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blog/Statistics_10days-day0.html
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@ -185,7 +185,7 @@ For a continuous probability distribution, the median is the value such that a n
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blog/Statistics_10days-day1.html
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blog/Statistics_10days-day2.html
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blog/Statistics_10days-day3.html
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@ -256,7 +256,7 @@ we call B the event "a blue ball is drawn" and R the event "a red ball is drawn"
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blog/Statistics_10days-day4.html
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@ -311,7 +311,7 @@
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blog/Statistics_10days-day5.html
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@ -331,7 +331,7 @@ Between 20 and 22 hours?</p>
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blog/Statistics_10days-day6.html
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@ -270,7 +270,7 @@ The total number of tickets bought follows a normal distribution of mean <span c
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blog/Statistics_10days-day7.html
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@ -272,7 +272,7 @@
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blog/Statistics_10days-day8.html
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@ -277,7 +277,7 @@ $$</div>
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blog/Statistics_10days-day9.html
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@ -275,7 +275,7 @@
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cryptocurrencies/Installing_bitcoind_on_raspberry_pi.html
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@ -286,7 +286,7 @@ maxuploadtarget=5000
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cryptocurrencies/blockchain_bad.html
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@ -161,7 +161,7 @@
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cryptocurrencies/mayer_multiple.html
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@ -365,7 +365,7 @@
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dl/csv_logger_keras.html
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@ -279,7 +279,7 @@ Let's first import some libraries</p>
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dl/keras_info.html
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@ -161,7 +161,7 @@
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dl/keras_input.html
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@ -149,7 +149,7 @@
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dl/keras_install.html
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@ -152,7 +152,7 @@
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dl/keras_load.html
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@ -154,7 +154,7 @@
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dl/model_checkpoint_keras.html
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@ -235,7 +235,7 @@ Let's first import some libraries</p>
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dl/tensorboard_keras.html
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@ -280,7 +280,7 @@
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index.html
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@ -409,6 +409,7 @@
</div>
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<ul>
<li><a href="./python/numpy_save.html">Save a numpy array to disk</a></li>
<li><a href="./python/select_lines_values_list.html">Filter or select lines of a DataFrame containing values in a list</a></li>
<li><a href="./python/reverse_column_order.html">Reverse column order in pandas</a></li>
<li><a href="./python/reverse_row_order.html">Reverse row order in pandas</a></li>
@ -496,6 +497,7 @@
</div>
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<li><a href="./python/natural_sort.html">Natural sort of list</a></li>
<li><a href="./python/maximize_window.html">Maximize a window in Windows</a></li>
<li><a href="./python/case_config.html">Case sensitive ConfigParser</a></li>
<li><a href="./python/list_windows.html">List all opened windows on Windows</a></li>
@ -713,7 +715,7 @@
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jupyter/clear_cell.html
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@ -149,7 +149,7 @@
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jupyter/remote_run_notebook.html
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@ -211,7 +211,7 @@
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linux/Reloading_.bashrc.html
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@ -144,7 +144,7 @@ However, you can use the following command to do it </p>
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linux/Reloading_fstab.html
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@ -143,7 +143,7 @@
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linux/bashrc.html
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@ -203,7 +203,7 @@
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linux/directory_size.html
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@ -148,7 +148,7 @@
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linux/free_disk_space_linux.html
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@ -167,7 +167,7 @@ none 0 0 0 - /config
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linux/get_ip_linux.html
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@ -256,7 +256,7 @@ wifi0 Link encap:UNSPEC HWaddr 5C-51-4F-41-7A-AD-00-00-00-00-00-00-00-00-00
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linux/linux_process_information.html
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@ -172,7 +172,7 @@ USER;PID;%CPU;%MEM;VSZ;RSS;TTY;STAT;START;TIME;COMMAND</p>
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linux/mount_nfs_share_fstab.html
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@ -158,7 +158,7 @@
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linux/ramdisk.html
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@ -169,7 +169,7 @@ dd <span class="k">if</span><span class="o">=</span>/dev/zero <span class="nv">o
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linux/sed.html
