TR and MP comments incorporated into Ch 11

DS-100 · Apr 30, 2023 · 349154d · 349154d
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diff --git a/content/ch/11/viz_comparisons.ipynb b/content/ch/11/viz_comparisons.ipynb
diff --git a/content/ch/11/viz_context.ipynb b/content/ch/11/viz_context.ipynb
diff --git a/content/ch/11/viz_data_design.ipynb b/content/ch/11/viz_data_design.ipynb
diff --git a/content/ch/11/viz_intro.ipynb b/content/ch/11/viz_intro.ipynb
@@ -35,7 +35,7 @@
     "In {numref}`Chapter %s <ch:eda>`, we connected the choice of a statistical graph to the kind of data being plotted; we also introduced many standard plots and showed how to read them.  In this chapter, we discuss the principles of effective data visualization that make it easier for our audience to grasp the message in our plot. We talk about how to choose scales for axes,\n",
     "handle large amounts of data with smoothing and aggregation, facilitate\n",
     "meaningful comparisons, incorporate study design, and add contextual information. \n",
-    "We also show how to create plots in Python using `plotly`, a popular package for plotting in Python. \n",
+    "We also show how to create plots using `plotly`, a popular package for plotting in Python. \n",
     "\n",
     "One tricky part about writing a chapter on data visualization is that \n",
     "software packages for visualization change all the time, so any code we display\n",

diff --git a/content/ch/11/viz_other_tools.ipynb b/content/ch/11/viz_other_tools.ipynb
@@ -46,7 +46,7 @@
    "source": [
     "## `matplotlib`\n",
     "\n",
-    "[matplotlib](https://matplotlib.org/) is one of the first data visualization tools for Python.\n",
+    "The library [matplotlib](https://matplotlib.org/) is one of the first data visualization tools for Python.\n",
     "Because of this, it is widely used and has a large ecosystem of packages.\n",
     "Notably, the built-in plotting methods for `pandas` dataframes\n",
     "make plots using `matplotlib`.\n",
@@ -85,8 +85,8 @@
     "The grammar of graphics is an elegant system that we can use to describe \n",
     "nearly every kind of plot we wish to make.\n",
     "\n",
-    "This system is implemented in the popular plotting libraries `ggplot2` for the\n",
-    "R programming language and `vega` for JavaScript.\n",
+    "This system is implemented in the popular plotting libraries [ggplot2](https://ggplot2.tidyverse.org/) for the\n",
+    "R programming language and [vega](https://vega.github.io/vega/) for JavaScript.\n",
     "A Python package called [altair](https://altair-viz.github.io/) provides a way to create `vega` plots using\n",
     "Python, and we encourage interested readers to look over its documentation.\n",
     "\n",

diff --git a/content/ch/11/viz_plotly.ipynb b/content/ch/11/viz_plotly.ipynb
diff --git a/content/ch/11/viz_scale.ipynb b/content/ch/11/viz_scale.ipynb
diff --git a/content/ch/11/viz_smoothing.ipynb b/content/ch/11/viz_smoothing.ipynb
diff --git a/content/ch/11/viz_summary.ipynb b/content/ch/11/viz_summary.ipynb
@@ -52,12 +52,19 @@
     "After this chapter, you should be able to create a plot and understand\n",
     "what kinds of adjustments would make the plot more effective.\n",
     "As you learn how to make informative visualizations be patient and iterate.\n",
-    "None of us makes the perfect plot on the first try. And, as we make discoveries in an analysis, we continue to refine our plots. Then, when it comes time to present our findings to others, we sift through our work to get the few plots that best convince our future reader of the correctness and importance of our analysis. This can even lead to the creation of a new plot that best conveys our findings, which we iteratively develop. \n",
+    "None of us makes the perfect plot on the first try. And, as we make discoveries in an analysis, we continue to refine our plots. Then, when it comes time to present our findings to others, we sift through our work to get the few plots that best convince our future reader of the correctness and importance of our analysis. This can even lead to the creation of a new plot that better conveys our findings, which we iteratively develop. \n",
     "\n",
     "In the next chapter, we walk through an extended case study that\n",
     "combines everything we've learned in the book so far. We hope that you\n",
     "find yourself surprised by how much you can already do."
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
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