Notebook review (#23)

* initial commit

* uninstalled pre-commit

* modified up to chapter 9

* finished all notebooks

Author: Azaya89

.github/workflows/pre-commit.yml

@@ -183,7 +183,7 @@
     "# 🔁 Modify the string for title below to change the title of the plot\n",
     "plot = figure(title=\"Please change this title\")\n",
     "\n",
-    "plot.circle([1, 2, 3], [6, 7, 4], size=10)\n",
+    "plot.scatter([1, 2, 3], [6, 7, 4], size=10, marker=\"circle\")\n",
     "show(plot)"
    ]
   },
@@ -287,9 +287,9 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "global-global-interactive-dataviz-bokeh",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
-   "name": "conda-env-global-global-interactive-dataviz-bokeh-py"
+   "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
@@ -301,7 +301,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.4"
+   "version": "3.12.0"
   },
   "vscode": {
    "interpreter": {

.pre-commit-config.yaml

@@ -157,7 +157,7 @@
     "\n",
     "A glyph is a visual representation of data. In the example above, the line representing\n",
     "the x and y data is a line glyph. Bokeh supports many different kinds of glyphs to use\n",
-    "inside of plots. Examples of glyphs include circles, wedges, bars, or tiles.\n",
+    "inside of plots. Examples of glyphs include scatters, wedges, bars, or tiles.\n",
     "\n",
     "You will use some of the most common glyphs throughout this tutorial."
    ]
@@ -231,13 +231,13 @@
     "\n",
     "# create three plots with one renderer each\n",
     "s1 = figure(width=250, height=250, background_fill_color=\"#fafafa\")\n",
-    "s1.circle(x, y0, size=12, color=\"#53777a\", alpha=0.8)\n",
+    "s1.scatter(x, y0, size=12, color=\"#53777a\", alpha=0.8, marker=\"circle\")\n",
     "\n",
     "s2 = figure(width=250, height=250, background_fill_color=\"#fafafa\")\n",
-    "s2.triangle(x, y1, size=12, color=\"#c02942\", alpha=0.8)\n",
+    "s2.scatter(x, y1, size=12, color=\"#c02942\", alpha=0.8, marker=\"triangle\")\n",
     "\n",
     "s3 = figure(width=250, height=250, background_fill_color=\"#fafafa\")\n",
-    "s3.square(x, y2, size=12, color=\"#d95b43\", alpha=0.8)\n",
+    "s3.scatter(x, y2, size=12, color=\"#d95b43\", alpha=0.8, marker=\"square\")\n",
     "\n",
     "# put the results in a row and show\n",
     "show(row(s1, s2, s3))"
@@ -270,9 +270,9 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "global-global-interactive-dataviz-bokeh",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
-   "name": "conda-env-global-global-interactive-dataviz-bokeh-py"
+   "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
@@ -284,7 +284,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.4"
+   "version": "3.12.0"
   },
   "vscode": {
    "interpreter": {

