deploy: a0f2780

00_python/01_Python_Basics.html

@@ -445,7 +445,7 @@ <h2> Contents </h2>
 <h1>Introduction to Python in Jupyter Notebook/Google Colab<a class="headerlink" href="#introduction-to-python-in-jupyter-notebook-google-colab" title="Permalink to this heading">#</a></h1>
 <div class="cell docutils container">
 <div class="cell_input docutils container">
-<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="o">!</span>pip<span class="w"> </span>install<span class="w"> </span>-q<span class="w"> </span>-r<span class="w"> </span>requirements.txt
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="ch">#!pip install -q -r requirements.txt</span>
 </pre></div>
 </div>
 </div>
@@ -576,11 +576,11 @@ <h3>1.2.2.2 More Complicated Data Types<a class="headerlink" href="#more-complic
 <span class="nb">print</span><span class="p">(</span><span class="n">colors</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span>
 <span class="nb">print</span><span class="p">(</span><span class="n">colors</span><span class="p">[</span><span class="mi">2</span><span class="p">])</span>
 
-<span class="c1">#Notice here how the first element of the list is index 0, not 1! </span>
+<span class="c1">#Notice here how the first element of the list is index 0, not 1!</span>
 <span class="c1">#Languages like MATLAB are 1 indexed, be careful!</span>
 
 <span class="c1">#In addition to lists, there are tuples</span>
-<span class="c1">#Tuples behave very similarly to lists except that you can&#39;t change them </span>
+<span class="c1">#Tuples behave very similarly to lists except that you can&#39;t change them</span>
 <span class="c1"># after you make them</span>
 
 <span class="c1">#An empty Tuple isn&#39;t very useful:</span>
@@ -595,9 +595,9 @@ <h3>1.2.2.2 More Complicated Data Types<a class="headerlink" href="#more-complic
 <span class="c1">#You can access tuples just like lists</span>
 <span class="nb">print</span><span class="p">(</span><span class="n">rosa_parks_info</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">+</span> <span class="s2">&quot; &quot;</span> <span class="o">+</span> <span class="n">rosa_parks_info</span><span class="p">[</span><span class="mi">1</span><span class="p">])</span>
 
-<span class="c1"># You cannot modify existing tuples, but you can make new tuples that extend </span>
+<span class="c1"># You cannot modify existing tuples, but you can make new tuples that extend</span>
 <span class="c1"># the information.</span>
-<span class="c1"># I expect Tuples to come up less than lists. So we&#39;ll just leave it at that. </span>
+<span class="c1"># I expect Tuples to come up less than lists. So we&#39;ll just leave it at that.</span>
 </pre></div>
 </div>
 </div>
@@ -625,7 +625,7 @@ <h3>1.2.2.3 Using Variables<a class="headerlink" href="#using-variables" title="
 <span class="nb">print</span><span class="p">(</span><span class="n">float1</span> <span class="o">*</span> <span class="n">float2</span><span class="p">)</span>
 <span class="nb">print</span><span class="p">(</span><span class="n">float1</span> <span class="o">/</span> <span class="n">float2</span><span class="p">)</span>
 
-<span class="c1">#Here&#39;s an interesting one that showed up in the first homework in 2017. Modulus: </span>
+<span class="c1">#Here&#39;s an interesting one that showed up in the first homework in 2017. Modulus:</span>
 <span class="nb">print</span><span class="p">(</span><span class="mi">5</span> <span class="o">%</span> <span class="mi">2</span><span class="p">)</span>
 </pre></div>
 </div>
@@ -704,10 +704,10 @@ <h3>1.2.2.5 Loops in Python<a class="headerlink" href="#loops-in-python" title="
 <span class="k">while</span><span class="p">(</span><span class="n">i</span> <span class="o">&lt;</span> <span class="nb">len</span><span class="p">(</span><span class="n">fib</span><span class="p">)):</span>
     <span class="nb">print</span><span class="p">(</span><span class="n">fib</span><span class="p">[</span><span class="n">i</span><span class="p">])</span>
     <span class="n">i</span> <span class="o">=</span> <span class="n">i</span> <span class="o">+</span> <span class="mi">1</span>
-    
+
 <span class="c1">#In matlab, to do the same thing you would have the conditional as: counter &lt; (length(fib) + 1)</span>
 <span class="c1">#This is because matlab starts indexing at 1, and python starts at 0.</span>
-    
+
 <span class="c1">#The above type of loop is so common that the &#39;for&#39; loop is the way to write it faster.</span>
 
