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aeturrell committed Sep 7, 2023
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141 changes: 13 additions & 128 deletions _sources/auto-research-outputs.ipynb
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"cells": [
{
"cell_type": "markdown",
"id": "9022538b",
"id": "11227fbd",
"metadata": {},
"source": [
"(auto-research-outputs)=\n",
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},
{
"cell_type": "code",
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{
"data": {
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"<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>time</th>\n",
" <th>Lunch</th>\n",
" <th>Dinner</th>\n",
" </tr>\n",
" <tr>\n",
" <th>smoker</th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>Yes</th>\n",
" <td>2.83</td>\n",
" <td>3.07</td>\n",
" </tr>\n",
" <tr>\n",
" <th>No</th>\n",
" <td>2.67</td>\n",
" <td>3.13</td>\n",
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"time Lunch Dinner\n",
"smoker \n",
"Yes 2.83 3.07\n",
"No 2.67 3.13"
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"source": [
"import seaborn as sns\n",
"import pandas as pd\n",
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},
{
"cell_type": "markdown",
"id": "cf830321",
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"This can be turned into a $\\LaTeX$ table using the following command"
]
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"'\\\\begin{table}\\n\\\\caption{A Table}\\n\\\\label{tab:descriptive}\\n\\\\begin{tabular}{lrr}\\n\\\\toprule\\ntime & Lunch & Dinner \\\\\\\\\\nsmoker & & \\\\\\\\\\n\\\\midrule\\nYes & 2.830000 & 3.070000 \\\\\\\\\\nNo & 2.670000 & 3.130000 \\\\\\\\\\n\\\\bottomrule\\n\\\\end{tabular}\\n\\\\end{table}\\n'"
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"table.to_latex(caption='A Table', label='tab:descriptive')"
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"Or perhaps you have a regression table, for example"
]
},
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"<table style=\"text-align:center\"><tr><td colspan=\"3\" style=\"border-bottom: 1px solid black\"></td></tr>\n",
"<tr><td style=\"text-align:left\"></td><td colspan=\"2\"><em>Dependent variable: target</em></td></tr><tr><td style=\"text-align:left\"></td><tr><td style=\"text-align:left\"></td><td>(1)</td><td>(2)</td></tr>\n",
"<tr><td colspan=\"3\" style=\"border-bottom: 1px solid black\"></td></tr>\n",
"\n",
"<tr><td style=\"text-align:left\">ABP</td><td>416.673<sup>***</sup></td><td>397.581<sup>***</sup></td></tr>\n",
"<tr><td style=\"text-align:left\"></td><td>(69.495)</td><td>(70.870)</td></tr>\n",
"<tr><td style=\"text-align:left\">Age</td><td>37.241<sup></sup></td><td>24.703<sup></sup></td></tr>\n",
"<tr><td style=\"text-align:left\"></td><td>(64.117)</td><td>(65.411)</td></tr>\n",
"<tr><td style=\"text-align:left\">BMI</td><td>787.182<sup>***</sup></td><td>789.744<sup>***</sup></td></tr>\n",
"<tr><td style=\"text-align:left\"></td><td>(65.424)</td><td>(66.887)</td></tr>\n",
"<tr><td style=\"text-align:left\">Intercept</td><td>152.133<sup>***</sup></td><td>152.133<sup>***</sup></td></tr>\n",
"<tr><td style=\"text-align:left\"></td><td>(2.853)</td><td>(2.853)</td></tr>\n",
"<tr><td style=\"text-align:left\">S1</td><td></td><td>197.848<sup></sup></td></tr>\n",
"<tr><td style=\"text-align:left\"></td><td></td><td>(143.812)</td></tr>\n",
"<tr><td style=\"text-align:left\">S2</td><td></td><td>-169.243<sup></sup></td></tr>\n",
"<tr><td style=\"text-align:left\"></td><td></td><td>(142.744)</td></tr>\n",
"<tr><td style=\"text-align:left\">Sex</td><td>-106.576<sup>*</sup></td><td>-82.862<sup></sup></td></tr>\n",
"<tr><td style=\"text-align:left\"></td><td>(62.125)</td><td>(64.851)</td></tr>\n",
"\n",
"<td colspan=\"3\" style=\"border-bottom: 1px solid black\"></td></tr>\n",
"<tr><td style=\"text-align: left\">Observations</td><td>442</td><td>442</td></tr><tr><td style=\"text-align: left\">R<sup>2</sup></td><td>0.400</td><td>0.403</td></tr><tr><td style=\"text-align: left\">Adjusted R<sup>2</sup></td><td>0.395</td><td>0.395</td></tr><tr><td style=\"text-align: left\">Residual Std. Error</td><td>59.976 (df=437)</td><td>59.982 (df=435)</td></tr><tr><td style=\"text-align: left\">F Statistic</td><td>72.913<sup>***</sup> (df=4; 437)</td><td>48.915<sup>***</sup> (df=6; 435)</td></tr>\n",
"<tr><td colspan=\"3\" style=\"border-bottom: 1px solid black\"></td></tr><tr><td style=\"text-align: left\">Note:</td><td colspan=\"2\" style=\"text-align: right\"><sup>*</sup>p&lt;0.1; <sup>**</sup>p&lt;0.05; <sup>***</sup>p&lt;0.01</td></tr></table>"
],
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"<stargazer.stargazer.Stargazer at 0x15443f910>"
]
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"source": [
"import pandas as pd\n",
"from sklearn import datasets\n",
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},
{
"cell_type": "markdown",
"id": "1f3049d2",
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"which can similarly be cast into $\\LaTeX$ using `reg_results.render_latex()`.\n",
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"language": "python",
"name": "python3"
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"name": "ipython",
"version": 3
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83,
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50 changes: 5 additions & 45 deletions _sources/code-best-practice.ipynb
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"cells": [
{
"cell_type": "markdown",
"id": "647ce369",
"id": "9cd4b31b",
"metadata": {},
"source": [
"(code-best-practice)=\n",
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},
{
"cell_type": "code",
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"text": [
"The Zen of Python, by Tim Peters\n",
"\n",
