https://mybinder.org/v2/gist/tonyfast/de50b4c52660cc1b7ef283083ac07c0f/master

Modern-pandas-0001.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Modern 🐼🐼🐼🐼🐼🐼.0001\n",
    "\n",
    "> In two ways, our abstractions tend to be richer and more complex than those in the mathematical and physical sciences. First, our abstractions do not necessarily enjoy the clean, elegant or easily definable algebraic properties of mathematical abstractions, such as real numbers or sets, of the physical world. For example, a stack of elements is a common abstract data type used in computing. __*We would not think ‘to add’ two stacks as we would two integers.*__\n",
    ">> [Computational Thinking and Thinking about Computing](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2696102/)\n",
    "\n",
    "* Use `🐼.read_*` methods to load data.\n",
    "    * less __import__s == less 👉🎹🎹🎹🎹🎹👈\n",
    "* With `🐼.dtypes` of `list, dict, and object`, use `🐼.Series.apply(🐼.Series)` to expand `🐼.Series` to `🐼.DataFrame`.  \n",
    "    * Rely on existing indices to avoid intermediate naming.\n",
    "* Use `🐼.stack and pandas.unstack` to swap levels.\n",
    "    * Don't be 🙀 of `🐼.MultiIndex`, they are your friend.  For tidy data, independent variables on the index and dependent variables on the columns."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [],
   "source": [
    "    try: import quansight\n",
    "    except: ...\n",
    "    import pandas; from toolz.curried import *"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> When playing with new approaches, try to use data you understand.  \n",
    "> > _For example, you know what you've done on Github, or you are familiar with data you frequently use._"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [],
   "source": [
    "    USERNAME = 'tonyfast' # Change users to see your own gists, or try looking at your `\"/repos\"`\n",
    "\n",
    "    df = pandas.read_json(F\"https://api.github.com/users/{USERNAME}/gists\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Some values are `object`s."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [],
   "source": [
    "    assert df.dtypes.files == 'object'\n",
    "    assert df.files.apply(flip(isinstance)(dict)).all()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "These easiest way to expand the values is the pattern below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "28  bgcolor-of-markdown.ipynb    {'filename': 'bgcolor-of-markdown.ipynb', 'typ...\n",
       "25  test_ado.ipynb               {'filename': 'test_ado.ipynb', 'type': 'text/p...\n",
       "    requirements.txt             {'filename': 'requirements.txt', 'type': 'text...\n",
       "5   unembed.ipynb                {'filename': 'unembed.ipynb', 'type': 'text/pl...\n",
       "22  dynamic_map.ipynb            {'filename': 'dynamic_map.ipynb', 'type': 'tex...\n",
       "11  gistfile1.txt                {'filename': 'gistfile1.txt', 'type': 'text/pl...\n",
       "dtype: object"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "    assert isinstance(df.files.apply(pandas.Series), pandas.DataFrame)\n",
    "    df.files.apply(pandas.Series).stack().sample(6)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
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       "                                                               filename  \\\n",
       "0  requirements.txt                                    requirements.txt   \n",
       "   sophie-r-demo-rdflib-sugar.ipynb    sophie-r-demo-rdflib-sugar.ipynb   \n",
       "1  requirements.txt                                    requirements.txt   \n",
       "   chris-ml-study-hall.ipynb                  chris-ml-study-hall.ipynb   \n",
       "2  requirements.txt                                    requirements.txt   \n",
       "   schemaorg-pydantic.ipynb                    schemaorg-pydantic.ipynb   \n",
       "3  requirements.txt                                    requirements.txt   \n",
       "   functors.ipynb                                        functors.ipynb   \n",
       "   index.ipynb                                              index.ipynb   \n",
       "   rdflib_patch.ipynb                                rdflib_patch.ipynb   \n",
       "   readme.ipynb                                            readme.ipynb   \n",
       "   schema.ipynb                                            schema.ipynb   \n",
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       "8  schema_frame.ipynb                                schema_frame.ipynb   \n",
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       "10 contents_model_schema.ipynb              contents_model_schema.ipynb   \n",
