKVCenHblPW/cK9u5q6JwEHkiUQNwKDJXUCPoyIT2ubkws8GBFrgLmS6twlExEhqeoOskTSFmRdHQAdgBaSjknPfxQRVX1TPZT+nQXMqUhYJL0ObAcsBc6VdGxabzuyrpOtgKci4o0UX24LysMRsQJYIeldssSncmfd8xGxMO1rOtk4j4+o/j2aSdaa9CDwYFXHHxE3ATcB9OjUqsZzZWZm9atUCcQcoMrm/UpWsW43S0uANLBwL+AIsm6Ek/iqZaGCyL4g96um7k+rKX8K+BmwPXApcGyKNd9RKisqxVCIJZI6RsTi1JT/bipfRPZFXqEzsCi1FvSEtQNIu0TE0DzjW1Mp1jVAszQw9DBgv4j4TNJE0nnPo06A1VT9uapqnZreo38mS+SOBi6VtGdErKolDjMzayClGgPxOLBJpf71HjnjCCosAHpKaiJpO6BfWndLoElE3A/8CuiV1l9G1owO8DKwlaT90jbNJXWvLbCIeAvYEtg5Il4HngYuIkssKsvdX314CDg1LZ9K1sVQUT4ojcvYF/g4p6ujvrUla235TNJuwL6pfDLZ+I6usHbGyPqq8j2S1ATYLiKeAC5JMW1WD/szM7N6UpIWiNQ8fywwXNIlwBdkycL5lVZ9BngDmAvMAyqmLnYCbk1fNJDN4IBsdsMISZ+TjVk4AbhWUluyYx1O1vpRm+fImtMha3n4PVkiUdlfgfskDQR+nke9AEi6k2wGx5aSFgKXR8RIYBhwTxpL8Q+ylhWAR8imcL5KNo3z9Hz3VQfjgbMlzSP7gp8MkMYoDAbGpPP+LvDt9dlRRHyZBppWfo9eAf6SygRcGxEfrc++zMyq8+YVe9ZrffmMcyr0dt533HEHV111FRFBmzZtuPHGG9lrr70AGD9+POeddx6rV6/mrLPOYsiQIbXsvX6ounmoZo1Jj06tYtxPdip1GHnxIEqz0po3bx7dunVb+7wUCcTixYtZvHgxvXr1YtmyZfTu3ZsHH3yQUaNG0aFDB4YMGcKwYcP48MMPueqqq3j22Wfp1q0b7du353//938ZOnQozz33HKtXr2aXXXZhwoQJdO7cmb59+3LnnXey++6713rcAJKmVjOhoFa+lLWZmVkDK/R23vvvvz/t27cHYN999117Uannn3+enXbaiR133JEWLVrwve99j7Fjx359h0XgBMLMzKyECr2d98iRIznyyCMBWLRoEdtt99UY+86dO7No0aIGibuxTuM0MzNr9Aq9nfcTTzzByJEjefrpqoblNSy3QJiZmZVAobfznjlzJmeddRZjx45liy22AKBTp0689dZX1xlcuHAhnTp1apD4nUCYmZk1sEJv5/3mm29y3HHHcfvtt7PLLrusXb9v377Mnz+fN954gy+//JK77rqLAQMGNMgxuAvDzMw2aqWYGVXo7byvuOIKli5dyk9/+lMAmjVrxpQpU2jWrBnXX389RxxxBKtXr+aMM86ge/daL3lULzyN0zYInsZpZvmqajrjxsDTOM3MzKzknECYmZlZwZxAmJnZRmdj674vxvE6gTAzs41Ky5YtWbp06UaTREQES5cupWXL2m6sXBjPwrANQouO3dn+simlDsPMGoHOnTuzcOFC3nvvvVKH0mBatmxJ586d67VOJxBmZrZRad68OV27di11GI2euzDMzMysYE4gzMzMrGBOIMzMzKxgvhKlbRAkLQNeLnUctdgSeL/UQeTBcdavxhBnY4gRHGd92xJoHRFb1WVjD6K0DcXLdb0ca0ORNKXcYwTHWd8aQ5yNIUZwnPUtxdmlrtu7C8PMzMwK5gTCzMzMCuYEwjYUN5U6gDw0hhjBcda3xhBnY4gRHGd9W684PYjSzMzMCuYWCDMzMyuYEwgzMzMrmBMIa9QkfUfSy5JelTSk1PFUkLSdpCckzZU0R9J5qXyopEWSpqfHd8sg1gWSZqV4pqSyDpImSJqf/m1fwvh2zTlf0yV9Iun8cjiXkm6R9K6k2TllVZ47Za5Nn9WZknqVOM6rJb2UYnlAUrtU3kXS5znndUSJ46z2fZb0y3Q+X5Z0RAljvDsnvgWSpqfyUp7L6v4G1d/nMyL88KNRPoCmwGvAjkALYAawe6njSrF1BHql5TbAK8DuwFDgolLHVynWBcCWlcr+AAxJy0OAq0odZ857/g6wQzmcS+BAoBcwu7ZzB3wX+F9AwL7AcyWO83CgWVq+KifOLrnrlcH5rPJ9Tv+fZgCbAF3T34KmpYix0ut/BC4rg3NZ3d+gevt8ugXCGrN+wKsR8XpEfAncBQwscUwARMTiiHgxLS8D5gGdShtVQQYCo9PyaOCY0oWyjkOB1yLiH6UOBCAingI+qFRc3bkbCNwWmclAO0kdSxVnRDwaEavS08lA/d7ruQ6qOZ/VGQjcFRErIuIN4FWyvwlFVVOMkgScBNxZ7DhqU8PfoHr7fDqBsMasE/BWzvOFlOGXtKQuwN7Ac6nonNREeEspuwZyBPCopKmSBqeybSJicVp+B9imNKF9zfdY949zuZ1LqP7clfPn9QyyX58VukqaJulJSf1LFVSOqt7ncjyf/YElETE/p6zk57LS36B6+3w6gTArIkmbAfcD50fEJ8CNwDeBnsBisubOUjsgInoBRwI/k3Rg7ouRtW+WfL63pBbAAODeVFSO53Id5XLuaiLpUmAVcEcqWgxsHxF7AxcC/yNp81LFRyN4n3N8n3UT3JKfyyr+Bq21vp9PJxDWmC0Ctst53jmVlQVJzcn+494REWMAImJJRKyOiDXAzTRAk2ttImJR+vdd4AGymJZUNF+mf98tXYRrHQm8GBFLoDzPZVLduSu7z6uk04CjgFPSlwmpS2BpWp5KNrZgl1LFWMP7XFbnU1Iz4Djg7oqyUp/Lqv4GUY+fTycQ1pi9AOwsqWv6dfo94KESxwSs7QsdCcyLiP/IKc/tUzwWmF1524YkqbWkNhXLZAPrZpOdx1PTaqcCY0sT4TrW+XVXbucyR3Xn7iFgUBrtvi/wcU5TcoOT9B3gF8CAiPgsp3wrSU3T8o7AzsDrpYmyxvf5IeB7kjaR1JUszucbOr4chwEvRcTCioJSnsvq/gZRn5/PUowO9cOP+nqQjRx+hSyzv7TU8eTEdQBZ0+BMYHp6fBe4HZiVyh8COpY4zh3JRrLPAOZUnENgC+AxYD7wd6BDieNsDSwF2uaUlfxckiU0i4GVZH3GZ1Z37shGt9+QPquzgD4ljvNVsj7vis/niLTu8emzMB14ETi6xHFW+z4Dl6bz+TJwZKliTOWjgLMrrVvKc1nd36B6+3z6UtZmZmZWMHdhmJmZWcGcQJiZmVnBnECYmZlZwZxAmJmZWcGcQJiZmVnBnECYmZUJZXcZ3bTUcZjlw9M4zczKhKQFZPPv3y91LGa1cQuEmVkBJA1KN3aaIel2SV0kPZ7KHpO0fVpvlKQTcrZbnv49SNJESfdJeknSHenqf+cC3wCekPREaY7OLH/NSh2AmVljIak78Ctg/4h4X1IHslsij46I0ZLOAK6l9tuf7w10B94GngG+FRHXSroQONgtENYYuAXCzCx/hwD3VnzBR8QHwH7A/6TXbye7hHBtno+IhZHdIGo60KX+QzUrLicQZmbFsYr0N1ZSE6BFzmsrcpZX49Zga4ScQJiZ5e9x4ERJWwCkLoxnye4EC3AKMCktLwB6p+UBQPM86l8GtKmvYM2KyVmvmVmeImKOpCuBJyWtBqYBPwdulXQx8B5welr9ZmCspBnAeODTPHZxEzBe0tsRcXD9H4FZ/fE0TjMzMyuYuzDMzMysYE4gzMzMrGBOIMzMzKxgTiDMzMysYE4gzMzMrGBOIMzMzKxgTiDMzMysYP8PbZviZluLF84AAAAASUVORK5CYII=\n", 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", 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" ] }, "metadata": { "needs_background": "light" - }, - "output_type": "display_data" + } } ], - "source": [ - "order = [\n", - " 'Personal laptop',\n", - " 'Large workstation',\n", - " 'Cluster of 2-10 machines',\n", - " 'Cluster with 10-100 machines',\n", - " 'Cluster with 100+ machines'\n", - "]\n", - "d = df['Local machine or Cluster?'].str.split(\";\").explode().reset_index()\n", - "sns.countplot(y=\"Local machine or Cluster?\", data=d, hue=\"Year\", order=order);" - ] + "metadata": {} }, { "cell_type": "markdown", - "metadata": {}, "source": [ "Just like last year, most repondents thought that more documentation and examples would be the most valuable improvements to the project.\n", "\n", "One interesting change comes from looking at \"Which would help you most right now?\" split by API group (`dask.dataframe`, `dask.array`, etc.). Last year showed that \"More examples\" in my field was the most important for all API groups (first table below). But in 2020 there are some differences (second plot below)." - ] + ], + "metadata": {} }, { "cell_type": "code", "execution_count": 9, - "metadata": {}, + "source": [ + "help_by_api = (\n", + " pd.merge(\n", + " df.loc[2019, 'Dask APIs'].str.split(';').explode(),\n", + " df.loc[2019, 'Which would help you most right now?'],\n", + " left_index=True, right_index=True)\n", + " .groupby('Which would help you most right now?')['Dask APIs'].value_counts()\n", + " .unstack(fill_value=0).T\n", + " .loc[['Array', 'Bag', 'DataFrame', 'Delayed', 'Futures', 'ML', 'Xarray']]\n", + " \n", + ")\n", + "(\n", + " help_by_api\n", + " .style\n", + " .background_gradient(axis=\"columns\")\n", + " .set_caption(\"2019 normalized by row. Darker means that a higher proporiton of \"\n", + " \"users of that API prefer that priority.\")\n", + ")" + ], "outputs": [ { + "output_type": "execute_result", "data": { "text/html": [ "