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-rw-r--r--.mypy.ini3
-rw-r--r--.pylintrc3
-rw-r--r--Makefile1
-rw-r--r--notebooks/Cluster Size and Title Length.ipynb553
-rw-r--r--notebooks/Journal_Names.html14635
-rw-r--r--notebooks/Journal_Names.ipynb2032
-rw-r--r--notebooks/Journal_Names.pdfbin69255 -> 0 bytes
-rw-r--r--notebooks/Journal_Names.zipbin26734 -> 0 bytes
-rw-r--r--notes/bm.md19
-rw-r--r--notes/clustering.md102
-rw-r--r--notes/general.md197
-rw-r--r--notes/todo.md23
-rw-r--r--notes/workflow.md60
-rw-r--r--pyproject.toml3
-rw-r--r--setup.py50
15 files changed, 1 insertions, 17680 deletions
diff --git a/.mypy.ini b/.mypy.ini
deleted file mode 100644
index ebcf395..0000000
--- a/.mypy.ini
+++ /dev/null
@@ -1,3 +0,0 @@
-[mypy]
-ignore_missing_imports = True
-
diff --git a/.pylintrc b/.pylintrc
deleted file mode 100644
index 72e94cb..0000000
--- a/.pylintrc
+++ /dev/null
@@ -1,3 +0,0 @@
-[MESSAGES CONTROL]
-
-disable=C0301
diff --git a/Makefile b/Makefile
index ff7cb30..752fad3 100644
--- a/Makefile
+++ b/Makefile
@@ -49,6 +49,7 @@ clean: ## Clean all artifacts
rm -rf .pytest_cache/
rm -rf .coverage
rm -rf .mypy_cache/
+ find . -name "__pycache__" -type d -exec rm -rf {} \;
# Upload requires https://github.com/pypa/twine and some configuration.
.PHONY: upload
diff --git a/notebooks/Cluster Size and Title Length.ipynb b/notebooks/Cluster Size and Title Length.ipynb
deleted file mode 100644
index b78ba8b..0000000
--- a/notebooks/Cluster Size and Title Length.ipynb
+++ /dev/null
@@ -1,553 +0,0 @@
-{
- "cells": [
- {
- "cell_type": "code",
- "execution_count": 1,
- "metadata": {},
- "outputs": [],
- "source": [
- "import pandas as pd"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 7,
- "metadata": {},
- "outputs": [],
- "source": [
- "df = pd.read_csv(\"../fixtures/cluster_title_normalized_dups_size_keylen.tsv\", sep=\"\\t\", names=[\"size\", \"len\"])"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 8,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "5818143"
- ]
- },
- "execution_count": 8,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "len(df)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 9,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/html": [
- "<div>\n",
- "<style scoped>\n",
- " .dataframe tbody tr th:only-of-type {\n",
- " vertical-align: middle;\n",
- " }\n",
- "\n",
- " .dataframe tbody tr th {\n",
- " vertical-align: top;\n",
- " }\n",
- "\n",
- " .dataframe thead th {\n",
- " text-align: right;\n",
- " }\n",
- "</style>\n",
- "<table border=\"1\" class=\"dataframe\">\n",
- " <thead>\n",
- " <tr style=\"text-align: right;\">\n",
- " <th></th>\n",
- " <th>size</th>\n",
- " <th>len</th>\n",
- " </tr>\n",
- " </thead>\n",
- " <tbody>\n",
- " <tr>\n",
- " <th>0</th>\n",
- " <td>264</td>\n",
- " <td>0</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>1</th>\n",
- " <td>2</td>\n",
- " <td>3</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>2</th>\n",
- " <td>2</td>\n",
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- " </tr>\n",
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- " <th>3</th>\n",
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- " </tr>\n",
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- " <th>4</th>\n",
- " <td>2</td>\n",
- " <td>4</td>\n",
- " </tr>\n",
- " </tbody>\n",
- "</table>\n",
- "</div>"
- ],
- "text/plain": [
- " size len\n",
- "0 264 0\n",
- "1 2 3\n",
- "2 2 3\n",
- "3 2 3\n",
- "4 2 4"
- ]
- },
- "execution_count": 9,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "df.head()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 21,
- "metadata": {},
- "outputs": [],
- "source": [
- "pd.set_option('display.float_format', lambda x: '%.3f' % x)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 23,
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- " size len\n",
- "count 5818143.000 5818143.000\n",
- "mean 4.350 52.120\n",
- "std 196.347 35.026\n",
- "min 2.000 0.000\n",
- "25% 2.000 24.000\n",
- "50% 2.000 46.000\n",
- "75% 3.000 72.000\n",
- "max 151383.000 11686.000\n"
- ]
- }
- ],
- "source": [
- "print(df.describe())"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 27,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/html": [
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- "<table border=\"1\" class=\"dataframe\">\n",
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- "<p>448170 rows × 2 columns</p>\n",
- "</div>"
- ],
- "text/plain": [
- " size len\n",
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- "284 7 6\n",
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- "... ... ...\n",
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- "execution_count": 27,
- "metadata": {},
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- "source": [
- "df[df[\"size\"] > 4]"
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diff --git a/notebooks/Journal_Names.html b/notebooks/Journal_Names.html
deleted file mode 100644
index a87394a..0000000
--- a/notebooks/Journal_Names.html
+++ /dev/null
@@ -1,14635 +0,0 @@
-<!DOCTYPE html>
-<html>
-<head><meta charset="utf-8" />
-
-<title>Journal_Names</title>
-
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- /*!
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-/*!
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-html {
- font-family: sans-serif;
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- vertical-align: baseline;
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- display: none;
- height: 0;
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-[hidden],
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- display: none;
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- outline: 0;
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-/*!
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-* Font Awesome
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-*/
-/*!
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- * License - http://fontawesome.io/license (Font: SIL OFL 1.1, CSS: MIT License)
- */
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- border: solid 0.08em #eee;
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-.fa-pull-right {
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-.fa.fa-pull-right {
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-.fa.pull-left {
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-.fa.pull-right {
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-.fa-spin {
- -webkit-animation: fa-spin 2s infinite linear;
- animation: fa-spin 2s infinite linear;
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-.fa-pulse {
- -webkit-animation: fa-spin 1s infinite steps(8);
- animation: fa-spin 1s infinite steps(8);
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- }
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-:root .fa-rotate-90,
-:root .fa-rotate-180,
-:root .fa-rotate-270,
-:root .fa-flip-horizontal,
-:root .fa-flip-vertical {
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-.fa-stack-2x {
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-.fa-inverse {
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-.fa-close:before,
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-.fa-rotate-right:before,
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-.fa-photo:before,
-.fa-image:before,
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-.fa-angle-double-up:before {
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-.fa-angle-down:before {
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-.fa-mobile-phone:before,
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-[dir="rtl"] span#login_widget {
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- to make sure that empty JavaScript output_subareas have no height. */
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-<div class="text_cell_render border-box-sizing rendered_html">
-<h1 id="Journal-Names">Journal Names<a class="anchor-link" href="#Journal-Names">&#182;</a></h1><p>Questions in the context of fuzzy matching.</p>
-<ul>
-<li>How many journal names appear more than once?</li>
-<li>What is the average length of the duplicated names vs the unique names?</li>
-</ul>
-<p>Input file is a single larger JSON, mapping names to issns.</p>
-<div class="highlight"><pre><span></span><span class="p">{</span>
- <span class="nt">&quot;Acta Orientalia.&quot;</span><span class="p">:</span> <span class="p">[</span>
- <span class="s2">&quot;0001-6438&quot;</span>
- <span class="p">],</span>
- <span class="nt">&quot;Acta Orientalia (København)&quot;</span><span class="p">:</span> <span class="p">[</span>
- <span class="s2">&quot;0001-6438&quot;</span>
- <span class="p">],</span>
-<span class="err">..</span>
-</pre></div>
-
-</div>
-</div>
-</div>
-<div class="cell border-box-sizing code_cell rendered">
-<div class="input">
-<div class="prompt input_prompt">In&nbsp;[4]:</div>
-<div class="inner_cell">
- <div class="input_area">
-<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">import</span> <span class="nn">json</span>
-<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
-</pre></div>
-
- </div>
-</div>
-</div>
-
-</div>
-<div class="cell border-box-sizing code_cell rendered">
-<div class="input">
-<div class="prompt input_prompt">In&nbsp;[5]:</div>
-<div class="inner_cell">
- <div class="input_area">
-<div class=" highlight hl-ipython3"><pre><span></span><span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="s2">&quot;../data/name_to_issn.json&quot;</span><span class="p">)</span> <span class="k">as</span> <span class="n">f</span><span class="p">:</span>
- <span class="n">mapping</span> <span class="o">=</span> <span class="n">json</span><span class="o">.</span><span class="n">load</span><span class="p">(</span><span class="n">f</span><span class="p">)</span>
-</pre></div>
-
- </div>
-</div>
-</div>
-
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-<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
-</div><div class="inner_cell">
-<div class="text_cell_render border-box-sizing rendered_html">
-<p>We have about 3M keys.</p>
-
-</div>
-</div>
-</div>
-<div class="cell border-box-sizing code_cell rendered">
-<div class="input">
-<div class="prompt input_prompt">In&nbsp;[7]:</div>
-<div class="inner_cell">
- <div class="input_area">
-<div class=" highlight hl-ipython3"><pre><span></span><span class="nb">len</span><span class="p">(</span><span class="n">mapping</span><span class="p">)</span>
-</pre></div>
-
- </div>
-</div>
-</div>
-
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-<div class="output">
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- <div class="prompt output_prompt">Out[7]:</div>
-
-
-
-
-<div class="output_text output_subarea output_execute_result">
-<pre>2929727</pre>
-</div>
-
-</div>
-
-</div>
-</div>
-
-</div>
-<div class="cell border-box-sizing code_cell rendered">
-<div class="input">
-<div class="prompt input_prompt">In&nbsp;[21]:</div>
-<div class="inner_cell">
- <div class="input_area">
-<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(((</span><span class="n">k</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">v</span><span class="p">))</span> <span class="k">for</span> <span class="n">k</span><span class="p">,</span> <span class="n">v</span> <span class="ow">in</span> <span class="n">mapping</span><span class="o">.</span><span class="n">items</span><span class="p">()),</span> <span class="n">columns</span><span class="o">=</span><span class="p">[</span><span class="s2">&quot;name&quot;</span><span class="p">,</span> <span class="s2">&quot;issn_count&quot;</span><span class="p">])</span>
