fix typos

Author: hauselin

.DS_Store

@@ -27,7 +27,7 @@ knitr::opts_chunk$set(echo = TRUE, cache = FALSE, comment = NA, message = FALSE,
 
 Get source code for this RMarkdown script [here](https://raw.githubusercontent.com/hauselin/rtutorialsite/master/_posts/2020-05-17-reshape-python-pandas-dataframe-from-long-to-wide-with-pivottable/reshape-python-pandas-dataframe-from-long-to-wide-with-pivottable.Rmd).
 
-This Python tutorial is also available on [Medium, Towards Data Science](https://towardsdatascience.com/reshape-pandas-dataframe-with-melt-in-python-tutorial-and-visualization-29ec1450bb02). Click here if you're looking for the R version of melt (also the `melt` function in R).
+This Python tutorial is on [Medium, Towards Data Science](https://towardsdatascience.com/reshape-pandas-dataframe-with-melt-in-python-tutorial-and-visualization-29ec1450bb02). Click here if you're looking for the tutorial for the R version of melt (also the `melt` function in R).
 
 ## Consider being a patron and supporting my work?
 
@@ -37,7 +37,7 @@ How does the pandas `melt()` method reshape dataframes? How do you reshape a dat
 
 ![Summary of how pd.melt() works](./main_wide2long.png)
 
-Also, you might want to check out the official pandas documentation and my [numpy reshape tutorial](https://towardsdatascience.com/reshape-pandas-dataframe-with-melt-in-python-tutorial-and-visualization-29ec1450bb02).
+Also, you might want to check out the official pandas documentation and my [numpy reshape tutorial](https://towardsdatascience.com/reshaping-numpy-arrays-in-python-a-step-by-step-pictorial-tutorial-aed5f471cf0b?source=friends_link&sk=3dc229066e89cb5bcd4bb86b301f0a5c).
 
 Let's load the `reticulate` library in R so we can run Python in RStudio. I'll then load my conda python environment. I highly recommend you try the code in Python while you read this article. Try running this tutorial on my shared [DeepNote notebook](https://beta.deepnote.com/project/d1350ad6-bcb4-4c3d-857b-c29d01b8a803) (you can only run but not edit this notebook).
 
@@ -83,7 +83,7 @@ df_wide
 
 Common terms for this transformation are melt, unpivot, gather, stack. See `pd.melt()` documentation [here](https://pandas.pydata.org/docs/reference/api/pandas.melt.html).
 
-### Melt Example 1
+### Melt example 1
 
 We melt the dataframe by specifying the identifier columns via `id_vars`. The “leftover” non-identifier columns (english, math, physics) will be melted or stacked onto each other into one column.
 
@@ -101,7 +101,7 @@ pd.melt(frame=df_wide,
 
 ![Wide to long: new indicator column “cLaSs” + values melted/stacked “gRaDe” column](./pic3.png)
 
-### Melt Example 2
+### Melt example 2
 
 You can use `value_vars` to specify which columns you want to melt or stack into column (here, we exclude physics column, so `value_vars=["english", "math"]`). We also drop the school column from `id_vars`.
 
@@ -118,7 +118,7 @@ pd.melt(frame=df_wide,
 
 ![Wide to long: original columns school and physics have been dropped](./pic4.png)
 
-### Melt Example 3
+### Melt example 3
 
 Finally, let’s see what happens if we specify only the student column as the identifier column (`id_vars="student"`) but do not specify which columns you want to stack via `value_vars`. As a result, all non-identifier columns (school, english, math, physics) will be stacked into one column.
 
@@ -140,6 +140,6 @@ This table looks wrong because the `school` column in `df_wide` doesn't belong
 
 ## Support my work
 
-I hope now you have a better understanding of how `pd.melt` reshapes dataframes. If you find this post useful, check out my other articles and visit my [Medium page](https://medium.com/@ausius).
+I hope now you have a better understanding of how `pd.melt` reshapes dataframes. If you find this post useful, check out my other articles and folow me on [Medium ](https://medium.com/@ausius).
 
 If you've enjoyed my article, [support my work and become a patron here](https://donorbox.org/support-my-teaching)!

