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surveys/surveys/index.html
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@ -1013,6 +1013,7 @@ span.linenos.special { color: #000000; background-color: #ffffc0; padding-left:
.highlight-ipynb .m { color: var(--jp-mirror-editor-number-color) } /* Literal.Number */
.highlight-ipynb .s { color: var(--jp-mirror-editor-string-color) } /* Literal.String */
.highlight-ipynb .ow { color: var(--jp-mirror-editor-operator-color); font-weight: bold } /* Operator.Word */
.highlight-ipynb .pm { color: var(--jp-mirror-editor-punctuation-color) } /* Punctuation.Marker */
.highlight-ipynb .w { color: var(--jp-mirror-editor-variable-color) } /* Text.Whitespace */
.highlight-ipynb .mb { color: var(--jp-mirror-editor-number-color) } /* Literal.Number.Bin */
.highlight-ipynb .mf { color: var(--jp-mirror-editor-number-color) } /* Literal.Number.Float */
@ -2394,6 +2395,8 @@ jp-needs-light-background
<span class="n">X</span> <span class="o">=</span> <span class="p">[</span><span class="n">x</span> <span class="k">for</span> <span class="n">x</span><span class="p">,</span> <span class="n">y</span> <span class="ow">in</span> <span class="n">best_practice_score_se</span><span class="p">]</span>
<span class="n">Y</span> <span class="o">=</span> <span class="p">[</span><span class="n">y</span> <span class="k">for</span> <span class="n">x</span><span class="p">,</span> <span class="n">y</span> <span class="ow">in</span> <span class="n">best_practice_score_se</span><span class="p">]</span>
<span class="nb">print</span><span class="p">(</span><span class="nb">sum</span><span class="p">(</span><span class="n">Y</span><span class="p">)</span> <span class="o">/</span> <span class="nb">len</span><span class="p">(</span><span class="n">Y</span><span class="p">))</span>
<span class="n">sc</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">scatter</span><span class="p">(</span><span class="n">X</span><span class="p">,</span> <span class="n">Y</span><span class="p">,</span> <span class="n">c</span><span class="o">=</span><span class="s2">&quot;black&quot;</span><span class="p">,</span> <span class="n">s</span><span class="o">=</span><span class="p">[</span><span class="n">x</span> <span class="o">*</span> <span class="mi">50</span> <span class="k">for</span> <span class="n">x</span><span class="p">,</span> <span class="n">y</span> <span class="ow">in</span> <span class="n">best_practice_score_ds</span><span class="p">])</span>
<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s2">&quot;Ratio of implemented deployment best practices&quot;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s2">&quot;Years of professional software engineering experience&quot;</span><span class="p">)</span>
@ -2441,6 +2444,8 @@ plt.rcParams["figure.figsize"] = (14, 10)
X = [x for x, y in best_practice_score_se]
Y = [y for x, y in best_practice_score_se]
print(sum(Y) / len(Y))
sc = plt.scatter(X, Y, c="black", s=[x * 50 for x, y in best_practice_score_ds])
plt.ylabel("Ratio of implemented deployment best practices")
plt.xlabel("Years of professional software engineering experience")
@ -2490,6 +2495,18 @@ stats.pearsonr(
<div class="jp-OutputArea jp-Cell-outputArea">
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<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="text/plain">
<pre>0.5157738095238095
</pre>
</div>
</div>
<div class="jp-OutputArea-child">
@ -3123,9 +3140,9 @@ tam[["pu", "peou", "itu"]]</div>
</div>
</clipboard-copy>
</div>
<div class="highlight-ipynb hl-python"><pre><span></span><span class="n">stats</span><span class="o">.</span><span class="n">pearsonr</span><span class="p">(</span><span class="n">tam</span><span class="p">[</span><span class="s2">&quot;peou&quot;</span><span class="p">],</span> <span class="n">tam</span><span class="p">[</span><span class="s2">&quot;pu&quot;</span><span class="p">])</span>