-</pre></div>
-
- </div>
-</div>
-</div>
-
-</div>
-<div class="cell border-box-sizing code_cell rendered">
-<div class="input">
-<div class="prompt input_prompt">In&nbsp;[25]:</div>
-<div class="inner_cell">
- <div class="input_area">
-<div class=" highlight hl-ipython3"><pre><span></span><span class="nb">len</span><span class="p">(</span><span class="n">df</span><span class="p">)</span>
-</pre></div>
-
- </div>
-</div>
-</div>
-
-<div class="output_wrapper">
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-
-
-
-
-<div class="output_text output_subarea output_execute_result">
-<pre>2929727</pre>
-</div>
-
-</div>
-
-</div>
-</div>
-
-</div>
-<div class="cell border-box-sizing code_cell rendered">
-<div class="input">
-<div class="prompt input_prompt">In&nbsp;[26]:</div>
-<div class="inner_cell">
- <div class="input_area">
-<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df</span><span class="o">.</span><span class="n">head</span><span class="p">()</span>
-</pre></div>
-
- </div>
-</div>
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-</style>
-<table border="1" class="dataframe">
- <thead>
- <tr style="text-align: right;">
- <th></th>
- <th>name</th>
- <th>issn_count</th>
- </tr>
- </thead>
- <tbody>
- <tr>
- <th>0</th>
- <td>Acta Orientalia.</td>
- <td>1</td>
- </tr>
- <tr>
- <th>1</th>
- <td>Acta Orientalia (København)</td>
- <td>1</td>
- </tr>
- <tr>
- <th>2</th>
- <td>˜The œpublishers weekly.</td>
- <td>1</td>
- </tr>
- <tr>
- <th>3</th>
- <td>Publishers weekly</td>
- <td>1</td>
- </tr>
- <tr>
- <th>4</th>
- <td>ASMT news</td>
- <td>1</td>
- </tr>
- </tbody>
-</table>
-</div>
-</div>
-
-</div>
-
-</div>
-</div>
-
-</div>
-<div class="cell border-box-sizing code_cell rendered">
-<div class="input">
-<div class="prompt input_prompt">In&nbsp;[31]:</div>
-<div class="inner_cell">
- <div class="input_area">
-<div class=" highlight hl-ipython3"><pre><span></span><span class="n">unique_name</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="n">df</span><span class="o">.</span><span class="n">issn_count</span> <span class="o">==</span> <span class="mi">1</span><span class="p">]</span>
-</pre></div>
-
- </div>
-</div>
-</div>
-
-</div>
-<div class="cell border-box-sizing code_cell rendered">
-<div class="input">
-<div class="prompt input_prompt">In&nbsp;[32]:</div>
-<div class="inner_cell">
- <div class="input_area">
-<div class=" highlight hl-ipython3"><pre><span></span><span class="n">repeated_names</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="n">df</span><span class="o">.</span><span class="n">issn_count</span> <span class="o">&gt;</span> <span class="mi">1</span><span class="p">]</span>
-</pre></div>
-
- </div>
-</div>
-</div>
-
-</div>
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-<div class="input">
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-<div class="inner_cell">
- <div class="input_area">
-<div class=" highlight hl-ipython3"><pre><span></span><span class="nb">len</span><span class="p">(</span><span class="n">repeated_names</span><span class="p">)</span>
-</pre></div>
-
- </div>
-</div>
-</div>
-
-<div class="output_wrapper">
-<div class="output">
-
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- <div class="prompt output_prompt">Out[34]:</div>
-
-
-
-
-<div class="output_text output_subarea output_execute_result">
-<pre>194241</pre>
-</div>
-
-</div>
-
-</div>
-</div>
-
-</div>
-<div class="cell border-box-sizing code_cell rendered">
-<div class="input">
-<div class="prompt input_prompt">In&nbsp;[33]:</div>
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- <div class="input_area">
-<div class=" highlight hl-ipython3"><pre><span></span><span class="nb">len</span><span class="p">(</span><span class="n">repeated_names</span><span class="p">)</span> <span class="o">/</span> <span class="nb">len</span><span class="p">(</span><span class="n">df</span><span class="p">)</span>
-</pre></div>
-
- </div>
-</div>
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-
-
-
-
-<div class="output_text output_subarea output_execute_result">
-<pre>0.06630003409874026</pre>
-</div>
-
-</div>
-
-</div>
-</div>
-
-</div>
-<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
-</div><div class="inner_cell">
-<div class="text_cell_render border-box-sizing rendered_html">
-<p>About 6% (or 194241) names are repeated.</p>
-
-</div>
-</div>
-</div>
-<div class="cell border-box-sizing code_cell rendered">
-<div class="input">
-<div class="prompt input_prompt">In&nbsp;[35]:</div>
-<div class="inner_cell">
- <div class="input_area">
-<div class=" highlight hl-ipython3"><pre><span></span><span class="n">repeated_names</span><span class="o">.</span><span class="n">describe</span><span class="p">()</span>
-</pre></div>
-
- </div>
-</div>
-</div>
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-
-
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-<div class="output_html rendered_html output_subarea output_execute_result">
-<div>
-<style scoped>
- .dataframe tbody tr th:only-of-type {
- vertical-align: middle;
- }
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- .dataframe tbody tr th {
- vertical-align: top;
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- text-align: right;
- }
-</style>
-<table border="1" class="dataframe">
- <thead>
- <tr style="text-align: right;">
- <th></th>
- <th>issn_count</th>
- </tr>
- </thead>
- <tbody>
- <tr>
- <th>count</th>
- <td>194241.000000</td>
- </tr>
- <tr>
- <th>mean</th>
- <td>3.197523</td>
- </tr>
- <tr>
- <th>std</th>
- <td>25.081605</td>
- </tr>
- <tr>
- <th>min</th>
- <td>2.000000</td>
- </tr>
- <tr>
- <th>25%</th>
- <td>2.000000</td>
- </tr>
- <tr>
- <th>50%</th>
- <td>2.000000</td>
- </tr>
- <tr>
- <th>75%</th>
- <td>2.000000</td>
- </tr>
- <tr>
- <th>max</th>
- <td>8980.000000</td>
- </tr>
- </tbody>
-</table>
-</div>
-</div>
-
-</div>
-
-</div>
-</div>
-
-</div>
-<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
-</div><div class="inner_cell">
-<div class="text_cell_render border-box-sizing rendered_html">
-<p>Which name is shared by over 8000 ISSN?</p>
-
-</div>
-</div>
-</div>
-<div class="cell border-box-sizing code_cell rendered">
-<div class="input">
-<div class="prompt input_prompt">In&nbsp;[40]:</div>
-<div class="inner_cell">
- <div class="input_area">
-<div class=" highlight hl-ipython3"><pre><span></span><span class="n">repeated_names</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="n">repeated_names</span><span class="o">.</span><span class="n">issn_count</span><span class="o">.</span><span class="n">argmax</span><span class="p">()]</span> <span class="c1"># Annual report.</span>
-</pre></div>
-
- </div>
-</div>
-</div>
-
-<div class="output_wrapper">
-<div class="output">
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-
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- <div class="prompt output_prompt">Out[40]:</div>
-
-
-
-
-<div class="output_text output_subarea output_execute_result">
-<pre>name Annual report.
-issn_count 8980
-Name: 45907, dtype: object</pre>
-</div>
-
-</div>
-
-</div>
-</div>
-
-</div>
-<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
-</div><div class="inner_cell">
-<div class="text_cell_render border-box-sizing rendered_html">
-<p>It is the "Annual report."</p>
-
-</div>
-</div>
-</div>
-<div class="cell border-box-sizing code_cell rendered">
-<div class="input">
-<div class="prompt input_prompt">In&nbsp;[42]:</div>
-<div class="inner_cell">
- <div class="input_area">
-<div class=" highlight hl-ipython3"><pre><span></span><span class="n">mapping</span><span class="p">[</span><span class="s2">&quot;Annual report.&quot;</span><span class="p">][:</span><span class="mi">10</span><span class="p">]</span>
-</pre></div>
-
- </div>
-</div>
-</div>
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-
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-
-<div class="output_text output_subarea output_execute_result">
-<pre>[&#39;0706-537X&#39;,
- &#39;1186-7957&#39;,
- &#39;2324-1926&#39;,
- &#39;1445-9248&#39;,
- &#39;0872-3982&#39;,
- &#39;1714-1524&#39;,
- &#39;1037-8812&#39;,
- &#39;0225-0241&#39;,
- &#39;1327-6344&#39;,
- &#39;0702-7702&#39;]</pre>
-</div>
-
-</div>
-
-</div>
-</div>
-
-</div>
-<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
-</div><div class="inner_cell">
-<div class="text_cell_render border-box-sizing rendered_html">
-<p>On average a repeated name will point to 3 ISSN. About 24k names point to more than 3 ISSN.</p>
-
-</div>
-</div>
-</div>
-<div class="cell border-box-sizing code_cell rendered">
-<div class="input">
-<div class="prompt input_prompt">In&nbsp;[45]:</div>
-<div class="inner_cell">
- <div class="input_area">
-<div class=" highlight hl-ipython3"><pre><span></span><span class="nb">len</span><span class="p">(</span><span class="n">repeated_names</span><span class="p">[</span><span class="n">repeated_names</span><span class="o">.</span><span class="n">issn_count</span> <span class="o">&gt;</span> <span class="mi">3</span><span class="p">])</span>
-</pre></div>
-
- </div>
-</div>
-</div>
-
-<div class="output_wrapper">
-<div class="output">
-
-
-<div class="output_area">
-
- <div class="prompt output_prompt">Out[45]:</div>
-
-
-
-
-<div class="output_text output_subarea output_execute_result">
-<pre>24107</pre>
-</div>
-
-</div>
-
-</div>
-</div>
-
-</div>
-<div class="cell border-box-sizing code_cell rendered">
-<div class="input">
-<div class="prompt input_prompt">In&nbsp;[49]:</div>
-<div class="inner_cell">
- <div class="input_area">
-<div class=" highlight hl-ipython3"><pre><span></span><span class="n">repeated_names</span><span class="p">[</span><span class="n">repeated_names</span><span class="o">.</span><span class="n">issn_count</span> <span class="o">&gt;</span> <span class="mi">3</span><span class="p">]</span><span class="o">.</span><span class="n">sample</span><span class="p">(</span><span class="n">n</span><span class="o">=</span><span class="mi">10</span><span class="p">)</span>
-</pre></div>
-
- </div>
-</div>
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- <div class="prompt output_prompt">Out[49]:</div>
-
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-
-<div class="output_html rendered_html output_subarea output_execute_result">
-<div>
-<style scoped>
- .dataframe tbody tr th:only-of-type {
- vertical-align: middle;
- }
-
- .dataframe tbody tr th {
- vertical-align: top;
- }
-
- .dataframe thead th {
- text-align: right;
- }
-</style>
-<table border="1" class="dataframe">
- <thead>
- <tr style="text-align: right;">
- <th></th>
- <th>name</th>
- <th>issn_count</th>
- </tr>
- </thead>
- <tbody>
- <tr>
- <th>322100</th>
- <td>Philosophica.</td>
- <td>17</td>
- </tr>
- <tr>
- <th>183928</th>
- <td>Edad de oro.</td>
- <td>4</td>
- </tr>
- <tr>
- <th>294309</th>
- <td>Horoskop.</td>
- <td>10</td>
- </tr>
- <tr>
- <th>517039</th>
- <td>˜Le œGrand journal.</td>
- <td>11</td>
- </tr>
- <tr>
- <th>1664616</th>
- <td>Caleidoscop şcolar.</td>
- <td>4</td>
- </tr>
- <tr>
- <th>258430</th>
- <td>˜La œFeuille.</td>
- <td>34</td>
- </tr>
- <tr>
- <th>309546</th>
- <td>˜The œWilson quarterly.</td>
- <td>4</td>
- </tr>
- <tr>
- <th>795859</th>
- <td>Introductory research essay</td>