 <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Let&#39;s try that again&quot;</span><span class="p">)</span>

01_pandas_statistics/01_Pandas_Intro.html

@@ -425,7 +425,8 @@ <h2> Contents </h2>
 <div id="searchbox"></div>
                 <article class="bd-article" role="main">
 
-  <section class="tex2jax_ignore mathjax_ignore" id="introduction-to-pandas">
+  <p><img align="left" src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in Colab" title="Open in Google Colaboratory"></a><p><a href="https://githubtocolab.com/vmcf-konfmi/MB100T01/blob/main/advanced_image_analysis_mb100t01/01_pandas_statistics/01_Pandas_Intro.ipynb"></p>
+<section class="tex2jax_ignore mathjax_ignore" id="introduction-to-pandas">
 <h1>Introduction to Pandas<a class="headerlink" href="#introduction-to-pandas" title="Permalink to this heading">#</a></h1>
 <p><a class="reference external" href="http://pandas.pydata.org/"><em>pandas</em></a> is a column-oriented data analysis API. It’s a great tool for handling and analyzing input data, and many ML frameworks support <em>pandas</em> data structures as inputs.
 Although a comprehensive introduction to the <em>pandas</em> API would span many pages, the core concepts are fairly straightforward, and we’ll present them below. For a more complete reference, the <a class="reference external" href="http://pandas.pydata.org/pandas-docs/stable/index.html"><em>pandas</em> docs site</a> contains extensive documentation and many tutorials.</p>
@@ -1253,7 +1254,8 @@ <h2>Exercise<a class="headerlink" href="#exercise" title="Permalink to this head
 </ul>
 <div class="cell docutils container">
 <div class="cell_input docutils container">
-<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">blobs_df</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="s1">&#39;../../data/blobs_statistics.csv&#39;</span><span class="p">)</span>
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">blobs_df</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="s2">&quot;https://github.com/vmcf-konfmi/MB100T01/raw/main/data/blobs_statistics.csv&quot;</span><span class="p">)</span>
+<span class="c1">#blobs_df = pd.read_csv(&#39;../../data/blobs_statistics.csv&#39;)</span>
 <span class="n">blobs_df</span>
 </pre></div>
 </div>

01_pandas_statistics/02_Pandas_operations.html

@@ -423,7 +423,8 @@ <h2> Contents </h2>
 <div id="searchbox"></div>
                 <article class="bd-article" role="main">
 
-  <section class="tex2jax_ignore mathjax_ignore" id="basic-operations">
+  <p><img align="left" src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in Colab" title="Open in Google Colaboratory"></a><p><a href="https://githubtocolab.com/vmcf-konfmi/MB100T01/blob/main/advanced_image_analysis_mb100t01/01_pandas_statistics/02_Pandas_operations.ipynb"></p>
+<section class="tex2jax_ignore mathjax_ignore" id="basic-operations">
 <h1>Basic Operations<a class="headerlink" href="#basic-operations" title="Permalink to this heading">#</a></h1>
 <p>Inspiration and some of the parts came from: Python Data Science <a class="reference external" href="https://github.com/jakevdp/PythonDataScienceHandbook/tree/master">GitHub repository</a>, <a class="reference external" href="https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/LICENSE-CODE">MIT License</a> and <a class="reference external" href="https://colab.research.google.com/notebooks/mlcc/intro_to_pandas.ipynb">Introduction to Pandas</a> by Google, <a class="reference external" href="https://www.apache.org/licenses/LICENSE-2.0">Apache 2.0</a></p>
 <p>If running this from Google Colab, uncomment the cell below and run it. Otherwise, just skip it.</p>