notebooks/01_introduction.ipynb

@@ -294,8 +294,7 @@
     "Creating a scatter plot follows a similar pattern as creating a line chart:\n",
     "\n",
     "1. Create a new figure using the `figure()` function.\n",
-    "2. Add the scatter plot points to the figure using a glyph function\n",
-    "(such as `circle()` or `square()`).\n",
+    "2. Add the scatter plot points to the figure using the scatter glyph function.\n",
     "3. Display the plot using the `show()` function.\n",
     "\n",
     "For example:"
@@ -311,7 +310,7 @@
     "p = figure(width=400, height=200)\n",
     "\n",
     "# add a circle renderer with x and y coordinates and size\n",
-    "p.circle([1, 2, 3, 4, 5], [6, 7, 2, 4, 5], size=15)\n",
+    "p.scatter([1, 2, 3, 4, 5], [6, 7, 2, 4, 5], size=15)\n",
     "\n",
     "show(p)  # show the results"
    ]
@@ -321,7 +320,7 @@
    "metadata": {},
    "source": [
     "Changing the shapes representing the points in your scatter plot is easy.\n",
-    "Just swap out the `circle()` function for a different glyph function.\n",
+    "Just specify the `marker` type for a different scatter glyph shape. The default is `circle`\n",
     "\n",
     "The cell below contains a scatter plot with different scatter markers that you\n",
     "can try. This example also uses additional arguments to change the color\n",
@@ -341,14 +340,14 @@
     "x = [1, 2, 3, 4, 5]\n",
     "y = [6, 7, 2, 4, 5]\n",
     "\n",
-    "# 🔁 use one of the different glyph functions to see what they do\n",
-    "p.triangle(x, y, size=15, color=\"red\", alpha=0.5)\n",
-    "# p.triangle_dot(x, y, size=15, color=\"yellow\", alpha=0.5)\n",
-    "# p.square(x, y, size=15, color=\"pink\", alpha=0.5)\n",
-    "# p.square_dot(x, y, size=15, color=\"blue\", alpha=0.5)\n",
-    "# p.square_cross(x, y, size=15, color=\"green\", alpha=0.5)\n",
-    "# p.square_pin(x, y, size=15, color=\"maroon\", alpha=0.5)\n",
-    "# p.asterisk(x, y, size=15, color=\"orange\", alpha=0.5)\n",
+    "# 🔁 use one of the different marker types to see what they do\n",
+    "# p.scatter(x, y, size=15, color=\"red\", alpha=0.5, marker=\"triangle\")\n",
+    "# p.scatter(x, y, size=15, color=\"yellow\", alpha=0.5, marker=\"triangle_dot\")\n",
+    "# p.scatter(x, y, size=15, color=\"pink\", alpha=0.5, marker=\"square\")\n",
+    "# p.scatter(x, y, size=15, color=\"blue\", alpha=0.5, marker=\"square_dot\")\n",
+    "# p.scatter(x, y, size=15, color=\"green\", alpha=0.5, marker=\"square_cross\")\n",
+    "# p.scatter(x, y, size=15, color=\"maroon\", alpha=0.5, marker=\"square_pin\")\n",
+    "# p.scatter(x, y, size=15, color=\"orange\", alpha=0.5, marker=\"asterisk\")\n",
     "\n",
     "show(p)  # show the results"
    ]
@@ -387,7 +386,7 @@
     "plot.line(x, y)\n",
     "\n",
     "# add scatter markers to the plot\n",
-    "plot.circle_dot(x, y, size=15, color=\"red\", alpha=0.5)\n",
+    "plot.scatter(x, y, size=15, color=\"red\", alpha=0.5, marker=\"circle_dot\")\n",
     "\n",
     "show(plot)"
    ]
@@ -525,13 +524,20 @@
     "Customizing the appearance of your plot is what you'll learn about in the\n",
     "[next chapter](05_styling.ipynb) of this tutorial!"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "global-global-interactive-dataviz-bokeh",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
-   "name": "conda-env-global-global-interactive-dataviz-bokeh-py"
+   "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
@@ -543,7 +549,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.4"
+   "version": "3.12.0"
   },
   "vscode": {
    "interpreter": {

notebooks/03_basic_concepts.ipynb

@@ -113,7 +113,7 @@
     "### Visual properties\n",
     "\n",
     "All the elements of a Bokeh visualization are Python objects. You can customize their\n",
-    "appearance by setting these objects' properties.s\n",
+    "appearance by setting these objects' properties.\n",
     "\n",
     "Bokeh's visual properties work similarly across different kinds of objects.\n",
     "They are organized into four groups:\n",
@@ -254,7 +254,7 @@
     "plot.background_fill_color = \"lightblue\"  # set a background color\n",
     "plot.xgrid.grid_line_color = None  # make the x-axis grid lines invisible\n",
     "\n",
-    "plot.circle([1, 2, 3, 4, 5], [2, 5, 8, 2, 7], size=10)\n",
+    "plot.scatter([1, 2, 3, 4, 5], [2, 5, 8, 2, 7], size=10)\n",
     "\n",
     "show(plot)"
    ]
@@ -279,15 +279,15 @@
     "For example:\n",
     "\n",
     "```python\n",
-    "plot.circle(x, y, fill_color='yellow', line_color='red')\n",
+    "plot.scatter(x, y, fill_color='yellow', line_color='red')\n",
     "```\n",
     "\n",
     "Or you can set the properties of the glyph after you have defined it. To access the\n",
     "visual properties of a glyph after defining it for the first time, use the ``.glyph``\n",
     "attribute. For example:\n",
     "\n",
     "```python\n",
-    "circle = plot.circle(x, y)\n",
+    "circle = plot.scatter(x, y)\n",
     "circle.glyph.fill_color = 'green'\n",
     "circle.glyph.line_color = 'blue'\n",
     "```\n",
@@ -307,7 +307,7 @@
     "plot = figure(height=300)\n",
     "\n",
     "# add a circle glyph and define its colors to be \"yellow\" and \"red\"\n",
-    "circle = plot.circle([1, 2, 3], [2, 5, 8], size=15, fill_color=\"yellow\", line_color=\"red\")\n",
+    "circle = plot.scatter([1, 2, 3], [2, 5, 8], size=15, fill_color=\"yellow\", line_color=\"red\")\n",
     "circle.glyph.fill_color = \"green\"  # use the .glyph attribute to access the visual properties of the glyph\n",
     "circle.glyph.line_color = \"blue\"\n",
     "\n",
@@ -486,7 +486,7 @@
     "attribute when calling the renderer function. For example:\n",
     "\n",
     "```python\n",
-    "p.circle(x, y3, legend_label=\"Temperature\")\n",
+    "p.scatter(x, y3, legend_label=\"Temperature\")\n",
     "```\n",
     "\n",
     "This adds a legend with the entry \"Temperature\" to your plot.\n",
@@ -527,7 +527,7 @@
     "    line_color=\"blue\",\n",
     "    line_width=2,\n",
     ")\n",
-    "circle = legends_plot.circle(\n",
+    "circle = legends_plot.scatter(\n",
     "    x,\n",
     "    y2,\n",
     "    legend_label=\"Objects\",\n",
@@ -633,7 +633,7 @@
     "mapper_plot = figure(width=500, height=250)\n",
     "\n",
     "# create circle renderer with color mapper\n",
-    "circle_scatter = mapper_plot.circle(\n",
+    "circle_scatter = mapper_plot.scatter(\n",
     "    x,\n",
     "    y,\n",
     "    color=linear_cmap(\"y\", \"Turbo256\", min(y), max(y)),\n",
@@ -760,9 +760,9 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "global-global-interactive-dataviz-bokeh",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
-   "name": "conda-env-global-global-interactive-dataviz-bokeh-py"
+   "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
@@ -774,7 +774,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.4"
+   "version": "3.12.0"
   },
   "vscode": {
    "interpreter": {