- <td>4</td>
- </tr>
- <tr>
- <th>1470838</th>
- <td>Publicaciones del SEMYR.</td>
- <td>4</td>
- </tr>
- <tr>
- <th>657041</th>
- <td>˜Le œKiosque.</td>
- <td>14</td>
- </tr>
- </tbody>
-</table>
-</div>
-</div>
-
-</div>
-
-</div>
-</div>
-
-</div>
-<div class="cell border-box-sizing code_cell rendered">
-<div class="input">
-<div class="prompt input_prompt">In&nbsp;[50]:</div>
-<div class="inner_cell">
- <div class="input_area">
-<div class=" highlight hl-ipython3"><pre><span></span><span class="n">mapping</span><span class="p">[</span><span class="s2">&quot;Philosophica.&quot;</span><span class="p">]</span>
-</pre></div>
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- </div>
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-</div>
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- <div class="prompt output_prompt">Out[50]:</div>
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-<pre>[&#39;1285-9133&#39;,
- &#39;1480-4670&#39;,
- &#39;1487-5349&#39;,
- &#39;1724-6598&#39;,
- &#39;2183-0134&#39;,
- &#39;2538-693X&#39;,
- &#39;2610-8933&#39;,
- &#39;2035-8326&#39;,
- &#39;2295-9084&#39;,
- &#39;1517-8889&#39;,
- &#39;2249-5053&#39;,
- &#39;2420-9198&#39;,
- &#39;2654-9263&#39;,
- &#39;2610-8925&#39;,
- &#39;1158-9574&#39;,
- &#39;0872-4784&#39;,
- &#39;0379-8402&#39;]</pre>
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-<div class="cell border-box-sizing code_cell rendered">
-<div class="input">
-<div class="prompt input_prompt">In&nbsp;[61]:</div>
-<div class="inner_cell">
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-<div class=" highlight hl-ipython3"><pre><span></span><span class="n">repeated_names</span><span class="p">[</span><span class="n">repeated_names</span><span class="o">.</span><span class="n">issn_count</span> <span class="o">&gt;</span> <span class="mi">3</span><span class="p">]</span><span class="o">.</span><span class="n">issn_count</span><span class="o">.</span><span class="n">hist</span><span class="p">(</span><span class="n">bins</span><span class="o">=</span><span class="mi">20</span><span class="p">)</span>
-</pre></div>
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-<pre>&lt;AxesSubplot:&gt;</pre>
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src="data:image/png;base64,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-<div class="cell border-box-sizing code_cell rendered">
-<div class="input">
-<div class="prompt input_prompt">In&nbsp;[60]:</div>
-<div class="inner_cell">
- <div class="input_area">
-<div class=" highlight hl-ipython3"><pre><span></span><span class="n">repeated_names</span><span class="p">[(</span><span class="n">repeated_names</span><span class="o">.</span><span class="n">issn_count</span> <span class="o">&gt;</span> <span class="mi">3</span><span class="p">)</span> <span class="o">&amp;</span> <span class="p">(</span><span class="n">repeated_names</span><span class="o">.</span><span class="n">issn_count</span> <span class="o">&lt;</span> <span class="mi">50</span><span class="p">)]</span><span class="o">.</span><span class="n">issn_count</span><span class="o">.</span><span class="n">hist</span><span class="p">(</span><span class="n">bins</span><span class="o">=</span><span class="mi">10</span><span class="p">)</span>
-</pre></div>
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-<pre>&lt;AxesSubplot:&gt;</pre>
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-<div class=" highlight hl-ipython3"><pre><span></span><span class="n">repeated_names</span><span class="p">[(</span><span class="n">repeated_names</span><span class="o">.</span><span class="n">issn_count</span> <span class="o">&gt;</span> <span class="mi">3</span><span class="p">)</span> <span class="o">&amp;</span> <span class="p">(</span><span class="n">repeated_names</span><span class="o">.</span><span class="n">issn_count</span> <span class="o">&lt;</span> <span class="mi">20</span><span class="p">)]</span><span class="o">.</span><span class="n">issn_count</span><span class="o">.</span><span class="n">hist</span><span class="p">(</span><span class="n">bins</span><span class="o">=</span><span class="mi">10</span><span class="p">)</span>
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-<div class=" highlight hl-ipython3"><pre><span></span><span class="n">repeated_names</span><span class="p">[(</span><span class="n">repeated_names</span><span class="o">.</span><span class="n">issn_count</span> <span class="o">&gt;</span> <span class="mi">3</span><span class="p">)</span> <span class="o">&amp;</span> <span class="p">(</span><span class="n">repeated_names</span><span class="o">.</span><span class="n">issn_count</span> <span class="o">&lt;</span> <span class="mi">8</span><span class="p">)]</span><span class="o">.</span><span class="n">issn_count</span><span class="o">.</span><span class="n">hist</span><span class="p">()</span>
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-<div class=" highlight hl-ipython3"><pre><span></span><span class="n">repeated_names</span><span class="p">[</span><span class="n">repeated_names</span><span class="o">.</span><span class="n">issn_count</span> <span class="o">&gt;</span> <span class="mi">1000</span><span class="p">]</span><span class="o">.</span><span class="n">issn_count</span><span class="o">.</span><span class="n">hist</span><span class="p">(</span><span class="n">bins</span><span class="o">=</span><span class="mi">10</span><span class="p">)</span>
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-<pre>&lt;AxesSubplot:&gt;</pre>
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src="data:image/png;base64,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->
-</div>
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-</div>
-
-</div>
-</div>
-
-</div>
-<div class="cell border-box-sizing code_cell rendered">
-<div class="input">
-<div class="prompt input_prompt">In&nbsp;[71]:</div>
-<div class="inner_cell">
- <div class="input_area">
-<div class=" highlight hl-ipython3"><pre><span></span><span class="n">repeated_names</span><span class="p">[</span><span class="n">repeated_names</span><span class="o">.</span><span class="n">issn_count</span> <span class="o">&gt;</span> <span class="mi">1000</span><span class="p">]</span>
-</pre></div>
-
- </div>
-</div>
-</div>
-
-<div class="output_wrapper">
-<div class="output">
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-<div class="output_area">
-
- <div class="prompt output_prompt">Out[71]:</div>
-
-
-
-<div class="output_html rendered_html output_subarea output_execute_result">
-<div>
-<style scoped>
- .dataframe tbody tr th:only-of-type {
- vertical-align: middle;
- }
-
- .dataframe tbody tr th {
- vertical-align: top;
- }
-
- .dataframe thead th {
- text-align: right;
- }
-</style>
-<table border="1" class="dataframe">
- <thead>
- <tr style="text-align: right;">
- <th></th>
- <th>name</th>
- <th>issn_count</th>
- </tr>
- </thead>
- <tbody>
- <tr>
- <th>3499</th>
- <td>Bulletin.</td>
- <td>2752</td>
- </tr>
- <tr>
- <th>7632</th>
- <td>Newsletter.</td>
- <td>2715</td>
- </tr>
- <tr>
- <th>8317</th>
- <td>Rapport.</td>
- <td>1050</td>
- </tr>
- <tr>
- <th>23662</th>
- <td>Proceedings.</td>
- <td>1403</td>
- </tr>
- <tr>
- <th>45839</th>
- <td>Annual report /</td>
- <td>1090</td>
- </tr>
- <tr>
- <th>45907</th>
- <td>Annual report.</td>
- <td>8980</td>
- </tr>
- <tr>
- <th>45964</th>
- <td>Annuaire.</td>
- <td>1260</td>
- </tr>
- <tr>
- <th>47217</th>
- <td>Rapport annuel.</td>
- <td>2656</td>
- </tr>
- </tbody>
-</table>
-</div>
-</div>
-
-</div>
-
-</div>
-</div>
-
-</div>
-<div class="cell border-box-sizing code_cell rendered">
-<div class="input">
-<div class="prompt input_prompt">In&nbsp;[72]:</div>
-<div class="inner_cell">
- <div class="input_area">
-<div class=" highlight hl-ipython3"><pre><span></span><span class="n">repeated_names</span><span class="p">[</span><span class="n">repeated_names</span><span class="o">.</span><span class="n">issn_count</span> <span class="o">&gt;</span> <span class="mi">500</span><span class="p">]</span>
-</pre></div>
-
- </div>
-</div>
-</div>
-
-<div class="output_wrapper">
-<div class="output">
-
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-<div class="output_area">
-
- <div class="prompt output_prompt">Out[72]:</div>
-
-
-
-<div class="output_html rendered_html output_subarea output_execute_result">
-<div>
-<style scoped>
- .dataframe tbody tr th:only-of-type {
- vertical-align: middle;
- }
-
- .dataframe tbody tr th {
- vertical-align: top;
- }
-
- .dataframe thead th {
- text-align: right;
- }
-</style>
-<table border="1" class="dataframe">
- <thead>
- <tr style="text-align: right;">
- <th></th>
- <th>name</th>
- <th>issn_count</th>
- </tr>
- </thead>
- <tbody>
- <tr>
- <th>102</th>
- <td>Bulletin d'information.</td>
- <td>693</td>
- </tr>
- <tr>
- <th>3218</th>
- <td>Bulletin de liaison.</td>
- <td>510</td>
- </tr>
- <tr>
- <th>3499</th>
- <td>Bulletin.</td>
- <td>2752</td>
- </tr>
- <tr>
- <th>7632</th>
- <td>Newsletter.</td>
- <td>2715</td>
- </tr>
- <tr>
- <th>8317</th>
- <td>Rapport.</td>
- <td>1050</td>
- </tr>
- <tr>
- <th>23662</th>
- <td>Proceedings.</td>
- <td>1403</td>
- </tr>
- <tr>
- <th>45794</th>
- <td>Report.</td>
- <td>743</td>
- </tr>
- <tr>
- <th>45839</th>
- <td>Annual report /</td>
- <td>1090</td>
- </tr>
- <tr>
- <th>45907</th>
- <td>Annual report.</td>
- <td>8980</td>
- </tr>
- <tr>
- <th>45964</th>
- <td>Annuaire.</td>
- <td>1260</td>
- </tr>
- <tr>
- <th>46370</th>
- <td>Jaarverslag.</td>
- <td>675</td>
- </tr>
- <tr>
- <th>47142</th>
- <td>Rapport d'activité.</td>
- <td>660</td>
- </tr>
- <tr>
- <th>47217</th>
- <td>Rapport annuel.</td>
- <td>2656</td>
- </tr>
- <tr>
- <th>49289</th>
- <td>Jahresbericht.</td>
- <td>518</td>
- </tr>
- <tr>
- <th>57558</th>
- <td>Annual report</td>
- <td>760</td>
- </tr>
- <tr>
- <th>121599</th>
- <td>Alumni directory /</td>
- <td>511</td>
- </tr>
- <tr>
- <th>128827</th>
- <td>Bulletin municipal.</td>
- <td>521</td>
- </tr>
- <tr>
- <th>150529</th>
- <td>˜La œLettre.</td>
- <td>623</td>
- </tr>
- <tr>
- <th>168933</th>
- <td>Local climatological data.</td>
- <td>613</td>
- </tr>
- <tr>
- <th>269004</th>
- <td>Estimates.</td>
- <td>535</td>
- </tr>
- </tbody>
-</table>
-</div>
-</div>
-
-</div>
-
-</div>
-</div>
-
-</div>
-<div class="cell border-box-sizing code_cell rendered">
-<div class="input">
-<div class="prompt input_prompt">In&nbsp;[75]:</div>
-<div class="inner_cell">
- <div class="input_area">
-<div class=" highlight hl-ipython3"><pre><span></span><span class="n">repeated_names</span><span class="p">[</span><span class="n">repeated_names</span><span class="o">.</span><span class="n">issn_count</span> <span class="o">&gt;</span> <span class="mi">200</span><span class="p">]</span>
-</pre></div>
-
- </div>
-</div>
-</div>
-
-<div class="output_wrapper">
-<div class="output">
-
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-<div class="output_area">
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- <div class="prompt output_prompt">Out[75]:</div>
-
-
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-<div class="output_html rendered_html output_subarea output_execute_result">
-<div>
-<style scoped>
- .dataframe tbody tr th:only-of-type {
- vertical-align: middle;
- }
-
- .dataframe tbody tr th {
- vertical-align: top;
- }
-
- .dataframe thead th {
- text-align: right;
- }
-</style>
-<table border="1" class="dataframe">
- <thead>