01_pandas_statistics/03_Pandas_EDA.html

@@ -416,7 +416,8 @@ <h2> Contents </h2>
 <div id="searchbox"></div>
                 <article class="bd-article" role="main">
 
-  <section class="tex2jax_ignore mathjax_ignore" id="exploratory-data-analysis">
+  <p><img align="left" src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in Colab" title="Open in Google Colaboratory"></a><p><a href="https://githubtocolab.com/vmcf-konfmi/MB100T01/blob/main/advanced_image_analysis_mb100t01/01_pandas_statistics/03_Pandas_EDA.ipynb"></p>
+<section class="tex2jax_ignore mathjax_ignore" id="exploratory-data-analysis">
 <h1>Exploratory Data Analysis<a class="headerlink" href="#exploratory-data-analysis" title="Permalink to this heading">#</a></h1>
 <p>Inspiration and some of the parts came from: Python Data Science <a class="reference external" href="https://github.com/jakevdp/PythonDataScienceHandbook/tree/master">GitHub repository</a>, <a class="reference external" href="https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/LICENSE-CODE">MIT License</a> and <a class="reference external" href="https://colab.research.google.com/notebooks/mlcc/intro_to_pandas.ipynb">Introduction to Pandas</a> by Google, <a class="reference external" href="https://www.apache.org/licenses/LICENSE-2.0">Apache 2.0</a></p>
 <p>If running this from Google Colab, uncomment the cell below and run it. Otherwise, just skip it.</p>

01_pandas_statistics/04_Pandas_Bonus.html

@@ -425,7 +425,8 @@ <h2> Contents </h2>
 <div id="searchbox"></div>
                 <article class="bd-article" role="main">
 
-  <section class="tex2jax_ignore mathjax_ignore" id="basic-plots-groupping-and-multi-level-tables">
+  <p><img align="left" src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in Colab" title="Open in Google Colaboratory"></a><p><a href="https://githubtocolab.com/vmcf-konfmi/MB100T01/blob/main/advanced_image_analysis_mb100t01/01_pandas_statistics/04_Pandas_Bonus.ipynb"></p>
+<section class="tex2jax_ignore mathjax_ignore" id="basic-plots-groupping-and-multi-level-tables">
 <h1>Basic Plots, Groupping and Multi-Level Tables<a class="headerlink" href="#basic-plots-groupping-and-multi-level-tables" title="Permalink to this heading">#</a></h1>
 <p>Inspiration and some of the parts came from: Python Data Science <a class="reference external" href="https://github.com/jakevdp/PythonDataScienceHandbook/tree/master">GitHub repository</a>, <a class="reference external" href="https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/LICENSE-CODE">MIT License</a> and <a class="reference external" href="https://colab.research.google.com/notebooks/mlcc/intro_to_pandas.ipynb">Introduction to Pandas</a> by Google, <a class="reference external" href="https://www.apache.org/licenses/LICENSE-2.0">Apache 2.0</a></p>
 <p>If running this from Google Colab, uncomment the cell below and run it. Otherwise, just skip it.</p>

01_pandas_statistics/05_Statistic.html

@@ -448,7 +448,8 @@ <h2> Contents </h2>
 <div id="searchbox"></div>
                 <article class="bd-article" role="main">
 
-  <section class="tex2jax_ignore mathjax_ignore" id="statistics">
+  <p><img align="left" src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in Colab" title="Open in Google Colaboratory"></a><p><a href="https://githubtocolab.com/vmcf-konfmi/MB100T01/blob/main/advanced_image_analysis_mb100t01/01_pandas_statistics/05_Statistic.ipynb"></p>
+<section class="tex2jax_ignore mathjax_ignore" id="statistics">
 <h1>Statistics<a class="headerlink" href="#statistics" title="Permalink to this heading">#</a></h1>
 <p>Sources and inspiration:</p>
 <ul class="simple">