notebooks/04_basic_plots.ipynb

@@ -92,7 +92,7 @@
     "column names to sequences of values.\n",
     "\n",
     "You can create a ColumnDataSource from Python dictionaries. The keys of the dictionary\n",
-    "are the column names, and the values are the sequences of values:"
+    "are the column names, and the values of the dictionary are the sequences of values:"
    ]
   },
   {
@@ -191,7 +191,7 @@
    "metadata": {},
    "source": [
     "In the examples so far, you have used a Python list or pandas series for the `x` and `y`\n",
-    "values of functions like `p.circle`. This means that Bokeh has created the\n",
+    "values of functions like `p.scatter`. This means that Bokeh has created the\n",
     "ColumnDataSource for you automatically.\n",
     "\n",
     "However, instead of passing individual sequences of values to a renderer, you can also\n",
@@ -225,7 +225,7 @@
     "\n",
     "# create a plot and renderer with ColumnDataSource data\n",
     "p = figure(height=300)\n",
-    "p.circle(\n",
+    "p.scatter(\n",
     "    x=\"x_values\",  # use the sequence in the \"x_values\" column\n",
     "    y=\"y_values\",  # use the sequence in the \"y_values\" column\n",
     "    source=source,  # use the ColumnDataSource as the data source\n",
@@ -423,7 +423,7 @@
     "\n",
     "p = figure(height=300)\n",
     "\n",
-    "p.circle(\n",
+    "p.scatter(\n",
     "    x=\"x\",\n",
     "    y=\"y\",\n",
     "    radius=\"r\",\n",
@@ -467,9 +467,9 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "global-global-interactive-dataviz-bokeh",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
-   "name": "conda-env-global-global-interactive-dataviz-bokeh-py"
+   "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
@@ -481,7 +481,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.12"
+   "version": "3.12.0"
   },
   "vscode": {
    "interpreter": {

notebooks/05_styling.ipynb

@@ -233,7 +233,7 @@
     "from bokeh.plotting import figure\n",
     "\n",
     "p = figure(x_range=(0, 10), y_range=(0, 10), height=300)\n",
-    "p.circle([2, 5, 8], [4, 7, 6], color=\"olive\", size=10)\n",
+    "p.scatter([2, 5, 8], [4, 7, 6], color=\"olive\", size=10)\n",
     "\n",
     "# 🔁 adjust some of the properties of this label\n",
     "# first label, using the same coordinates as the circle (5 on the x-axis and 7 on the y-axis)\n",
@@ -414,9 +414,9 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "global-global-interactive-dataviz-bokeh",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
-   "name": "conda-env-global-global-interactive-dataviz-bokeh-py"
+   "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
@@ -428,7 +428,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.4"
+   "version": "3.12.0"
   },
   "vscode": {
    "interpreter": {