- <tr style="text-align: right;">
- <th></th>
- <th>name</th>
- <th>issn_count</th>
- </tr>
- </thead>
- <tbody>
- <tr>
- <th>102</th>
- <td>Bulletin d'information.</td>
- <td>693</td>
- </tr>
- <tr>
- <th>2665</th>
- <td>Newsletter /</td>
- <td>259</td>
- </tr>
- <tr>
- <th>3218</th>
- <td>Bulletin de liaison.</td>
- <td>510</td>
- </tr>
- <tr>
- <th>3499</th>
- <td>Bulletin.</td>
- <td>2752</td>
- </tr>
- <tr>
- <th>3926</th>
- <td>Boletín.</td>
- <td>216</td>
- </tr>
- <tr>
- <th>...</th>
- <td>...</td>
- <td>...</td>
- </tr>
- <tr>
- <th>425644</th>
- <td>Rapport d'activité ...</td>
- <td>394</td>
- </tr>
- <tr>
- <th>532500</th>
- <td>Relatório e contas.</td>
- <td>247</td>
- </tr>
- <tr>
- <th>603144</th>
- <td>Bildung und Beruf regional.</td>
- <td>292</td>
- </tr>
- <tr>
- <th>1006131</th>
- <td>Vies de famille.</td>
- <td>222</td>
- </tr>
- <tr>
- <th>1110247</th>
- <td>Country risk service.</td>
- <td>271</td>
- </tr>
- </tbody>
-</table>
-<p>66 rows × 2 columns</p>
-</div>
-</div>
-
-</div>
-
-</div>
-</div>
-
-</div>
-<div class="cell border-box-sizing code_cell rendered">
-<div class="input">
-<div class="prompt input_prompt">In&nbsp;[76]:</div>
-<div class="inner_cell">
- <div class="input_area">
-<div class=" highlight hl-ipython3"><pre><span></span><span class="n">repeated_names</span><span class="p">[</span><span class="n">repeated_names</span><span class="o">.</span><span class="n">issn_count</span> <span class="o">&gt;</span> <span class="mi">100</span><span class="p">]</span>
-</pre></div>
-
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-</div>
-</div>
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-<div class="output_wrapper">
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-<style scoped>
- .dataframe tbody tr th:only-of-type {
- vertical-align: middle;
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- vertical-align: top;
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- text-align: right;
- }
-</style>
-<table border="1" class="dataframe">
- <thead>
- <tr style="text-align: right;">
- <th></th>
- <th>name</th>
- <th>issn_count</th>
- </tr>
- </thead>
- <tbody>
- <tr>
- <th>102</th>
- <td>Bulletin d'information.</td>
- <td>693</td>
- </tr>
- <tr>
- <th>2665</th>
- <td>Newsletter /</td>
- <td>259</td>
- </tr>
- <tr>
- <th>3218</th>
- <td>Bulletin de liaison.</td>
- <td>510</td>
- </tr>
- <tr>
- <th>3499</th>
- <td>Bulletin.</td>
- <td>2752</td>
- </tr>
- <tr>
- <th>3926</th>
- <td>Boletín.</td>
- <td>216</td>
- </tr>
- <tr>
- <th>...</th>
- <td>...</td>
- <td>...</td>
- </tr>
- <tr>
- <th>1306798</th>
- <td>Country commerce.</td>
- <td>120</td>
- </tr>
- <tr>
- <th>1318569</th>
- <td>Bible studies for life.</td>
- <td>159</td>
- </tr>
- <tr>
- <th>1796742</th>
- <td>LexisNexis practice guide.</td>
- <td>101</td>
- </tr>
- <tr>
- <th>2628387</th>
- <td>Operational risk report.</td>
- <td>119</td>
- </tr>
- <tr>
- <th>2650557</th>
- <td>Interempresas net.</td>
- <td>108</td>
- </tr>
- </tbody>
-</table>
-<p>191 rows × 2 columns</p>
-</div>
-</div>
-
-</div>
-
-</div>
-</div>
-
-</div>
-<div class="cell border-box-sizing code_cell rendered">
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-<div class="inner_cell">
- <div class="input_area">
-<div class=" highlight hl-ipython3"><pre><span></span><span class="n">repeated_names</span>
-</pre></div>
-
- </div>
-</div>
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- text-align: right;
- }
-</style>
-<table border="1" class="dataframe">
- <thead>
- <tr style="text-align: right;">
- <th></th>
- <th>name</th>
- <th>issn_count</th>
- </tr>
- </thead>
- <tbody>
- <tr>
- <th>5</th>
- <td>Activitas Nervosa Superior.</td>
- <td>2</td>
- </tr>
- <tr>
- <th>11</th>
- <td>Library journal.</td>
- <td>2</td>
- </tr>
- <tr>
- <th>23</th>
- <td>Acta cardiologica.</td>
- <td>2</td>
- </tr>
- <tr>
- <th>26</th>
- <td>Actualidad económica.</td>
- <td>3</td>
- </tr>
- <tr>
- <th>31</th>
- <td>Acta Ornithologica.</td>
- <td>3</td>
- </tr>
- <tr>
- <th>...</th>
- <td>...</td>
- <td>...</td>
- </tr>
- <tr>
- <th>2929626</th>
- <td>Modern machine shop México.</td>
- <td>2</td>
- </tr>
- <tr>
- <th>2929635</th>
- <td>Lecture notes in control and information scien...</td>
- <td>2</td>
- </tr>
- <tr>
- <th>2929646</th>
- <td>Critical Studies in Dance Leadership and Inclu...</td>
- <td>2</td>
- </tr>
- <tr>
- <th>2929691</th>
- <td>Nigerian Journal of Wildlife Management</td>
- <td>2</td>
- </tr>
- <tr>
- <th>2929702</th>
- <td>Verzeichniss der Kunstwerke lebender Künstler,...</td>
- <td>2</td>
- </tr>
- </tbody>
-</table>
-<p>194241 rows × 2 columns</p>
-</div>
-</div>
-
-</div>
-
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-</div>
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-</div>
-<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
-</div><div class="inner_cell">
-<div class="text_cell_render border-box-sizing rendered_html">
-<p>If a name matches a repeated name exactly or fuzzy matches to a repeated name and there is not other information available, the match status must be ambigious.</p>
-
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diff --git a/notebooks/Journal_Names.ipynb b/notebooks/Journal_Names.ipynb
deleted file mode 100644
index 91da2a2..0000000
--- a/notebooks/Journal_Names.ipynb
+++ /dev/null
@@ -1,2032 +0,0 @@
-{
- "cells": [
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# Journal Names\n",
- "\n",
- "Questions in the context of fuzzy matching.\n",
- "\n",
- "* How many journal names appear more than once?\n",
- "* What is the average length of the duplicated names vs the unique names?\n",
- "\n",
- "\n",
- "Input file is a single larger JSON, mapping names to issns.\n",
- "```json\n",
- "{\n",
- " \"Acta Orientalia.\": [\n",
- " \"0001-6438\"\n",
- " ],\n",
- " \"Acta Orientalia (København)\": [\n",
- " \"0001-6438\"\n",
- " ],\n",
- "..\n",
- "```"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 62,
- "metadata": {},
- "outputs": [],
- "source": [
- "import json\n",
- "import pandas as pd"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 63,
- "metadata": {},
- "outputs": [],
- "source": [
- "with open(\"../data/name_to_issn.json\") as f:\n",
- " mapping = json.load(f)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "We have about 3M keys."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 64,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "2938859"
- ]
- },
- "execution_count": 64,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "len(mapping)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 65,
- "metadata": {},
- "outputs": [],
- "source": [
- "df = pd.DataFrame(((k, len(v)) for k, v in mapping.items()), columns=[\"name\", \"issn_count\"])"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 66,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "2938859"
- ]
- },
- "execution_count": 66,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "len(df)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 67,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/html": [
- "<div>\n",
- "<style scoped>\n",
- " .dataframe tbody tr th:only-of-type {\n",
- " vertical-align: middle;\n",
- " }\n",
- "\n",
- " .dataframe tbody tr th {\n",
- " vertical-align: top;\n",
- " }\n",
- "\n",
- " .dataframe thead th {\n",
- " text-align: right;\n",
- " }\n",
- "</style>\n",
- "<table border=\"1\" class=\"dataframe\">\n",
- " <thead>\n",
- " <tr style=\"text-align: right;\">\n",
- " <th></th>\n",
- " <th>name</th>\n",
- " <th>issn_count</th>\n",
- " </tr>\n",
- " </thead>\n",
- " <tbody>\n",
- " <tr>\n",
- " <th>0</th>\n",
- " <td>Acta Orientalia.</td>\n",
- " <td>1</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>1</th>\n",
- " <td>Acta Orientalia (København)</td>\n",
- " <td>1</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>2</th>\n",
- " <td>˜The œpublishers weekly.</td>\n",
- " <td>2</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>3</th>\n",
- " <td>Publishers weekly</td>\n",
- " <td>2</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>4</th>\n",
- " <td>ASMT news</td>\n",
- " <td>1</td>\n",
- " </tr>\n",
- " </tbody>\n",
- "</table>\n",
- "</div>"
- ],
- "text/plain": [
- " name issn_count\n",
- "0 Acta Orientalia. 1\n",
- "1 Acta Orientalia (København) 1\n",
- "2 ˜The œpublishers weekly. 2\n",
- "3 Publishers weekly 2\n",
- "4 ASMT news 1"
- ]
- },
- "execution_count": 67,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "df.head()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 68,
- "metadata": {},
- "outputs": [],
- "source": [
- "unique_name = df[df.issn_count == 1]"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 69,
- "metadata": {},
- "outputs": [],
- "source": [
- "repeated_names = df[df.issn_count > 1]"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 70,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "586466"
- ]
- },
- "execution_count": 70,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "len(repeated_names)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 71,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "0.1995556779008452"
- ]
- },
- "execution_count": 71,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "len(repeated_names) / len(df)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "About 19% (or 586466) names are repeated. "
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 72,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/html": [
- "<div>\n",
- "<style scoped>\n",
- " .dataframe tbody tr th:only-of-type {\n",
- " vertical-align: middle;\n",
- " }\n",
- "\n",
- " .dataframe tbody tr th {\n",
- " vertical-align: top;\n",
- " }\n",
- "\n",
- " .dataframe thead th {\n",
- " text-align: right;\n",
- " }\n",
- "</style>\n",
- "<table border=\"1\" class=\"dataframe\">\n",
- " <thead>\n",
- " <tr style=\"text-align: right;\">\n",
- " <th></th>\n",
- " <th>issn_count</th>\n",
- " </tr>\n",
- " </thead>\n",
- " <tbody>\n",
- " <tr>\n",
- " <th>count</th>\n",
- " <td>586466.000000</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>mean</th>\n",
- " <td>2.443930</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>std</th>\n",
- " <td>15.260303</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>min</th>\n",
- " <td>2.000000</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>25%</th>\n",
- " <td>2.000000</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>50%</th>\n",
- " <td>2.000000</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>75%</th>\n",
- " <td>2.000000</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>max</th>\n",
- " <td>9520.000000</td>\n",
- " </tr>\n",
- " </tbody>\n",
- "</table>\n",
- "</div>"
- ],
- "text/plain": [
- " issn_count\n",
- "count 586466.000000\n",
- "mean 2.443930\n",
- "std 15.260303\n",
- "min 2.000000\n",
- "25% 2.000000\n",
- "50% 2.000000\n",
- "75% 2.000000\n",
- "max 9520.000000"
- ]
- },
- "execution_count": 72,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "repeated_names.describe()"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Which name is shared most?"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 73,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "name Annual report.\n",
- "issn_count 9520\n",
- "Name: 45999, dtype: object"
- ]
- },
- "execution_count": 73,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "repeated_names.iloc[repeated_names.issn_count.argmax()] # Annual report."