       "11 gistfile1.txt                                          gistfile1.txt   \n",
       "12 drop-in-semantic-enrichment.ipynb  drop-in-semantic-enrichment.ipynb   \n",
       "13 pod-schema-context.ipynb                    pod-schema-context.ipynb   \n",
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       "   jsonschema-types.ipynb                        jsonschema-types.ipynb   \n",
       "15 environment.yml                                      environment.yml   \n",
       "   postBuild                                                  postBuild   \n",
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       "16 visits_gallery.ipynb                            visits_gallery.ipynb   \n",
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       "18 .md                                                              .md   \n",
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       "22 dynamic_map.ipynb                                  dynamic_map.ipynb   \n",
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       "24 research_data.ipynb                              research_data.ipynb   \n",
       "25 requirements.txt                                    requirements.txt   \n",
       "   environment.yml                                      environment.yml   \n",
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       "\n",
       "                                                      type          language  \\\n",
       "0  requirements.txt                             text/plain              Text   \n",
       "   sophie-r-demo-rdflib-sugar.ipynb             text/plain  Jupyter Notebook   \n",
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       "   chris-ml-study-hall.ipynb                    text/plain  Jupyter Notebook   \n",
       "2  requirements.txt                             text/plain              Text   \n",
       "   schemaorg-pydantic.ipynb                     text/plain  Jupyter Notebook   \n",
       "3  requirements.txt                             text/plain              Text   \n",
       "   functors.ipynb                               text/plain  Jupyter Notebook   \n",
       "   index.ipynb                                  text/plain  Jupyter Notebook   \n",
       "   rdflib_patch.ipynb                           text/plain  Jupyter Notebook   \n",
       "   readme.ipynb                                 text/plain  Jupyter Notebook   \n",
       "   schema.ipynb                                 text/plain  Jupyter Notebook   \n",
       "   webtypes.ipynb                               text/plain  Jupyter Notebook   \n",
       "   wypes.ipynb                                  text/plain  Jupyter Notebook   \n",
       "4  x.py                               application/x-python            Python   \n",
       "5  requirements.txt                             text/plain              Text   \n",
       "   unembed.ipynb                                text/plain  Jupyter Notebook   \n",
       "6  requirements.txt                             text/plain              Text   \n",
       "   rdf_type_system.ipynb                        text/plain  Jupyter Notebook   \n",
       "7  requirements.txt                             text/plain              Text   \n",
       "   tidy_rdf.csv                                   text/csv               CSV   \n",
       "   tidy_rdf.ipynb                               text/plain  Jupyter Notebook   \n",
       "8  schema_frame.ipynb                           text/plain  Jupyter Notebook   \n",
       "9  shema_org_python_types.ipynb                 text/plain  Jupyter Notebook   \n",
       "10 contents_model_schema.ipynb                  text/plain  Jupyter Notebook   \n",
       "11 gistfile1.txt                                text/plain              Text   \n",
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       "   jsonschema-types.ipynb                       text/plain  Jupyter Notebook   \n",
       "15 environment.yml                             text/x-yaml              YAML   \n",
       "   postBuild                                    text/plain              None   \n",
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       "16 visits_gallery.ipynb                         text/plain  Jupyter Notebook   \n",
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       "19 clocky.ipynb                                 text/plain  Jupyter Notebook   \n",
       "20 requirements.txt                             text/plain              Text   \n",
       "   all_the_schemas.ipynb                        text/plain  Jupyter Notebook   \n",
       "21 local_context.ipynb                          text/plain  Jupyter Notebook   \n",
       "22 dynamic_map.ipynb                            text/plain  Jupyter Notebook   \n",