<div class="highlight-ipynb hl-python"><pre><span></span><span class="n">tam</span><span class="p">[[</span><span class="s2">&quot;pu&quot;</span><span class="p">,</span> <span class="s2">&quot;peou&quot;</span><span class="p">,</span> <span class="s2">&quot;itu&quot;</span><span class="p">]]</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span>
</pre></div>
<div id="cell-10" class="clipboard-copy-txt">stats.pearsonr(tam["peou"], tam["pu"])</div>
<div id="cell-10" class="clipboard-copy-txt">tam[["pu", "peou", "itu"]].mean()</div>
</div>
</div>
@ -3149,7 +3166,10 @@ tam[["pu", "peou", "itu"]]</div>
<div class="jp-RenderedText jp-OutputArea-output jp-OutputArea-executeResult" data-mime-type="text/plain">
<pre>(0.5515422017785757, 0.09838124227663879)</pre>
<pre>pu 6.125
peou 5.450
itu 5.950
dtype: float64</pre>
</div>
</div>
@ -3180,9 +3200,9 @@ tam[["pu", "peou", "itu"]]</div>
</div>
</clipboard-copy>
</div>
<div class="highlight-ipynb hl-python"><pre><span></span><span class="n">stats</span><span class="o">.</span><span class="n">pearsonr</span><span class="p">(</span><span class="n">tam</span><span class="p">[</span><span class="s2">&quot;peou&quot;</span><span class="p">],</span> <span class="n">tam</span><span class="p">[</span><span class="s2">&quot;itu&quot;</span><span class="p">])</span>
<div class="highlight-ipynb hl-python"><pre><span></span><span class="n">tam</span><span class="p">[[</span><span class="s2">&quot;pu&quot;</span><span class="p">,</span> <span class="s2">&quot;peou&quot;</span><span class="p">,</span> <span class="s2">&quot;itu&quot;</span><span class="p">]]</span><span class="o">.</span><span class="n">median</span><span class="p">()</span>
</pre></div>
<div id="cell-11" class="clipboard-copy-txt">stats.pearsonr(tam["peou"], tam["itu"])</div>
<div id="cell-11" class="clipboard-copy-txt">tam[["pu", "peou", "itu"]].median()</div>
</div>
</div>
@ -3206,7 +3226,10 @@ tam[["pu", "peou", "itu"]]</div>
<div class="jp-RenderedText jp-OutputArea-output jp-OutputArea-executeResult" data-mime-type="text/plain">
<pre>(0.8066270322592023, 0.004809023073123024)</pre>
<pre>pu 6.375
peou 5.750
itu 6.250
dtype: float64</pre>
</div>
</div>
@ -3237,9 +3260,9 @@ tam[["pu", "peou", "itu"]]</div>
</div>
</clipboard-copy>
</div>
<div class="highlight-ipynb hl-python"><pre><span></span><span class="n">stats</span><span class="o">.</span><span class="n">pearsonr</span><span class="p">(</span><span class="n">tam</span><span class="p">[</span><span class="s2">&quot;pu&quot;</span><span class="p">],</span> <span class="n">tam</span><span class="p">[</span><span class="s2">&quot;itu&quot;</span><span class="p">])</span>
<div class="highlight-ipynb hl-python"><pre><span></span><span class="n">tam</span><span class="p">[[</span><span class="s2">&quot;pu&quot;</span><span class="p">,</span> <span class="s2">&quot;peou&quot;</span><span class="p">,</span> <span class="s2">&quot;itu&quot;</span><span class="p">]]</span><span class="o">.</span><span class="n">std</span><span class="p">()</span>
</pre></div>
<div id="cell-12" class="clipboard-copy-txt">stats.pearsonr(tam["pu"], tam["itu"])</div>
<div id="cell-12" class="clipboard-copy-txt">tam[["pu", "peou", "itu"]].std()</div>
</div>
</div>
@ -3262,6 +3285,180 @@ tam[["pu", "peou", "itu"]]</div>
<div class="jp-RenderedText jp-OutputArea-output jp-OutputArea-executeResult" data-mime-type="text/plain">
<pre>pu 0.859990
peou 1.039498
itu 1.321825
dtype: float64</pre>
</div>