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "It is the \"Annual report.\""
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 74,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "['1495-9097',\n",
- " '2205-7919',\n",
- " '1447-3836',\n",
- " '1914-9220',\n",
- " '0707-1515',\n",
- " '1494-6149',\n",
- " '2293-3174',\n",
- " '1977-9046',\n",
- " '0707-4298',\n",
- " '2239-9674']"
- ]
- },
- "execution_count": 74,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "mapping[\"Annual report.\"][:10]"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "On average a repeated name will point to 3 ISSN. Over 20k names point to more than 3 ISSN."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 76,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "27230"
- ]
- },
- "execution_count": 76,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "len(repeated_names[repeated_names.issn_count > 3])"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 77,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/html": [
- "<div>\n",
- "<style scoped>\n",
- " .dataframe tbody tr th:only-of-type {\n",
- " vertical-align: middle;\n",
- " }\n",
- "\n",
- " .dataframe tbody tr th {\n",
- " vertical-align: top;\n",
- " }\n",
- "\n",
- " .dataframe thead th {\n",
- " text-align: right;\n",
- " }\n",
- "</style>\n",
- "<table border=\"1\" class=\"dataframe\">\n",
- " <thead>\n",
- " <tr style=\"text-align: right;\">\n",
- " <th></th>\n",
- " <th>name</th>\n",
- " <th>issn_count</th>\n",
- " </tr>\n",
- " </thead>\n",
- " <tbody>\n",
- " <tr>\n",
- " <th>1356987</th>\n",
- " <td>Karrier online</td>\n",
- " <td>6</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>1778072</th>\n",
- " <td>Curriculum express for parents.</td>\n",
- " <td>4</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>366690</th>\n",
- " <td>Annual Report ....</td>\n",
- " <td>7</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>878789</th>\n",
- " <td>Brilliant.</td>\n",
- " <td>4</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>37507</th>\n",
- " <td>Synthesis.</td>\n",
- " <td>35</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>942931</th>\n",
- " <td>Special Burda</td>\n",
- " <td>11</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>640073</th>\n",
- " <td>Belle.</td>\n",
- " <td>6</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>2666134</th>\n",
- " <td>Naše delo</td>\n",
- " <td>6</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>376646</th>\n",
- " <td>Opinion.</td>\n",
- " <td>12</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>918869</th>\n",
- " <td>Limited edition magazine.</td>\n",
- " <td>16</td>\n",
- " </tr>\n",
- " </tbody>\n",
- "</table>\n",
- "</div>"
- ],
- "text/plain": [
- " name issn_count\n",
- "1356987 Karrier online 6\n",
- "1778072 Curriculum express for parents. 4\n",
- "366690 Annual Report .... 7\n",
- "878789 Brilliant. 4\n",
- "37507 Synthesis. 35\n",
- "942931 Special Burda 11\n",
- "640073 Belle. 6\n",
- "2666134 Naše delo 6\n",
- "376646 Opinion. 12\n",
- "918869 Limited edition magazine. 16"
- ]
- },
- "execution_count": 77,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "repeated_names[repeated_names.issn_count > 3].sample(n=10)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 78,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "['1158-9574',\n",
- " '2183-0134',\n",
- " '1517-8889',\n",
- " '1480-4670',\n",
- " '0379-8402',\n",
- " '1724-6598',\n",
- " '2035-8326',\n",
- " '2249-5053',\n",
- " '0872-4784',\n",
- " '2610-8933',\n",
- " '2610-8925',\n",
- " '2654-9263',\n",
- " '2420-9198',\n",
- " '2538-693X',\n",
- " '1487-5349',\n",
- " '1285-9133',\n",
- " '2655-5662',\n",
- " '2295-9084']"
- ]
- },
- "execution_count": 78,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "mapping[\"Philosophica.\"]"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 79,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<AxesSubplot:>"
- ]
- },
- "execution_count": 79,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": 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\n",
- "text/plain": [
- "<Figure size 432x288 with 1 Axes>"
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "repeated_names[repeated_names.issn_count > 3].issn_count.hist(bins=20)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 80,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<AxesSubplot:>"
- ]
- },
- "execution_count": 80,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": 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\n",
- "text/plain": [
- "<Figure size 432x288 with 1 Axes>"
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "repeated_names[(repeated_names.issn_count > 3) & (repeated_names.issn_count < 50)].issn_count.hist(bins=10)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 81,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<AxesSubplot:>"
- ]
- },
- "execution_count": 81,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": 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\n",
- "text/plain": [
- "<Figure size 432x288 with 1 Axes>"
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "repeated_names[(repeated_names.issn_count > 3) & (repeated_names.issn_count < 20)].issn_count.hist(bins=10)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 82,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<AxesSubplot:>"
- ]
- },
- "execution_count": 82,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": 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\n",
- "text/plain": [
- "<Figure size 432x288 with 1 Axes>"
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "repeated_names[(repeated_names.issn_count > 3) & (repeated_names.issn_count < 8)].issn_count.hist()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 83,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<AxesSubplot:>"
- ]
- },
- "execution_count": 83,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
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- "cell_type": "code",
- "execution_count": 87,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/html": [
- "<div>\n",
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- " .dataframe tbody tr th:only-of-type {\n",
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- " <thead>\n",
- " <tr style=\"text-align: right;\">\n",
- " <th></th>\n",
- " <th>name</th>\n",
- " <th>issn_count</th>\n",
- " </tr>\n",
- " </thead>\n",
- " <tbody>\n",
- " <tr>\n",
- " <th>103</th>\n",
- " <td>Bulletin d'information.</td>\n",
- " <td>696</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>2676</th>\n",
- " <td>Newsletter /</td>\n",
- " <td>290</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>3230</th>\n",
- " <td>Bulletin de liaison.</td>\n",
- " <td>512</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>3511</th>\n",
- " <td>Bulletin.</td>\n",
- " <td>2797</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>3941</th>\n",
- " <td>Boletín.</td>\n",
- " <td>227</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>...</th>\n",
- " <td>...</td>\n",
- " <td>...</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>1315194</th>\n",
- " <td>Country commerce.</td>\n",
- " <td>120</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>1327255</th>\n",
- " <td>Bible studies for life.</td>\n",
- " <td>159</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>1805527</th>\n",
- " <td>LexisNexis practice guide.</td>\n",
- " <td>110</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>2637306</th>\n",
- " <td>Operational risk report.</td>\n",
- " <td>119</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>2659477</th>\n",
- " <td>Interempresas net.</td>\n",
- " <td>115</td>\n",
- " </tr>\n",
- " </tbody>\n",
- "</table>\n",
- "<p>204 rows × 2 columns</p>\n",
- "</div>"
- ],
- "text/plain": [
- " name issn_count\n",
- "103 Bulletin d'information. 696\n",
- "2676 Newsletter / 290\n",
- "3230 Bulletin de liaison. 512\n",
- "3511 Bulletin. 2797\n",
- "3941 Boletín. 227\n",
- "... ... ...\n",
- "1315194 Country commerce. 120\n",
- "1327255 Bible studies for life. 159\n",
- "1805527 LexisNexis practice guide. 110\n",
- "2637306 Operational risk report. 119\n",
- "2659477 Interempresas net. 115\n",
- "\n",
- "[204 rows x 2 columns]"
- ]
- },
- "execution_count": 87,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "repeated_names[repeated_names.issn_count > 100]"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 88,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/html": [
- "<div>\n",
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- " .dataframe tbody tr th:only-of-type {\n",
- " vertical-align: middle;\n",
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- " </tr>\n",
- " </thead>\n",
- " <tbody>\n",
- " <tr>\n",
- " <th>2</th>\n",
- " <td>˜The œpublishers weekly.</td>\n",
- " <td>2</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>3</th>\n",
- " <td>Publishers weekly</td>\n",
- " <td>2</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>6</th>\n",
- " <td>Activitas Nervosa Superior.</td>\n",
- " <td>2</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>12</th>\n",
- " <td>Library journal.</td>\n",
- " <td>2</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>24</th>\n",
- " <td>Acta cardiologica.</td>\n",
- " <td>2</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>...</th>\n",
- " <td>...</td>\n",
- " <td>...</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>2938851</th>\n",
- " <td>AAPS introductions in the pharmaceutical scien...</td>\n",
- " <td>2</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>2938852</th>\n",
- " <td>AAPS introductions in the pharmaceutical scien...</td>\n",
- " <td>2</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>2938856</th>\n",
- " <td>Verzeichniss der Werke lebender Künstler auf d...</td>\n",
- " <td>2</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>2938857</th>\n",
- " <td>IEEE Advanced Information Management, Communic...</td>\n",
- " <td>2</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>2938858</th>\n",
- " <td>Products finishing México (Print)</td>\n",
- " <td>2</td>\n",
- " </tr>\n",
- " </tbody>\n",
- "</table>\n",
- "<p>586466 rows × 2 columns</p>\n",
- "</div>"
- ],
- "text/plain": [
- " name issn_count\n",
- "2 ˜The œpublishers weekly. 2\n",
- "3 Publishers weekly 2\n",
- "6 Activitas Nervosa Superior. 2\n",
- "12 Library journal. 2\n",
- "24 Acta cardiologica. 2\n",
- "... ... ...\n",
- "2938851 AAPS introductions in the pharmaceutical scien... 2\n",
- "2938852 AAPS introductions in the pharmaceutical scien... 2\n",
- "2938856 Verzeichniss der Werke lebender Künstler auf d... 2\n",
- "2938857 IEEE Advanced Information Management, Communic... 2\n",
- "2938858 Products finishing México (Print) 2\n",
- "\n",
- "[586466 rows x 2 columns]"
- ]
- },
- "execution_count": 88,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "repeated_names"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "If a name matches a repeated name exactly or fuzzy matches to a repeated name and there is not other information available, the match status must be ambigious."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 89,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "['2735-9298', '2735-928X']"
- ]
- },
- "execution_count": 89,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "mapping[\"Nigerian Journal of Wildlife Management\"]"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "These are two ISSN refering to the same journal."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 90,
- "metadata": {},