       "23 awidgetable.ipynb                            text/plain  Jupyter Notebook   \n",
       "24 research_data.ipynb                          text/plain  Jupyter Notebook   \n",
       "25 requirements.txt                             text/plain              Text   \n",
       "   environment.yml                             text/x-yaml              YAML   \n",
       "   ado.ipynb                                    text/plain  Jupyter Notebook   \n",
       "   test_ado.ipynb                               text/plain  Jupyter Notebook   \n",
       "26 hacking-odo-for-2019.ipynb                   text/plain  Jupyter Notebook   \n",
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       "\n",
       "                                                                                raw_url  \\\n",
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       "   sophie-r-demo-rdflib-sugar.ipynb   https://gist.githubusercontent.com/tonyfast/5a...   \n",
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       "   chris-ml-study-hall.ipynb          https://gist.githubusercontent.com/tonyfast/60...   \n",
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       "   schemaorg-pydantic.ipynb           https://gist.githubusercontent.com/tonyfast/61...   \n",
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       "   functors.ipynb                     https://gist.githubusercontent.com/tonyfast/03...   \n",
       "   index.ipynb                        https://gist.githubusercontent.com/tonyfast/03...   \n",
       "   rdflib_patch.ipynb                 https://gist.githubusercontent.com/tonyfast/03...   \n",
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       "   schema.ipynb                       https://gist.githubusercontent.com/tonyfast/03...   \n",
       "   webtypes.ipynb                     https://gist.githubusercontent.com/tonyfast/03...   \n",
       "   wypes.ipynb                        https://gist.githubusercontent.com/tonyfast/03...   \n",
       "4  x.py                               https://gist.githubusercontent.com/tonyfast/8c...   \n",
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       "   unembed.ipynb                      https://gist.githubusercontent.com/tonyfast/0b...   \n",
       "6  requirements.txt                   https://gist.githubusercontent.com/tonyfast/14...   \n",
       "   rdf_type_system.ipynb              https://gist.githubusercontent.com/tonyfast/14...   \n",
       "7  requirements.txt                   https://gist.githubusercontent.com/tonyfast/98...   \n",
       "   tidy_rdf.csv                       https://gist.githubusercontent.com/tonyfast/98...   \n",
       "   tidy_rdf.ipynb                     https://gist.githubusercontent.com/tonyfast/98...   \n",
       "8  schema_frame.ipynb                 https://gist.githubusercontent.com/tonyfast/0a...   \n",
       "9  shema_org_python_types.ipynb       https://gist.githubusercontent.com/tonyfast/8e...   \n",
       "10 contents_model_schema.ipynb        https://gist.githubusercontent.com/tonyfast/ac...   \n",
       "11 gistfile1.txt                      https://gist.githubusercontent.com/tonyfast/03...   \n",
       "12 drop-in-semantic-enrichment.ipynb  https://gist.githubusercontent.com/tonyfast/fe...   \n",
       "13 pod-schema-context.ipynb           https://gist.githubusercontent.com/tonyfast/0c...   \n",
       "14 requirements.txt                   https://gist.githubusercontent.com/tonyfast/dc...   \n",
       "   drop-in-semantic-enrichment.ipynb  https://gist.githubusercontent.com/tonyfast/dc...   \n",
       "   jsonschema-types.ipynb             https://gist.githubusercontent.com/tonyfast/dc...   \n",
       "15 environment.yml                    https://gist.githubusercontent.com/tonyfast/b9...   \n",
       "   postBuild                          https://gist.githubusercontent.com/tonyfast/b9...   \n",
       "   visits_gallery.ipynb               https://gist.githubusercontent.com/tonyfast/b9...   \n",
       "16 visits_gallery.ipynb               https://gist.githubusercontent.com/tonyfast/e2...   \n",
       "17 one_cannot_redirect_os_sys.ipynb   https://gist.githubusercontent.com/tonyfast/38...   \n",
       "18 .md                                https://gist.githubusercontent.com/tonyfast/75...   \n",
       "   2019-08-05-Untitled.ipynb          https://gist.githubusercontent.com/tonyfast/75...   \n",
       "19 clocky.ipynb                       https://gist.githubusercontent.com/tonyfast/99...   \n",
       "20 requirements.txt                   https://gist.githubusercontent.com/tonyfast/c1...   \n",
       "   all_the_schemas.ipynb              https://gist.githubusercontent.com/tonyfast/c1...   \n",