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@ -494,7 +494,7 @@
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linux/share_nfs_share.html
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@ -151,7 +151,7 @@
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linux/simple_bash_function.html
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@ -208,7 +208,7 @@ The secret number is 126
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linux/version_kernel.html
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@ -160,7 +160,7 @@
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machine-learning/LeastSquareRegressionLine.html
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@ -234,7 +234,7 @@ Where :</p>
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machine-learning/Log_experiments_mlflow.html
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@ -176,7 +176,7 @@
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machine-learning/Multiple_Linear_Regression.html
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@ -248,7 +248,7 @@ b_2\\
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mathematics/Bayes.html
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@ -196,7 +196,7 @@
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mathematics/Binomial.html
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mathematics/Geometric.html
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@ -233,7 +233,7 @@ So :
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mathematics/KLD.html
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mathematics/Number_edges_Complete_graph.html
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<h1>
Natural sort of list
</h1>
<ol class="breadcrumb">
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<time class="published" datetime="2019-11-04T14:34:00+01:00">
04 novembre 2019
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<li>Python</li>
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<div class='article_content'>
<p>Natural sort order is an ordering of strings in alphabetical order, except that multi-digit numbers are ordered as a single character. Natural sort order has been promoted as being more human-friendly ("natural") than the machine-oriented pure alphabetical order.</p>
<p>For example, in alphabetical sorting "z11" would be sorted before "z2" because "1" is sorted as smaller than "2", while in natural sorting "z2" is sorted before "z11" because "2" is sorted as smaller than "11".</p>
<div class="highlight"><pre><span></span><span class="k">def</span> <span class="nf">natural_sort</span><span class="p">(</span><span class="n">l</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> return the list l in a natural sort order</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="n">convert</span> <span class="o">=</span> <span class="k">lambda</span> <span class="n">text</span><span class="p">:</span> <span class="nb">int</span><span class="p">(</span><span class="n">text</span><span class="p">)</span> <span class="k">if</span> <span class="n">text</span><span class="o">.</span><span class="n">isdigit</span><span class="p">()</span> <span class="k">else</span> <span class="n">text</span><span class="o">.</span><span class="n">lower</span><span class="p">()</span>
<span class="n">alphanum_key</span> <span class="o">=</span> <span class="k">lambda</span> <span class="n">key</span><span class="p">:</span> <span class="p">[</span><span class="n">convert</span><span class="p">(</span><span class="n">c</span><span class="p">)</span> <span class="k">for</span> <span class="n">c</span> <span class="ow">in</span> <span class="n">re</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s2">&quot;([0-9]+)&quot;</span><span class="p">,</span> <span class="n">key</span><span class="p">)]</span>
<span class="k">return</span> <span class="nb">sorted</span><span class="p">(</span><span class="n">l</span><span class="p">,</span> <span class="n">key</span><span class="o">=</span><span class="n">alphanum_key</span><span class="p">)</span>
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<h1>
Save a numpy array to disk
</h1>
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<time class="published" datetime="2019-11-04T13:31:00+01:00">
04 novembre 2019
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<p>In this article we will learn how to save a numpy array to the disk. We will then see how to load it back from the disk into memory.</p>
<p>First, let't import numpy.</p>
<div class="highlight"><pre><span></span><span class="c1"># Import modules</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="kn">as</span> <span class="nn">np</span>
</pre></div>
<p>We will generate an array to demonstrate saving and loading.</p>
<div class="highlight"><pre><span></span><span class="n">myarray</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">10</span><span class="p">)</span>
</pre></div>
<p>Numpy arrays can be save to the disk to the binary <code>.npy</code> format by using the <code>save</code> method.</p>
<div class="highlight"><pre><span></span><span class="n">np</span><span class="o">.</span><span class="n">save</span><span class="p">(</span><span class="s2">&quot;C:</span><span class="se">\\</span><span class="s2">temp</span><span class="se">\\</span><span class="s2">arr.npy&quot;</span><span class="p">,</span> <span class="n">myarray</span><span class="p">)</span>
</pre></div>
<p>Once saved, it can be retrived from the disk by using the <code>load</code> method.</p>
<div class="highlight"><pre><span></span><span class="n">my_other_array</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">load</span><span class="p">(</span><span class="s2">&quot;C:</span><span class="se">\\</span><span class="s2">temp</span><span class="se">\\</span><span class="s2">arr.npy&quot;</span><span class="p">)</span>
<span class="n">my_other_array</span>
</pre></div>
<div class="highlight"><pre><span></span><span class="nb">array</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">4</span><span class="p">,</span> <span class="mi">5</span><span class="p">,</span> <span class="mi">6</span><span class="p">,</span> <span class="mi">7</span><span class="p">,</span> <span class="mi">8</span><span class="p">,</span> <span class="mi">9</span><span class="p">])</span>
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