- "outputs": [],
- "source": [
- "import requests"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 91,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "{'@graph': [{'@id': 'http://id.loc.gov/vocabulary/countries/nr',\n",
- " 'label': 'Nigeria'},\n",
- " {'@id': 'organization/ISSNCenter#_e',\n",
- " '@type': 'http://schema.org/Organization'},\n",
- " {'@id': 'resource/ISSN-L/2735-9298',\n",
- " 'identifiedBy': 'resource/ISSN/2735-928X#ISSN-L'},\n",
- " {'@id': 'resource/ISSN/2735-928X',\n",
- " '@type': ['http://id.loc.gov/ontologies/bibframe/Work',\n",
- " 'http://id.loc.gov/ontologies/bibframe/Instance',\n",
- " 'http://schema.org/Periodical'],\n",
- " 'identifiedBy': ['resource/ISSN/2735-928X#ISSN-L',\n",
- " 'resource/ISSN/2735-928X#ISSN',\n",
- " 'resource/ISSN/2735-928X#KeyTitle'],\n",
- " 'mainTitle': 'Nigerian Journal of Wildlife Management',\n",
- " 'otherPhysicalFormat': 'resource/ISSN/2735-9298',\n",
- " 'title': 'resource/ISSN/2735-928X#KeyTitle',\n",
- " 'format': 'vocabularies/medium#Online',\n",
- " 'identifier': '2735-928X',\n",
- " 'isFormatOf': 'resource/ISSN/2735-9298',\n",
- " 'type': 'http://marc21rdf.info/terms/formofmaterial#a',\n",
- " 'http://purl.org/ontology/bibo/issn': '2735-928X',\n",
- " 'isPartOf': 'resource/ISSN-L/2735-9298',\n",
- " 'issn': '2735-928X',\n",
- " 'name': ['Nigerian JOurnal of Wildlife Management (Ondo. Online)',\n",
- " 'Nigerian Journal of Wildlife Management'],\n",
- " 'publication': 'resource/ISSN/2735-928X#ReferencePublicationEvent',\n",
- " 'url': 'http://www.wildlifesociety.ng.org/'},\n",
- " {'@id': 'resource/ISSN/2735-928X#ISSN',\n",
- " '@type': 'http://id.loc.gov/ontologies/bibframe/Issn',\n",
- " 'status': 'vocabularies/IdentifierStatus#Valid',\n",
- " 'value': '2735-928X'},\n",
- " {'@id': 'resource/ISSN/2735-928X#ISSN-L',\n",
- " '@type': 'http://id.loc.gov/ontologies/bibframe/IssnL',\n",
- " 'status': 'vocabularies/IdentifierStatus#Valid',\n",
- " 'value': '2735-9298'},\n",
- " {'@id': 'resource/ISSN/2735-928X#KeyTitle',\n",
- " '@type': ['http://id.loc.gov/ontologies/bibframe/Identifier',\n",
- " 'http://id.loc.gov/ontologies/bibframe/KeyTitle'],\n",
- " 'value': 'Nigerian JOurnal of Wildlife Management (Ondo. Online)'},\n",
- " {'@id': 'resource/ISSN/2735-928X#Record',\n",
- " '@type': 'http://schema.org/CreativeWork',\n",
- " 'status': 'vocabularies/RecordStatus#Register',\n",
- " 'modified': '20200808163600.0',\n",
- " 'mainEntity': 'resource/ISSN/2735-928X',\n",
- " 'wasAttributedTo': 'organization/ISSNCenter#_e'},\n",
- " {'@id': 'resource/ISSN/2735-928X#ReferencePublicationEvent',\n",
- " '@type': 'http://schema.org/PublicationEvent',\n",
- " 'location': 'http://id.loc.gov/vocabulary/countries/nr'}],\n",
- " '@context': {'status': {'@id': 'http://id.loc.gov/ontologies/bibframe/status',\n",
- " '@type': '@id'},\n",
- " 'value': {'@id': 'http://www.w3.org/1999/02/22-rdf-syntax-ns#value'},\n",
- " 'publication': {'@id': 'http://schema.org/publication', '@type': '@id'},\n",
- " 'mainTitle': {'@id': 'http://id.loc.gov/ontologies/bibframe/mainTitle'},\n",
- " 'title': {'@id': 'http://id.loc.gov/ontologies/bibframe/title',\n",
- " '@type': '@id'},\n",
- " 'name': {'@id': 'http://schema.org/name'},\n",
- " 'issn': {'@id': 'http://schema.org/issn'},\n",
- " 'format': {'@id': 'http://purl.org/dc/elements/1.1/format', '@type': '@id'},\n",
- " 'url': {'@id': 'http://schema.org/url'},\n",
- " 'identifiedBy': {'@id': 'http://id.loc.gov/ontologies/bibframe/identifiedBy',\n",
- " '@type': '@id'},\n",
- " 'otherPhysicalFormat': {'@id': 'http://id.loc.gov/ontologies/bibframe/otherPhysicalFormat',\n",
- " '@type': '@id'},\n",
- " 'isPartOf': {'@id': 'http://schema.org/isPartOf', '@type': '@id'},\n",
- " 'type': {'@id': 'http://purl.org/dc/terms/type', '@type': '@id'},\n",
- " 'identifier': {'@id': 'http://purl.org/dc/elements/1.1/identifier'},\n",
- " 'isFormatOf': {'@id': 'http://purl.org/dc/terms/isFormatOf', '@type': '@id'},\n",
- " 'wasAttributedTo': {'@id': 'http://www.w3.org/ns/prov#wasAttributedTo',\n",
- " '@type': '@id'},\n",
- " 'mainEntity': {'@id': 'http://schema.org/mainEntity', '@type': '@id'},\n",
- " 'modified': {'@id': 'http://purl.org/dc/terms/modified',\n",
- " '@type': 'http://www.w3.org/2001/XMLSchema#dateTime'},\n",
- " 'location': {'@id': 'http://schema.org/location', '@type': '@id'},\n",
- " 'label': {'@id': 'http://www.w3.org/2000/01/rdf-schema#label'}}}"
- ]
- },
- "execution_count": 91,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "requests.get(\"https://portal.issn.org/resource/ISSN/2735-928X?format=json\").json()"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Interestingly, most (80%) journal do not seem to have the distinction between electronic and print. But it may be that names are not used consistently."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 94,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "0.8004443220991548"
- ]
- },
- "execution_count": 94,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "len(unique_name) / len(df)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 96,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/html": [
- "<div>\n",
- "<style scoped>\n",
- " .dataframe tbody tr th:only-of-type {\n",
- " vertical-align: middle;\n",
- " }\n",
- "\n",
- " .dataframe tbody tr th {\n",
- " vertical-align: top;\n",
- " }\n",
- "\n",
- " .dataframe thead th {\n",
- " text-align: right;\n",
- " }\n",
- "</style>\n",
- "<table border=\"1\" class=\"dataframe\">\n",
- " <thead>\n",
- " <tr style=\"text-align: right;\">\n",
- " <th></th>\n",
- " <th>name</th>\n",
- " <th>issn_count</th>\n",
- " </tr>\n",
- " </thead>\n",
- " <tbody>\n",
- " <tr>\n",
- " <th>1848393</th>\n",
- " <td>Aux petits bonheurs des enfants</td>\n",
- " <td>1</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>1147789</th>\n",
- " <td>Statistik om boliger ... i Aalborg Kommune.</td>\n",
- " <td>1</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>2789832</th>\n",
- " <td>Mur (Regensburg)</td>\n",
- " <td>1</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>35201</th>\n",
- " <td>Boletín de la Sociedad Vasco-Navarra de pediat...</td>\n",
- " <td>1</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>1955109</th>\n",
- " <td>Cucina piatti unici.</td>\n",
- " <td>1</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>1039</th>\n",
- " <td>ABD</td>\n",
- " <td>1</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>2595157</th>\n",
- " <td>Tribuna quinzenal de Mataró</td>\n",
- " <td>1</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>416131</th>\n",
- " <td>Japan high tech review</td>\n",
- " <td>1</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>2885449</th>\n",
- " <td>Revista cósmica calavera.</td>\n",
- " <td>1</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>343232</th>\n",
- " <td>First days.</td>\n",
- " <td>1</td>\n",
- " </tr>\n",
- " </tbody>\n",
- "</table>\n",
- "</div>"
- ],
- "text/plain": [
- " name issn_count\n",
- "1848393 Aux petits bonheurs des enfants 1\n",
- "1147789 Statistik om boliger ... i Aalborg Kommune. 1\n",
- "2789832 Mur (Regensburg) 1\n",
- "35201 Boletín de la Sociedad Vasco-Navarra de pediat... 1\n",
- "1955109 Cucina piatti unici. 1\n",
- "1039 ABD 1\n",
- "2595157 Tribuna quinzenal de Mataró 1\n",
- "416131 Japan high tech review 1\n",
- "2885449 Revista cósmica calavera. 1\n",
- "343232 First days. 1"
- ]
- },
- "execution_count": 96,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "unique_name.sample(n=10)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Example \"Fieldiana\"\n",
- "\n",
- "* \"Fieldiana. Anthropology\"\n",
- "* https://www.jstor.org/journal/fieldianaanthro"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 97,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "['2162-4321', '0071-4739']"
- ]
- },
- "execution_count": 97,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "mapping[\"Fieldiana. Anthropology\"]"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "However, jstor reports two ISSN: INSSP: 0071-4739, EISSN: 2162-4321 - but ISSN.org does not know about it?"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 98,
- "metadata": {},
- "outputs": [],
- "source": [
- "unique_issn = set([item for v in mapping.values() for item in v])"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 99,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "True"
- ]
- },
- "execution_count": 99,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "\"2162-4321\" in unique_issn"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 100,
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Fieldiana. ['2162-4267', '2162-4321', '2162-4291', '0096-2651', '0015-0746', '0097-3572', '2163-7105', '0071-4739', '0015-0754', '2158-5520', '0096-0438', '2162-4348']\n",
- "Fieldiana. Anthropology ['2162-4321', '0071-4739']\n",
- "Fieldiana. Anthropology (Online) ['2162-4321', '0071-4739']\n"
- ]
- }
- ],
- "source": [
- "for k, v in mapping.items():\n",
- " if \"2162-4321\" in v:\n",
- " print(k, v)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "As an example: when given a string like \"Fieldiana\" we would return ambiguous. But \"Fieldiana. (Online)\" might be matched to '2162-4321'. "
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Other Examples"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 101,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/html": [
- "<div>\n",
- "<style scoped>\n",
- " .dataframe tbody tr th:only-of-type {\n",
- " vertical-align: middle;\n",
- " }\n",
- "\n",
- " .dataframe tbody tr th {\n",
- " vertical-align: top;\n",
- " }\n",
- "\n",
- " .dataframe thead th {\n",
- " text-align: right;\n",
- " }\n",
- "</style>\n",
- "<table border=\"1\" class=\"dataframe\">\n",
- " <thead>\n",
- " <tr style=\"text-align: right;\">\n",
- " <th></th>\n",
- " <th>name</th>\n",
- " <th>issn_count</th>\n",
- " </tr>\n",
- " </thead>\n",
- " <tbody>\n",
- " <tr>\n",
- " <th>571163</th>\n",
- " <td>Afhandling.</td>\n",
- " <td>2</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>1800364</th>\n",
- " <td>Advances in e-business research series (Online)</td>\n",
- " <td>2</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>2476171</th>\n",
- " <td>Journal of Automatic Control (Online)</td>\n",
- " <td>2</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>2756754</th>\n",
- " <td>Gerencia de riesgos y seguros.</td>\n",
- " <td>2</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>2799421</th>\n",
- " <td>˜The œskinny (Scotland ed. Online)</td>\n",
- " <td>2</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>1254438</th>\n",
- " <td>Accessible news (Print)</td>\n",
- " <td>2</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>2177530</th>\n",
- " <td>Biomathematical and biomechanical modeling of ...</td>\n",
- " <td>2</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>2093431</th>\n",
- " <td>˜Le œJura socialiste (Saint-Claude)</td>\n",
- " <td>2</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>2752857</th>\n",
- " <td>European Journal of Formal Sciences and Engine...</td>\n",
- " <td>2</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>389738</th>\n",
- " <td>Austral journal of veterinary sciences (Online)</td>\n",
- " <td>2</td>\n",
- " </tr>\n",
- " </tbody>\n",
- "</table>\n",
- "</div>"
- ],
- "text/plain": [
- " name issn_count\n",
- "571163 Afhandling. 2\n",
- "1800364 Advances in e-business research series (Online) 2\n",
- "2476171 Journal of Automatic Control (Online) 2\n",
- "2756754 Gerencia de riesgos y seguros. 2\n",
- "2799421 ˜The œskinny (Scotland ed. Online) 2\n",