       "21 local_context.ipynb                https://gist.githubusercontent.com/tonyfast/3b...   \n",
       "22 dynamic_map.ipynb                  https://gist.githubusercontent.com/tonyfast/d0...   \n",
       "23 awidgetable.ipynb                  https://gist.githubusercontent.com/tonyfast/a9...   \n",
       "24 research_data.ipynb                https://gist.githubusercontent.com/tonyfast/bc...   \n",
       "25 requirements.txt                   https://gist.githubusercontent.com/tonyfast/c0...   \n",
       "   environment.yml                    https://gist.githubusercontent.com/tonyfast/c0...   \n",
       "   ado.ipynb                          https://gist.githubusercontent.com/tonyfast/c0...   \n",
       "   test_ado.ipynb                     https://gist.githubusercontent.com/tonyfast/c0...   \n",
       "26 hacking-odo-for-2019.ipynb         https://gist.githubusercontent.com/tonyfast/87...   \n",
       "27 load-files-dask-graph.ipynb        https://gist.githubusercontent.com/tonyfast/ed...   \n",
       "28 bgcolor-of-markdown.ipynb          https://gist.githubusercontent.com/tonyfast/98...   \n",
       "29 notebook-graph.ipynb               https://gist.githubusercontent.com/tonyfast/4e...   \n",
       "\n",
       "                                         size  \n",
       "0  requirements.txt                       152  \n",
       "   sophie-r-demo-rdflib-sugar.ipynb     25568  \n",
       "1  requirements.txt                        39  \n",
       "   chris-ml-study-hall.ipynb            65107  \n",
       "2  requirements.txt                        43  \n",
       "   schemaorg-pydantic.ipynb             10353  \n",
       "3  requirements.txt                       180  \n",
       "   functors.ipynb                        2062  \n",
       "   index.ipynb                          35025  \n",
       "   rdflib_patch.ipynb                    1948  \n",
       "   readme.ipynb                         20500  \n",
       "   schema.ipynb                          7051  \n",
       "   webtypes.ipynb                        7071  \n",
       "   wypes.ipynb                           8911  \n",
       "4  x.py                                   466  \n",
       "5  requirements.txt                        10  \n",
       "   unembed.ipynb                         4565  \n",
       "6  requirements.txt                        44  \n",
       "   rdf_type_system.ipynb                 3999  \n",
       "7  requirements.txt                        33  \n",
       "   tidy_rdf.csv                        189339  \n",
       "   tidy_rdf.ipynb                        3388  \n",
       "8  schema_frame.ipynb                  118443  \n",
       "9  shema_org_python_types.ipynb        711585  \n",
       "10 contents_model_schema.ipynb          21615  \n",
       "11 gistfile1.txt                          452  \n",
       "12 drop-in-semantic-enrichment.ipynb   150801  \n",
       "13 pod-schema-context.ipynb              4167  \n",
       "14 requirements.txt                        39  \n",
       "   drop-in-semantic-enrichment.ipynb    84491  \n",
       "   jsonschema-types.ipynb                8027  \n",
       "15 environment.yml                        121  \n",
       "   postBuild                              124  \n",
       "   visits_gallery.ipynb                921339  \n",
       "16 visits_gallery.ipynb                112243  \n",
       "17 one_cannot_redirect_os_sys.ipynb      2108  \n",
       "18 .md                                   1110  \n",
       "   2019-08-05-Untitled.ipynb             6488  \n",
       "19 clocky.ipynb                          1932  \n",
       "20 requirements.txt                        47  \n",
       "   all_the_schemas.ipynb               228746  \n",
       "21 local_context.ipynb                 208136  \n",
       "22 dynamic_map.ipynb                   188169  \n",
       "23 awidgetable.ipynb                     4878  \n",
       "24 research_data.ipynb                2395626  \n",
       "25 requirements.txt                       202  \n",
       "   environment.yml                         73  \n",
       "   ado.ipynb                            19479  \n",
       "   test_ado.ipynb                      276323  \n",
       "26 hacking-odo-for-2019.ipynb            9185  \n",
       "27 load-files-dask-graph.ipynb          68404  \n",
       "28 bgcolor-of-markdown.ipynb             1841  \n",
       "29 notebook-graph.ipynb                716760  "
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "    assert isinstance(df.files.apply(pandas.Series), pandas.DataFrame)\n",
    "    df.files.apply(pandas.Series).stack().apply(pandas.Series)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}

requirements.txt

pandas
toolz