_posts/2020-05-14-reshaping-data-in-python-pandas/reshaping-data-in-python-pandas.Rmd

@@ -969,23 +969,23 @@ <h3 class="d-toc-header">Table of Contents</h3>
 <li><a href="#consider-being-a-patron-and-supporting-my-work">Consider being a patron and supporting my work?</a></li>
 <li><a href="#wide-data">Wide data</a></li>
 <li><a href="#wide-to-long-with-melt">Wide to long with <code>melt</code></a><ul>
-<li><a href="#melt-example-1">Melt Example 1</a></li>
-<li><a href="#melt-example-2">Melt Example 2</a></li>
-<li><a href="#melt-example-3">Melt Example 3</a></li>
+<li><a href="#melt-example-1">Melt example 1</a></li>
+<li><a href="#melt-example-2">Melt example 2</a></li>
+<li><a href="#melt-example-3">Melt example 3</a></li>
 </ul></li>
 <li><a href="#support-my-work">Support my work</a></li>
 </ul>
 </nav>
 <hr class="d-toc-separator"/>
 <p>Get source code for this RMarkdown script <a href="https://raw.githubusercontent.com/hauselin/rtutorialsite/master/_posts/2020-05-17-reshape-python-pandas-dataframe-from-long-to-wide-with-pivottable/reshape-python-pandas-dataframe-from-long-to-wide-with-pivottable.Rmd">here</a>.</p>
-<p>This Python tutorial is also available on <a href="https://towardsdatascience.com/reshape-pandas-dataframe-with-melt-in-python-tutorial-and-visualization-29ec1450bb02">Medium, Towards Data Science</a>. Click here if you’re looking for the R version of melt (also the <code>melt</code> function in R).</p>
+<p>This Python tutorial is on <a href="https://towardsdatascience.com/reshape-pandas-dataframe-with-melt-in-python-tutorial-and-visualization-29ec1450bb02">Medium, Towards Data Science</a>. Click here if you’re looking for the tutorial for the R version of melt (also the <code>melt</code> function in R).</p>
 <h2 id="consider-being-a-patron-and-supporting-my-work">Consider being a patron and supporting my work?</h2>
 <p><a href="https://donorbox.org/support-my-teaching">Donate and become a patron</a>: If you find value in what I do and have learned something from my site, please consider becoming a patron. It takes me many hours to research, learn, and put together tutorials. Your support really matters.</p>
 <p>How does the pandas <code>melt()</code> method reshape dataframes? How do you reshape a dataframe from wide to long form? This tutorial will walk you through reshaping dataframes using <code>pd.melt()</code> or the <code>melt</code> method associated with pandas dataframes.</p>
 <figure>
 <img src="main_wide2long.png" alt="Summary of how pd.melt() works" /><figcaption>Summary of how pd.melt() works</figcaption>
 </figure>
-<p>Also, you might want to check out the official pandas documentation and my <a href="https://towardsdatascience.com/reshape-pandas-dataframe-with-melt-in-python-tutorial-and-visualization-29ec1450bb02">numpy reshape tutorial</a>.</p>
+<p>Also, you might want to check out the official pandas documentation and my <a href="https://towardsdatascience.com/reshaping-numpy-arrays-in-python-a-step-by-step-pictorial-tutorial-aed5f471cf0b?source=friends_link&amp;sk=3dc229066e89cb5bcd4bb86b301f0a5c">numpy reshape tutorial</a>.</p>
 <p>Let’s load the <code>reticulate</code> library in R so we can run Python in RStudio. I’ll then load my conda python environment. I highly recommend you try the code in Python while you read this article. Try running this tutorial on my shared <a href="https://beta.deepnote.com/project/d1350ad6-bcb4-4c3d-857b-c29d01b8a803">DeepNote notebook</a> (you can only run but not edit this notebook).</p>
 <div class="layout-chunk" data-layout="l-body">
 <pre class="r"><code>