- "1254438 Accessible news (Print) 2\n",
- "2177530 Biomathematical and biomechanical modeling of ... 2\n",
- "2093431 ˜Le œJura socialiste (Saint-Claude) 2\n",
- "2752857 European Journal of Formal Sciences and Engine... 2\n",
- "389738 Austral journal of veterinary sciences (Online) 2"
- ]
- },
- "execution_count": 101,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "repeated_names.sample(n=10)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 102,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "['1608-3318', '1070-3284']"
- ]
- },
- "execution_count": 102,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "mapping[\"Russian journal of coordination chemistry.\"]"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "A new question: How many journals are listed under different names, yet still refer to the same journal?"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 103,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "['0733-2289']"
- ]
- },
- "execution_count": 103,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "mapping[\"San Bernardino County popular street atlas\"]"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Journal of ..."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 104,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/html": [
- "<div>\n",
- "<style scoped>\n",
- " .dataframe tbody tr th:only-of-type {\n",
- " vertical-align: middle;\n",
- " }\n",
- "\n",
- " .dataframe tbody tr th {\n",
- " vertical-align: top;\n",
- " }\n",
- "\n",
- " .dataframe thead th {\n",
- " text-align: right;\n",
- " }\n",
- "</style>\n",
- "<table border=\"1\" class=\"dataframe\">\n",
- " <thead>\n",
- " <tr style=\"text-align: right;\">\n",
- " <th></th>\n",
- " <th>name</th>\n",
- " <th>issn_count</th>\n",
- " </tr>\n",
- " </thead>\n",
- " <tbody>\n",
- " <tr>\n",
- " <th>983</th>\n",
- " <td>Journal of vocational behavior.</td>\n",
- " <td>2</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>984</th>\n",
- " <td>Journal of vocational behavior (Print)</td>\n",
- " <td>2</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>1213</th>\n",
- " <td>Journal of American Concrete Institute.</td>\n",
- " <td>1</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>1214</th>\n",
- " <td>Journal of the American Concrete Institute</td>\n",
- " <td>1</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>1317</th>\n",
- " <td>Journal of the American Dental Hygienists' Ass...</td>\n",
- " <td>1</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>...</th>\n",
- " <td>...</td>\n",
- " <td>...</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>2938472</th>\n",
- " <td>Journal of surgical procedures and case reports</td>\n",
- " <td>1</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>2938580</th>\n",
- " <td>Journal of Epidermiological Society of Nigeria...</td>\n",
- " <td>2</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>2938581</th>\n",
- " <td>Journal of Epidermiological Society of Nigeria</td>\n",
- " <td>2</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>2938795</th>\n",
- " <td>Journal of Practicing Teachers</td>\n",
- " <td>1</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>2938796</th>\n",
- " <td>Journal of Practicing Teachers (Uyo. Online)</td>\n",
- " <td>1</td>\n",
- " </tr>\n",
- " </tbody>\n",
- "</table>\n",
- "<p>40257 rows × 2 columns</p>\n",
- "</div>"
- ],
- "text/plain": [
- " name issn_count\n",
- "983 Journal of vocational behavior. 2\n",
- "984 Journal of vocational behavior (Print) 2\n",
- "1213 Journal of American Concrete Institute. 1\n",
- "1214 Journal of the American Concrete Institute 1\n",
- "1317 Journal of the American Dental Hygienists' Ass... 1\n",
- "... ... ...\n",
- "2938472 Journal of surgical procedures and case reports 1\n",
- "2938580 Journal of Epidermiological Society of Nigeria... 2\n",
- "2938581 Journal of Epidermiological Society of Nigeria 2\n",
- "2938795 Journal of Practicing Teachers 1\n",
- "2938796 Journal of Practicing Teachers (Uyo. Online) 1\n",
- "\n",
- "[40257 rows x 2 columns]"
- ]
- },
- "execution_count": 104,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "df[df.name.str.startswith(\"Journal of\")]"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": []
- }
- ],
- "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": "3.7.8"
- }
- },
- "nbformat": 4,
- "nbformat_minor": 4
-}
diff --git a/notebooks/Journal_Names.pdf b/notebooks/Journal_Names.pdf
deleted file mode 100644
index 04f392b..0000000
--- a/notebooks/Journal_Names.pdf
+++ /dev/null
Binary files differ
diff --git a/notebooks/Journal_Names.zip b/notebooks/Journal_Names.zip
deleted file mode 100644
index 00e96a3..0000000
--- a/notebooks/Journal_Names.zip
+++ /dev/null
Binary files differ
diff --git a/notes/bm.md b/notes/bm.md
deleted file mode 100644
index b6c3a7c..0000000
--- a/notes/bm.md
+++ /dev/null
@@ -1,19 +0,0 @@
-# b/m
-
-## cluster, verify
-
-* git pull deploy, aitio
-* cluster example
-* test with
-
-## regatedl match results
-
-* https://git.archive.org/martin/regatedl, in fixtures: https://git.archive.org/martin/regatedl/-/tree/master/fixtures
-
-## the temp data structure
-
-* should go in ~/.cache/...
-* sqlite; TSV
-
-## tigris ideas
-
diff --git a/notes/clustering.md b/notes/clustering.md
deleted file mode 100644
index 3f6312c..0000000
--- a/notes/clustering.md
+++ /dev/null
@@ -1,102 +0,0 @@
-# Clustering
-
-Original dataset:
-
-```
-$ sha1sum release_export_expanded.json.zst
-fa7ce335e27bbf6ccee227992ecd9b860e8e36af release_export_expanded.json.zst
-
-$ zstdcat -T0 release_export_expanded.json.zst | wc -l
-```
-
-Various clusters (title, title normalized, title nysiis (New York State
-Identification and Intelligence System, ...):
-
-```
-$ zstdcat -T0 release_export_expanded.json.zst | fuzzycat-cluster -t title > cluster_title.json
-```
-
-Parallel (TODO: use `--pipepart`):
-
-```
-$ zstdcat -T0 release_export_expanded.json.zst | \
- parallel --tmpdir /bigger/tmp --roundrobin --pipe -j 16 \
- fuzzycat-cluster --tmpdir /bigger/tmp -t title > cluster_title.json
-```
-
-Numbers of clusters:
-
-```
- 141022216 cluster_title.json
- 134709771 cluster_title_normalized.json
- 119829458 cluster_title_nysiis.json
-```
-
-The number of duplicate record goes up as number of clusters go down:
-
-```
- 2858088 cluster_title_dups.json
- 5818143 cluster_title_normalized_dups.json
- 6274940 cluster_title_nysiis_dups.json
-```
-
-# Cluster numbers
-
-Using normalized title as example:
-
-* 4306860 have cluster size 2, 1511283 have cluster size 3 or larger
-
-```
- size len
-count 5818143.000 5818143.000
-mean 4.350 52.120
-std 196.347 35.026
-min 2.000 0.000
-25% 2.000 24.000
-50% 2.000 46.000
-75% 3.000 72.000
-max 151383.000 11686.000
-```
-
-Around 448170 clusters with size 5 or more (with some example titles):
-
-```
-Medical Notes
-日本鉄鋼協会第97回講演大会講演概要
-Boutades
-Allergic Contact Dermatitis
-Comité international
-Incontinence
-Efficient Uncertainty Minimization for Fuzzy Spectral Clustering
-Early Intervention
-CURRENT READINGS IN NUCLEAR MEDICINE
-Nannocystis exedens
-```
-
-Grouping. API, hide.
-
-* gnu parallel; top, htop; how much; "chunks"; read one line; "pipeart";
- batching; "read from a file"; scan a file; "chunking"
-
-# TODO
-
-* [ ] do a SS like clustering, using title and author ngrams
-* [ ] cluster by doi without "vX" suffix
-
-# Verification
-
-* we only need to look at identified duplicates, which will be a few millions
-* we want fast access to all release JSON blob via ident, maybe do a
- "fuzzycat-cache" that copies relevant files into the fs, e.g.
-"~/.cache/fuzzycat/releases/d9/e4d4be49faafc750563351a126e7bafe29.json or via microblob (but http we do not need), or sqlite3 (https://www.sqlite.org/fasterthanfs.html)
-
-For verification we need to have the cached json blobs in some fast,
-thread-safe store. Estimated: 1K/s accesses, we still would need a few hours
-for a run.
-
-* [ ] find all ids we need, generate cache, maybe reduce number of fields
-* [ ] run verification on each cluster; generate a file of same format of
- "verified" clusters; take note the clustering and verification method
-
-Overall, we can combine various clustering and verification methods. We can
-also put together a list of maybe 100-200 test cases and evaluate methods.
diff --git a/notes/general.md b/notes/general.md
deleted file mode 100644
index 03f6ec4..0000000
--- a/notes/general.md
+++ /dev/null
@@ -1,197 +0,0 @@
-# fuzzycat (wip)
-
-Fuzzy matching publications for [fatcat](https://fatcat.wiki).
-
-* [fuzzycat](https://pypi.org/project/fuzzycat/)
-
-Note: This is currently work-in-progress.
-
-## Motivation
-
-Most of the results on sites like [Google
-Scholar](https://scholar.google.com/scholar?q=fuzzy+matching) group
-publications into clusters. Each cluster represents one publication, abstracted
-from its concrete representation as a link to a PDF.
-
-We call the abstract publication
-[work](https://guide.fatcat.wiki/entity_work.html) and the concrete instance a
-[release](https://guide.fatcat.wiki/entity_release.html). One goal is to group
-releases under works and to implement a versions feature (self-match). Another
-goal is to have support for matching of external lists (e.g. title lists or
-other document) to the existing records.
-
-This repository contains both generic code for matching as well as fatcat
-specific code using the fatcat openapi client.
-
-## Running and Deployment
-
-We defer more packaging polish until the code stabilizes a bit more. For now:
-
-```
-$ git clone git@github.com:miku/fuzzycat.git && cd fuzzycat
-$ pipenv install --deploy
-$ pipenv run python -m fuzzycat.main
-```
-
-For the future, an independent [pex](https://github.com/pantsbuild/pex) or
-[shiv](https://github.com/linkedin/shiv) executable would be a convenient
-option to allow execution from any directory.
-
-## Datasets
-
-A few relevant datasets are:
-
-* release and container metadata from a bulk fatcat export, e.g.
- [https://archive.org/details/fatcat_bulk_exports_2020-08-05](https://archive.org/details/fatcat_bulk_exports_2020-08-05)
-* issn journal level data, via [issnlister](https://github.com/miku/issnlister)
-* journal abbreviation lists
-
-## Matching approaches
-
-![](static/approach.png)
-
-## Performance data points
-
-### Against elasticsearch
-
-Candidate generation via elasticsearch, 40 parallel queries, sustained speed at
-about 17857 queries per hour, that is around 5 queries/s.
-
-```
-$ time cat ~/data/researchgate/x04 | \
- parallel -j40 --pipe -N 1 ./fatcatx_rg_unmatched.py - \
- > ~/data/researchgate/x04_results.ndj
-...
-real 3409m16.442s
-user 29177m5.516s
-sys 4927m3.277s
-```
-
-### Without a search index
-
-Candidate grouping for self-match can be done locally by extracting a key per
-document, then a group by (via sort and uniq). Clustering 150M docs took about
-607min (around 4k docs/s, no verification step).
-
-## Data issues
-
-### A republished article
-
-* [https://fatcat.wiki/release/search?q=%22The+doctor+with+seven+billion+patients%22](https://fatcat.wiki/release/search?q=%22The+doctor+with+seven+billion+patients%22)
-
-There is "student BMJ" and "BMJ" - this (html) article (interview) has been
-first published on "sbmj" (Published 07 July 2011), then "bmj" (Published 10
-August 2011).
-
-> Notes; Originally published as: Student BMJ 2011;19:d3983
-
-* https://www.bmj.com/content/343/sbmj.d3983
-* https://www.bmj.com/content/343/bmj.d4964
-
-It is essentially the same text, same title, author, just different DOI and
-probably a different recorded date.