"Beautiful is better than ugly.\n",
"Explicit is better than implicit.\n",
"Simple is better than complex.\n",
"Complex is better than complicated.\n",
"Flat is better than nested.\n",
"Sparse is better than dense.\n",
"Readability counts.\n",
"Special cases aren't special enough to break the rules.\n",
"Although practicality beats purity.\n",
"Errors should never pass silently.\n",
"Unless explicitly silenced.\n",
"In the face of ambiguity, refuse the temptation to guess.\n",
"There should be one-- and preferably only one --obvious way to do it.\n",
"Although that way may not be obvious at first unless you're Dutch.\n",
"Now is better than never.\n",
"Although never is often better than *right* now.\n",
"If the implementation is hard to explain, it's a bad idea.\n",
"If the implementation is easy to explain, it may be a good idea.\n",
"Namespaces are one honking great idea -- let's do more of those!\n"
]
}
],
"outputs": [],
"source": [
"import this"
]
},
{
"cell_type": "markdown",
"id": "adb781b0",
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"metadata": {},
"source": [
"## Advanced Coding Tips\n",
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"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
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"file_extension": ".py",
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302,
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14 changes: 1 addition & 13 deletions _sources/coming-from-excel.ipynb
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"cells": [
{
"cell_type": "markdown",
"id": "11e1ec8b",
"id": "1ceac46b",
"metadata": {},
"source": [
"# Coming from Excel\n",
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"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
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"file_extension": ".py",
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"name": "python",
"nbconvert_exporter": "python",
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14
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2 changes: 1 addition & 1 deletion _sources/coming-from-matlab.ipynb
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"cells": [
{
"cell_type": "markdown",
"id": "8e73a53a",
"id": "19bf82da",
"metadata": {},
"source": [
"# Coming from Matlab\n",
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"cells": [
{
"cell_type": "markdown",
"id": "0b7eda21",
"id": "75261ece",
"metadata": {},
"source": [
"# Coming from R\n",
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"cells": [
{
"cell_type": "markdown",
"id": "e53a4c0e",
"id": "a198dacf",
"metadata": {},
"source": [
"# Coming from Stata\n",
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4 changes: 3 additions & 1 deletion _sources/craft-referee.ipynb
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"cells": [
{
"cell_type": "markdown",
"id": "2848c6f3",
"id": "146b20a2",
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"(craft-referee)=\n",
"# Writing Referee Reports\n",
"\n",
"In this chapter, you'll learn tips and tricks for writing referee reports. Much of this chapter is advisory: some of it might work for you, some of it might not. It's not intended to be a foolproof guide, or to cover everyone's preferences--but it is designed to help you get started on writing good referee reports.\n",
"\n",
"This chapter very much stands on the shoulders of giants. Those giants include [The Turing Way](https://the-turing-way.netlify.app/)'s [Guidance on Peer Review](https://the-turing-way.netlify.app/communication/peer-review/peer-review-guidance.html), {cite:ts}`nyhan2015checklist`, {cite:ts}`berk2017write`, {cite:ts}`nicholas2011quick`, Econometrica's [guidelines for referees](https://www.econometricsociety.org/publications/econometrica/guidelines-referees), Marc Bellemare's [20 Rules for Refereeing](http://marcfbellemare.com/wordpress/5542), Tyler Cowan's [how to be a good referee](https://marginalrevolution.com/marginalrevolution/2006/10/how_to_be_a_goo.html), and Tatyana Deryugina's [how to be a constructive referee](https://deryugina.com/how-to-be-a-constructive-referee/).\n",
"\n",
"What is the purpose of a referee report? We think there are two:\n",
"\n",
"1. to help the editor make a decision about whether to publish the paper in their journal\n",
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In this chapter, you'll learn tips and tricks for writing referee reports. Much of this chapter is advisory: some of it might work for you, some of it might not. It's not intended to be a foolproof guide, or to cover everyone's preferences--but it is designed to help you get started on writing good referee reports.

This chapter very much stands on the shoulders of giants. Those giants include [The Turing Way](https://the-turing-way.netlify.app/)'s [Guidance on Peer Review](https://the-turing-way.netlify.app/communication/peer-review/peer-review-guidance.html), {cite:ts}`nyhan2015checklist`, {cite:ts}`berk2017write`, {cite:ts}`nicholas2011quick`, Econometrica's [guidelines for referees](https://www.econometricsociety.org/publications/econometrica/guidelines-referees), Marc Bellemare's [20 Rules for Refereeing](http://marcfbellemare.com/wordpress/5542), Tyler Cowan's [how to be a good referee](https://marginalrevolution.com/marginalrevolution/2006/10/how_to_be_a_goo.html), and Tatyana Deryugina's [how to be a constructive referee](https://deryugina.com/how-to-be-a-constructive-referee/).

What is the purpose of a referee report? We think there are two:

1. to help the editor make a decision about whether to publish the paper in their journal
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33 changes: 5 additions & 28 deletions _sources/craft-research-blogs.ipynb
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