@@ -1031,7 +1031,7 @@ <h2 id="wide-data">Wide data</h2>
 </div>
 <h2 id="wide-to-long-with-melt">Wide to long with <code>melt</code></h2>
 <p>Common terms for this transformation are melt, unpivot, gather, stack. See <code>pd.melt()</code> documentation <a href="https://pandas.pydata.org/docs/reference/api/pandas.melt.html">here</a>.</p>
-<h3 id="melt-example-1">Melt Example 1</h3>
+<h3 id="melt-example-1">Melt example 1</h3>
 <p>We melt the dataframe by specifying the identifier columns via <code>id_vars</code>. The “leftover” non-identifier columns (english, math, physics) will be melted or stacked onto each other into one column.</p>
 <p>A new indicator column will be created (contains values english, math, physics) and we can rename this new column (cLaSs) via <code>var_name</code>. We can also rename the column in which all the actual grades are contained (gRaDe) via <code>value_name</code>.</p>
 <div class="layout-chunk" data-layout="l-body">
@@ -1061,7 +1061,7 @@ <h3 id="melt-example-1">Melt Example 1</h3>
 <figure>
 <img src="pic3.png" alt="Wide to long: new indicator column “cLaSs” + values melted/stacked “gRaDe” column" /><figcaption>Wide to long: new indicator column “cLaSs” + values melted/stacked “gRaDe” column</figcaption>
 </figure>
-<h3 id="melt-example-2">Melt Example 2</h3>
+<h3 id="melt-example-2">Melt example 2</h3>
 <p>You can use <code>value_vars</code> to specify which columns you want to melt or stack into column (here, we exclude physics column, so <code>value_vars=[&quot;english&quot;, &quot;math&quot;]</code>). We also drop the school column from <code>id_vars</code>.</p>
 <div class="layout-chunk" data-layout="l-body">
 <pre class="python"><code>
@@ -1087,7 +1087,7 @@ <h3 id="melt-example-2">Melt Example 2</h3>
 <figure>
 <img src="pic4.png" alt="Wide to long: original columns school and physics have been dropped" /><figcaption>Wide to long: original columns school and physics have been dropped</figcaption>
 </figure>
-<h3 id="melt-example-3">Melt Example 3</h3>
+<h3 id="melt-example-3">Melt example 3</h3>
 <p>Finally, let’s see what happens if we specify only the student column as the identifier column (<code>id_vars=&quot;student&quot;</code>) but do not specify which columns you want to stack via <code>value_vars</code>. As a result, all non-identifier columns (school, english, math, physics) will be stacked into one column.</p>
 <p>The resulting long dataframe looks wrong because now the cLaSs and gRaDe columns contain values that shouldn’t be there. The point here is to show you how <code>pd.melt</code> works.</p>
 <div class="layout-chunk" data-layout="l-body">
@@ -1123,7 +1123,7 @@ <h3 id="melt-example-3">Melt Example 3</h3>
 <img src="pic5.png" alt="Wide to long: school column isn’t an identifier column" /><figcaption>Wide to long: school column isn’t an identifier column</figcaption>
 </figure>
 <h2 id="support-my-work">Support my work</h2>
-<p>I hope now you have a better understanding of how <code>pd.melt</code> reshapes dataframes. If you find this post useful, check out my other articles and visit my <a href="https://medium.com/@ausius">Medium page</a>.</p>
+<p>I hope now you have a better understanding of how <code>pd.melt</code> reshapes dataframes. If you find this post useful, check out my other articles and folow me on <a href="https://medium.com/@ausius">Medium</a>.</p>
 <p>If you’ve enjoyed my article, <a href="https://donorbox.org/support-my-teaching">support my work and become a patron here</a>!</p>
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_posts/2020-05-14-reshaping-data-in-python-pandas/reshaping-data-in-python-pandas.html