-
-Generic pattern "republication" duplicate:
-
-* metadata mostly same, except date and doi
-
-### Common title
-
-Probably a few thousand very common short titles.
-
-* [https://fatcat.wiki/release/search?q=%22Book+Reviews%22](https://fatcat.wiki/release/search?q=%22Book+Reviews%22) (238852)
-
-Some authors do this regularly:
-
-* [https://fatcat.wiki/release/search?q=%22Book+Reviews%22+%22william%22+%22michael%22](https://fatcat.wiki/release/search?q=%22Book+Reviews%22+%22william%22+%22michael%22) (398)
-
-Different DOI, so we know it is different.
-
-More examples:
-
-* [https://fatcat.wiki/release/search?q=%22errata%22](https://fatcat.wiki/release/search?q=%22errata%22) (37680)
-* [https://fatcat.wiki/release/search?q=%22Einleitung%22](https://fatcat.wiki/release/search?q=%22Einleitung%22) (68005)
-* [https://fatcat.wiki/release/search?q=%22Notes%22](https://fatcat.wiki/release/search?q=%22Notes%22) (1507705)
-* [https://fatcat.wiki/release/search?q=%22Letters+to+the+Editor%22](https://fatcat.wiki/release/search?q=%22Letters+to+the+Editor%22) (30976)
-
-### Title with extra data
-
-* like ISBN, ISSN, price and all kind of extra metadata
-* [https://fatcat.wiki/release/search?q=title%3A%22ISBN%22](https://fatcat.wiki/release/search?q=title%3A%22ISBN%22)
-* titles typically get longer: [https://fatcat.wiki/release/olxswrilxfci3ibb3bg5xhstr4](https://fatcat.wiki/release/olxswrilxfci3ibb3bg5xhstr4)
-* some of these are actually "reviews", e.g. [https://fatcat.wiki/release/4blc5mfc5bfaxkofuletqxuzp4](https://fatcat.wiki/release/4blc5mfc5bfaxkofuletqxuzp4)
-
-Another example:
-
-* too [long](https://fatcat.wiki/release/hewmq4afvnew7pwttvulzguubu), original suggested citation seems to be:
-
-> Parker, S. and Kerrod, R. (2002), "Children’s) Space Busters (1st) Looking at Stars (2nd)", Reference Reviews, Vol. 16 No. 5, pp. 26-27. https://doi.org/10.1108/rr.2002.16.5.26.252
-
-### Sometimes a title will be ambiguous
-
-For example given a title "Shakespeare in Tokyo" we would have to always return "ambiguous", as there are at least two separate publication with that name:
-
-* [https://fatcat.wiki/release/search?q=%22Shakespeare+in+Tokyo%22](https://fatcat.wiki/release/search?q=%22Shakespeare+in+Tokyo%22)
-
-This is similar to journal names, where some journal names will always be ambiguous.
-
-### Versions
-
-* same title, same authors, "vX" doi
-* [https://fatcat.wiki/release/search?q=%22Self-similarity+analysis+of+the+non-linear%22](https://fatcat.wiki/release/search?q=%22Self-similarity+analysis+of+the+non-linear%22)
-
-Sometimes, we have a couple of preprint versions, plus a published version (with a slightly different title):
-
-* [https://fatcat.wiki/release/search?q=%22Time-periodic+solutions+of+massive%22](https://fatcat.wiki/release/search?q=%22Time-periodic+solutions+of+massive%22)
-
-### Almost same
-
-* same author, maybe year
-* different DOI
-* title almost the same, e.g. [MassIVE MSV000085583 - Aedes aegypti protein profile and proteome analysis](https://fatcat.wiki/release/search?q=%22Aedes+aegypti+protein+profile+and+proteome+analysis%22)
-
-### Duplication by different granularity
-
-* [https://fatcat.wiki/release/search?q=%22Volkshochschule+Leipzig%22](https://fatcat.wiki/release/search?q=%22Volkshochschule+Leipzig%22) (20308)
-* contains both yearly entries, as well as "DOI per page",
- [https://fatcat.wiki/release/r734v367nza4tl37j6d74rfqo4](https://fatcat.wiki/release/r734v367nza4tl37j6d74rfqo4);
-could group pages under "container" of yearly release?
-* We have [one container](https://github.com/internetarchive/fatcat/blob/4f80b87722d64f27c985f0040ea177269b6e028b/fatcat-openapi2.yml#L704-L709) per release, currently.
-
-### Partial titles
-
-A metadata title might differ from the full title.
-
-* [https://fatcat.wiki/release/search?q=%22Brain-derived+neurotrophic+factor%22](https://fatcat.wiki/release/search?q=%22Brain-derived+neurotrophic+factor%22)
-
-Here, the [release](https://fatcat.wiki/release/2vi655gcejffhnzzbkkcnjpscm) points to two PDFs, one is an article, the other a weekly report (summary).
-
-### Exact duplicates
-
-* [https://fatcat.wiki/release/search?q=%22WEIGHTED+LIPSCHITZ+ESTIMATES+FOR+COMMUTATORS+ON+WEIGHTED+MORREY-HERZ+SPACES%22](https://fatcat.wiki/release/search?q=%22WEIGHTED+LIPSCHITZ+ESTIMATES+FOR+COMMUTATORS+ON+WEIGHTED+MORREY-HERZ+SPACES%22)
-
-### Difference in Subtitle (invisible)
-
-Subtitle is not visible metadata, all same, except for the DOI and the page number. Different.
-
-* [https://fatcat.wiki/release/search?q=%22Slip+in+tungsten+monocarbide%22](https://fatcat.wiki/release/search?q=%22Slip+in+tungsten+monocarbide%22)
-
-### The "what a difference a char makes" case
-
-Typically a yearly report, or "part 1", "part 2", like this:
-
-* [https://fatcat.wiki/release/search?q=%22The+Use+of+Bone+Age+in+Clinical+Practice+%22](https://fatcat.wiki/release/search?q=%22The+Use+of+Bone+Age+in+Clinical+Practice+%22)
-
-DOI differs and could hard code some patterns.
-
-### Published to two sites
-
-An article can have multiple DOI, e.g. when republished by a site that gives out DOI, e.g. researchgate. Example:
-
-* [Effect of Chlorophyll and Anthocyanin on the Secondary Bonds of Poly Vinyl Chloride](https://fatcat.wiki/release/search?q=%22Effect+of+Chlorophyll+and+Anthocyanin+on+the+Secondary+Bonds+of+Poly+Vinyl+Chloride+%22)
-
-> https://doi.org/10.11648/j.ijmsa.s.2015040201.15, https://doi.org/10.13140/rg.2.1.2398.3606
-
-Probably many "10.13140" prefixed DOI has at least another DOI.
-
-Some might be "rg-only", like this: [https://fatcat.wiki/release/search?q=%22Marco+de+trabajo+basado+en+los+datos+enlazados+para%22](https://fatcat.wiki/release/search?q=%22Marco+de+trabajo+basado+en+los+datos+enlazados+para%22)
diff --git a/notes/todo.md b/notes/todo.md
deleted file mode 100644
index 2c548b0..0000000
--- a/notes/todo.md
+++ /dev/null
@@ -1,23 +0,0 @@
-# Todo
-
-## Releases
-
-* [ ] stats of cases: versions, exact title matches; common prefixes (e.g. "XYZ Report 20XX", ...)
-
-## Containers
-
-* [ ] create notebook on duplicates
-* [ ] static mapping, that is efficient to store, maybe via: https://github.com/pytries/marisa-trie
-
-If matching only by name, we need to lookup a (exact) name.
-
-* need a mapping from "name" and "name variants" to journal "issnl"
-
-## Bulk
-
-* [ ] download export
-
-## Performance
-
-* provide some fast path
-
diff --git a/notes/workflow.md b/notes/workflow.md
deleted file mode 100644
index 8cdd817..0000000
--- a/notes/workflow.md
+++ /dev/null
@@ -1,60 +0,0 @@
-# Workflow
-
-Separate problem in half, first find clusters, then examine clusters (as
-proposed).
-
-## Finding clusters
-
-* group by raw exact title
-* group by lowercase title
-* group by slug title
-* group by ngram title and authors
-* group by ngram title (prefix, suffix) and authors
-* group by elasticsearch
-* group by doi without vX prefix
-* group by soundex
-* group by a simhash over the record
-
-As for performance, the feature needs to be calculated in one pass, then the
-grouping reduces to a sort, in a second pass.
-
-The output could be a TSV file, with method and then release identifiers.
-
-```
-rawt o3utonw5qzhddo7l4lmwptgeey nnpmnwln7be2zb5hd2qanq3r7q
-```
-
-Or jsonlines for a bit of structure (e.g. method, ids)
-
-```
-{"m": "rawt", "c": ["o3utonw5qzhddo7l4lmwptgeey", "nnpmnwln7be2zb5hd2qanq3r7q"]}
-```
-
-```
-$ zstdcat -T0 release_export_expanded.json.zst | fuzzycat-cluster -g > clusters.json
-```
-
-### Performance considerations
-
-* [orjson](https://github.com/ijl/orjson), [pysimdjson](https://github.com/TkTech/pysimdjson)
-
-## Format
-
-Options:
-
-* emit minimal cluster information, e.g. method description and actual identifiers
-* emit methods, and for each cluster item some core fields (title, author, id, date)
-
-## Examine cluster
-
-There will be various methods by which to examine the cluster as well.
-
-We need to fetch releases by identifier (API, but use "hide"), this can be the
-full record or some partial record that has been cached somewhere.
-
-The input is then a list of releases and the output would be a equally sized or
-smaller cluster of releases which we assume represent the same record.
-
-Apart from that, there may be different relations, e.g. not the exact same
-thing, but something, that has an interval to it, like some thing that mostly
-differs in year?
diff --git a/pyproject.toml b/pyproject.toml
deleted file mode 100644
index b0471b7..0000000
--- a/pyproject.toml
+++ /dev/null
@@ -1,3 +0,0 @@
-[build-system]
-requires = ["setuptools", "wheel"]
-build-backend = "setuptools.build_meta:__legacy__" \ No newline at end of file
diff --git a/setup.py b/setup.py
deleted file mode 100644
index 7a39369..0000000
--- a/setup.py
+++ /dev/null
@@ -1,50 +0,0 @@
-import setuptools
-
-from fuzzycat import __version__
-
-with open("README.md", "r") as fh:
- long_description = fh.read()
-
- setuptools.setup(
- name="fuzzycat",
- version=__version__,
- author="Martin Czygan",
- author_email="martin@archive.org",
- description="Fuzzy matching utilities for scholarly metadata",
- long_description=long_description,
- long_description_content_type="text/markdown",
- url="https://github.com/miku/fuzzycat",
- packages=setuptools.find_packages(),
- classifiers=[
- "Programming Language :: Python :: 3",
- "License :: OSI Approved :: MIT License",
- "Operating System :: OS Independent",
- ],
- python_requires=">=3.5",
- zip_safe=False,
- entry_points={"console_scripts": [
- "fuzzycat=fuzzycat.main:main"
- ]},
- install_requires=[
- "elasticsearch>=7",
- "ftfy",
- "fuzzy",
- "pydantic",
- "toml",
- "unidecode>=0.10",
- # "fatcat-openapi-client",
- # "simhash",
- ],
- extras_require={"dev": [
- "ipython",
- "isort",
- "jupyter",
- "matplotlib",
- "pandas",
- "pylint",
- "pytest",
- "pytest-cov",
- "twine",
- "yapf",
- ],},
- )