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<path fill="currentColor" fill-rule="evenodd" d="M0 6.75C0 5.784.784 5 1.75 5h1.5a.75.75 0 010 1.5h-1.5a.25.25 0 00-.25.25v7.5c0 .138.112.25.25.25h7.5a.25.25 0 00.25-.25v-1.5a.75.75 0 011.5 0v1.5A1.75 1.75 0 019.25 16h-7.5A1.75 1.75 0 010 14.25v-7.5z"></path>
<path fill="currentColor" fill-rule="evenodd" d="M5 1.75C5 .784 5.784 0 6.75 0h7.5C15.216 0 16 .784 16 1.75v7.5A1.75 1.75 0 0114.25 11h-7.5A1.75 1.75 0 015 9.25v-7.5zm1.75-.25a.25.25 0 00-.25.25v7.5c0 .138.112.25.25.25h7.5a.25.25 0 00.25-.25v-7.5a.25.25 0 00-.25-.25h-7.5z"></path>
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<div class="highlight-ipynb hl-python"><pre><span></span><span class="n">stats</span><span class="o">.</span><span class="n">pearsonr</span><span class="p">(</span><span class="n">tam</span><span class="p">[</span><span class="s2">&quot;peou&quot;</span><span class="p">],</span> <span class="n">tam</span><span class="p">[</span><span class="s2">&quot;pu&quot;</span><span class="p">])</span>
</pre></div>
<div id="cell-13" class="clipboard-copy-txt">stats.pearsonr(tam["peou"], tam["pu"])</div>
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<div class="jp-OutputPrompt jp-OutputArea-prompt">Out[13]:</div>
<div class="jp-RenderedText jp-OutputArea-output jp-OutputArea-executeResult" data-mime-type="text/plain">
<pre>(0.5515422017785757, 0.09838124227663879)</pre>
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<div class="jp-InputPrompt jp-InputArea-prompt">In&nbsp;[14]:</div><div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline">
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<path fill="currentColor" fill-rule="evenodd" d="M0 6.75C0 5.784.784 5 1.75 5h1.5a.75.75 0 010 1.5h-1.5a.25.25 0 00-.25.25v7.5c0 .138.112.25.25.25h7.5a.25.25 0 00.25-.25v-1.5a.75.75 0 011.5 0v1.5A1.75 1.75 0 019.25 16h-7.5A1.75 1.75 0 010 14.25v-7.5z"></path>
<path fill="currentColor" fill-rule="evenodd" d="M5 1.75C5 .784 5.784 0 6.75 0h7.5C15.216 0 16 .784 16 1.75v7.5A1.75 1.75 0 0114.25 11h-7.5A1.75 1.75 0 015 9.25v-7.5zm1.75-.25a.25.25 0 00-.25.25v7.5c0 .138.112.25.25.25h7.5a.25.25 0 00.25-.25v-7.5a.25.25 0 00-.25-.25h-7.5z"></path>
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<div class="highlight-ipynb hl-python"><pre><span></span><span class="n">stats</span><span class="o">.</span><span class="n">pearsonr</span><span class="p">(</span><span class="n">tam</span><span class="p">[</span><span class="s2">&quot;peou&quot;</span><span class="p">],</span> <span class="n">tam</span><span class="p">[</span><span class="s2">&quot;itu&quot;</span><span class="p">])</span>
</pre></div>
<div id="cell-14" class="clipboard-copy-txt">stats.pearsonr(tam["peou"], tam["itu"])</div>
</div>
</div>
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<div class="jp-Collapser jp-OutputCollapser jp-Cell-outputCollapser">
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<div class="jp-OutputPrompt jp-OutputArea-prompt">Out[14]:</div>
<div class="jp-RenderedText jp-OutputArea-output jp-OutputArea-executeResult" data-mime-type="text/plain">
<pre>(0.8066270322592023, 0.004809023073123024)</pre>
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<div class="jp-InputPrompt jp-InputArea-prompt">In&nbsp;[15]:</div><div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline">
<div class="CodeMirror cm-s-jupyter">
<div class="zeroclipboard-container">
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<span class="notice" hidden>Copied!</span>
<svg aria-hidden="true" width="20" height="20" viewBox="0 0 16 16" version="1.1" data-view-component="true" class="clipboard-copy-icon">
<path fill="currentColor" fill-rule="evenodd" d="M0 6.75C0 5.784.784 5 1.75 5h1.5a.75.75 0 010 1.5h-1.5a.25.25 0 00-.25.25v7.5c0 .138.112.25.25.25h7.5a.25.25 0 00.25-.25v-1.5a.75.75 0 011.5 0v1.5A1.75 1.75 0 019.25 16h-7.5A1.75 1.75 0 010 14.25v-7.5z"></path>