@@ -25,19 +25,21 @@ editor_options:
 knitr::opts_chunk$set(echo = TRUE, cache = FALSE, comment = NA, message = FALSE, warning = FALSE)
 ```
 
-Get source code for this RMarkdown script [here](https://raw.githubusercontent.com/hauselin/rtutorialsite/master/_posts/2020-05-14-reshaping-data-in-python-pandas/reshaping-data-in-python-pandas.Rmd).
+Get source code for this RMarkdown script [here](https://raw.githubusercontent.com/hauselin/rtutorialsite/master/_posts/2020-05-17-reshape-python-pandas-dataframe-from-long-to-wide-with-pivottable/reshape-python-pandas-dataframe-from-long-to-wide-with-pivottable.Rmd).
 
-This Python tutorial is also available on [Medium, Towards Data Science](https://towardsdatascience.com/reshape-pandas-dataframe-with-melt-in-python-tutorial-and-visualization-29ec1450bb02). Click here if you're looking for the R version of melt (also the `dcast` function in R).
+This Python tutorial is also on [Medium, Towards Data Science](https://towardsdatascience.com/reshape-pandas-dataframe-with-melt-in-python-tutorial-and-visualization-29ec1450bb02). Click here if you're looking for the tutorail for the R version of `pivot_table` (also the `dcast` function in R).
+
+The opposite of `pivot_table` is `melt`, and you can find the tutorial for `melt` (wide to long) [here](https://towardsdatascience.com/reshape-pandas-dataframe-with-melt-in-python-tutorial-and-visualization-29ec1450bb02?source=friends_link&sk=5200888fd2030a2ede726c00dec8b610).
 
 ## Consider being a patron and supporting my work?
 
 [Donate and become a patron](https://donorbox.org/support-my-teaching): If you find value in what I do and have learned something from my site, please consider becoming a patron. It takes me many hours to research, learn, and put together tutorials. Your support really matters.
 
-How does the pandas `pivot_table()` method reshape dataframes? How do you reshape a dataframe from wide to long form? This tutorial will walk you through reshaping dataframes using `pd.pivot_table()` or the `pivot_table` method associated with pandas dataframes.
+How does the pandas `pivot_table()` method reshape dataframes? How do you reshape a dataframe from long to wide form? This tutorial will walk you through reshaping dataframes using `pd.pivot_table()` or the `pivot_table` method associated with pandas dataframes.
 
 ![Summary of how pd.pivot_table() works](pic1.png)
 
-Also, you might want to check out the official pandas documentation and my [numpy reshape tutorial](https://towardsdatascience.com/reshape-pandas-dataframe-with-melt-in-python-tutorial-and-visualization-29ec1450bb02).
+Also, you might want to check out the official pandas documentation and my [numpy reshape tutorial](https://towardsdatascience.com/reshaping-numpy-arrays-in-python-a-step-by-step-pictorial-tutorial-aed5f471cf0b?source=friends_link&sk=3dc229066e89cb5bcd4bb86b301f0a5c).
 
 Let's load the `reticulate` library in R so we can run Python in RStudio. I'll then load my conda python environment. I highly recommend you try the code in Python while you read this article. Try running this tutorial on my shared [DeepNote notebook](https://beta.deepnote.com/project/b494e5b7-9e5c-4e06-8a4a-43130d27aa3f) (you can only run but not edit this notebook).
 
@@ -145,6 +147,6 @@ https://stackoverflow.com/questions/22798934/pandas-long-to-wide-reshape-by-two-
 
 ## Support my work
 
-I hope now you have a better understanding of how `pd.pivot_table` reshapes dataframes. If you find this post useful, check out my other articles and visit my [Medium page](https://medium.com/@ausius).
+I hope now you have a better understanding of how `pd.pivot_table` reshapes dataframes. If you find this post useful, check out my other articles and folow me on [Medium ](https://medium.com/@ausius).
 
 If you've enjoyed my article, [support my work and become a patron here](https://donorbox.org/support-my-teaching)!

_posts/2020-05-17-reshape-python-pandas-dataframe-from-long-to-wide-with-pivottable/reshape-python-pandas-dataframe-from-long-to-wide-with-pivottable.Rmd

@@ -976,15 +976,16 @@ <h3 class="d-toc-header">Table of Contents</h3>
 </ul>
 </nav>
 <hr class="d-toc-separator"/>
-<p>Get source code for this RMarkdown script <a href="https://raw.githubusercontent.com/hauselin/rtutorialsite/master/_posts/2020-05-14-reshaping-data-in-python-pandas/reshaping-data-in-python-pandas.Rmd">here</a>.</p>