<path fill="currentColor" fill-rule="evenodd" d="M5 1.75C5 .784 5.784 0 6.75 0h7.5C15.216 0 16 .784 16 1.75v7.5A1.75 1.75 0 0114.25 11h-7.5A1.75 1.75 0 015 9.25v-7.5zm1.75-.25a.25.25 0 00-.25.25v7.5c0 .138.112.25.25.25h7.5a.25.25 0 00.25-.25v-7.5a.25.25 0 00-.25-.25h-7.5z"></path>
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<div class="highlight-ipynb hl-python"><pre><span></span><span class="n">stats</span><span class="o">.</span><span class="n">pearsonr</span><span class="p">(</span><span class="n">tam</span><span class="p">[</span><span class="s2">&quot;pu&quot;</span><span class="p">],</span> <span class="n">tam</span><span class="p">[</span><span class="s2">&quot;itu&quot;</span><span class="p">])</span>
</pre></div>
<div id="cell-15" class="clipboard-copy-txt">stats.pearsonr(tam["pu"], tam["itu"])</div>
</div>
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<div class="jp-Collapser jp-OutputCollapser jp-Cell-outputCollapser">
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<div class="jp-OutputPrompt jp-OutputArea-prompt">Out[15]:</div>
<div class="jp-RenderedText jp-OutputArea-output jp-OutputArea-executeResult" data-mime-type="text/plain">
<pre>(0.7880605510627579, 0.006774486564715021)</pre>
</div>
@ -3283,7 +3480,7 @@ tam[["pu", "peou", "itu"]]</div>
<small>
Last update:
<span class="git-revision-date-localized-plugin git-revision-date-localized-plugin-date">August 13, 2022</span>
<span class="git-revision-date-localized-plugin git-revision-date-localized-plugin-date">August 19, 2022</span>
</small>

88
surveys/surveys/surveys.ipynb
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@ -553,6 +553,13 @@
"execution_count": 4,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"0.5157738095238095\n"
]
},
{
"data": {
"text/plain": [
@ -586,6 +593,8 @@
"\n",
"X = [x for x, y in best_practice_score_se]\n",
"Y = [y for x, y in best_practice_score_se]\n",
"\n",
"print(sum(Y) / len(Y))\n",
"sc = plt.scatter(X, Y, c=\"black\", s=[x * 50 for x, y in best_practice_score_ds])\n",
"plt.ylabel(\"Ratio of implemented deployment best practices\")\n",
"plt.xlabel(\"Years of professional software engineering experience\")\n",
@ -1136,7 +1145,10 @@
{
"data": {
"text/plain": [
"(0.5515422017785757, 0.09838124227663879)"
"pu 6.125\n",
"peou 5.450\n",
"itu 5.950\n",
"dtype: float64"
]
},
"execution_count": 10,
@ -1145,7 +1157,7 @@
}
],
"source": [
"stats.pearsonr(tam[\"peou\"], tam[\"pu\"])"
"tam[[\"pu\", \"peou\", \"itu\"]].mean()"
]
},
{
@ -1156,7 +1168,10 @@
{
"data": {
"text/plain": [
"(0.8066270322592023, 0.004809023073123024)"
"pu 6.375\n",
"peou 5.750\n",
"itu 6.250\n",
"dtype: float64"
]
},
"execution_count": 11,
@ -1165,7 +1180,7 @@
}
],
"source": [
"stats.pearsonr(tam[\"peou\"], tam[\"itu\"])"
"tam[[\"pu\", \"peou\", \"itu\"]].median()"
]
},
{
@ -1176,7 +1191,10 @@
{
"data": {
"text/plain": [
"(0.7880605510627579, 0.006774486564715021)"
"pu 0.859990\n",
"peou 1.039498\n",
"itu 1.321825\n",
"dtype: float64"
]
},
"execution_count": 12,
@ -1184,6 +1202,66 @@
"output_type": "execute_result"
}
],
"source": [
"tam[[\"pu\", \"peou\", \"itu\"]].std()"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(0.5515422017785757, 0.09838124227663879)"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"stats.pearsonr(tam[\"peou\"], tam[\"pu\"])"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(0.8066270322592023, 0.004809023073123024)"
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"stats.pearsonr(tam[\"peou\"], tam[\"itu\"])"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(0.7880605510627579, 0.006774486564715021)"
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"stats.pearsonr(tam[\"pu\"], tam[\"itu\"])"
]