-<p>This Python tutorial is also available on <a href="https://towardsdatascience.com/reshape-pandas-dataframe-with-melt-in-python-tutorial-and-visualization-29ec1450bb02">Medium, Towards Data Science</a>. Click here if you’re looking for the R version of melt (also the <code>dcast</code> function in R).</p>
+<p>Get source code for this RMarkdown script <a href="https://raw.githubusercontent.com/hauselin/rtutorialsite/master/_posts/2020-05-17-reshape-python-pandas-dataframe-from-long-to-wide-with-pivottable/reshape-python-pandas-dataframe-from-long-to-wide-with-pivottable.Rmd">here</a>.</p>
+<p>This Python tutorial is also on <a href="https://towardsdatascience.com/reshape-pandas-dataframe-with-melt-in-python-tutorial-and-visualization-29ec1450bb02">Medium, Towards Data Science</a>. Click here if you’re looking for the tutorail for the R version of <code>pivot_table</code> (also the <code>dcast</code> function in R).</p>
+<p>The opposite of <code>pivot_table</code> is <code>melt</code>, and you can find the tutorial for <code>melt</code> (wide to long) <a href="https://towardsdatascience.com/reshape-pandas-dataframe-with-melt-in-python-tutorial-and-visualization-29ec1450bb02?source=friends_link&amp;sk=5200888fd2030a2ede726c00dec8b610">here</a>.</p>
 <h2 id="consider-being-a-patron-and-supporting-my-work">Consider being a patron and supporting my work?</h2>
 <p><a href="https://donorbox.org/support-my-teaching">Donate and become a patron</a>: If you find value in what I do and have learned something from my site, please consider becoming a patron. It takes me many hours to research, learn, and put together tutorials. Your support really matters.</p>
-<p>How does the pandas <code>pivot_table()</code> method reshape dataframes? How do you reshape a dataframe from wide to long form? This tutorial will walk you through reshaping dataframes using <code>pd.pivot_table()</code> or the <code>pivot_table</code> method associated with pandas dataframes.</p>
+<p>How does the pandas <code>pivot_table()</code> method reshape dataframes? How do you reshape a dataframe from long to wide form? This tutorial will walk you through reshaping dataframes using <code>pd.pivot_table()</code> or the <code>pivot_table</code> method associated with pandas dataframes.</p>
 <figure>
 <img src="pic1.png" alt="Summary of how pd.pivot_table() works" /><figcaption>Summary of how pd.pivot_table() works</figcaption>
 </figure>
-<p>Also, you might want to check out the official pandas documentation and my <a href="https://towardsdatascience.com/reshape-pandas-dataframe-with-melt-in-python-tutorial-and-visualization-29ec1450bb02">numpy reshape tutorial</a>.</p>
+<p>Also, you might want to check out the official pandas documentation and my <a href="https://towardsdatascience.com/reshaping-numpy-arrays-in-python-a-step-by-step-pictorial-tutorial-aed5f471cf0b?source=friends_link&amp;sk=3dc229066e89cb5bcd4bb86b301f0a5c">numpy reshape tutorial</a>.</p>
 <p>Let’s load the <code>reticulate</code> library in R so we can run Python in RStudio. I’ll then load my conda python environment. I highly recommend you try the code in Python while you read this article. Try running this tutorial on my shared <a href="https://beta.deepnote.com/project/b494e5b7-9e5c-4e06-8a4a-43130d27aa3f">DeepNote notebook</a> (you can only run but not edit this notebook).</p>
 <div class="layout-chunk" data-layout="l-body">
 <pre class="r"><code>
@@ -1154,7 +1155,7 @@ <h2 id="resources">Resources</h2>
 <p><a href="https://chrisalbon.com/python/data_wrangling/pandas_pivot_tables/" class="uri">https://chrisalbon.com/python/data_wrangling/pandas_pivot_tables/</a></p>
 <p><a href="https://stackoverflow.com/questions/22798934/pandas-long-to-wide-reshape-by-two-variables" class="uri">https://stackoverflow.com/questions/22798934/pandas-long-to-wide-reshape-by-two-variables</a></p>
 <h2 id="support-my-work">Support my work</h2>
-<p>I hope now you have a better understanding of how <code>pd.pivot_table</code> reshapes dataframes. If you find this post useful, check out my other articles and visit my <a href="https://medium.com/@ausius">Medium page</a>.</p>
+<p>I hope now you have a better understanding of how <code>pd.pivot_table</code> reshapes dataframes. If you find this post useful, check out my other articles and folow me on <a href="https://medium.com/@ausius">Medium</a>.</p>
 <p>If you’ve enjoyed my article, <a href="https://donorbox.org/support-my-teaching">support my work and become a patron here</a>!</p>
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 <!--/radix_placeholder_article_footer-->