Move anatomy of a figure image to circumvent GitHub issues

Author: stefmolin

notebooks/1-getting_started_with_matplotlib.ipynb

@@ -1596,7 +1596,7 @@
    ],
    "source": [
     "stackoverflow_monthly.matplotlib.plot(\n",
-    "    figsize=(8, 2), xlabel='creation date', ylabel='total questions', \n",
+    "    figsize=(8, 2), xlabel='creation date', ylabel='total questions',\n",
     "    title='Matplotlib Questions per Month\\n(since the creation of Stack Overflow)'\n",
     ")"
    ]
@@ -1729,7 +1729,7 @@
     "The `Figure` object is the container for all components of our visualization. It contains one or more `Axes` objects, which can be thought of as the (sub)plots, as well as other [*Artists*](https://matplotlib.org/stable/tutorials/intermediate/artists.html), which draw on the plot canvas (x-axis, y-axis, legend, lines, etc.). The following image from the Matplotlib documentation illustrates the different components of a figure:\n",
     "\n",
     "<div style=\"text-align: center;\">\n",
-    "    <img width=\"40%\" src=\"https://raw.githubusercontent.com/stefmolin/python-data-viz-workshop/main/media/figure_anatomy.svg\" alt=\"Matplotlib figure anatomy\" style=\"min-width: 400px\">\n",
+    "    <img width=\"40%\" src=\"../slides/media/figure_anatomy.svg\" alt=\"Matplotlib figure anatomy\" style=\"min-width: 400px\">\n",
     "    <div><small><em><a href=\"https://matplotlib.org/stable/tutorials/introductory/quick_start.html#parts-of-a-figure\">Source</a></em></small></div>\n",
     "</div>"
    ]
@@ -5705,7 +5705,7 @@
    ],
    "source": [
     "ax = stackoverflow_monthly.matplotlib.plot(\n",
-    "    figsize=(8, 2), xlabel='creation date', ylabel='total questions', \n",
+    "    figsize=(8, 2), xlabel='creation date', ylabel='total questions',\n",
     "    title='Matplotlib Questions per Month\\n(since the creation of Stack Overflow)'\n",
     ")\n",
     "ax.set_ylim(0, None) # this can also be done with pandas\n",
@@ -21035,7 +21035,7 @@
     "fig, ax = plt.subplots(figsize=(8, 2))\n",
     "ax.plot(avgs.index, avgs.matplotlib)\n",
     "ax.fill_between(\n",
-    "    avgs.index, avgs.matplotlib - 2 * stds.matplotlib, \n",
+    "    avgs.index, avgs.matplotlib - 2 * stds.matplotlib,\n",
     "    avgs.matplotlib + 2 * stds.matplotlib, alpha=0.25\n",
     ")"
    ]
@@ -33816,7 +33816,7 @@
     "fig, ax = plt.subplots(figsize=(8, 2))\n",
     "ax.plot(avgs.index, avgs.matplotlib)\n",
     "ax.fill_between(\n",
-    "    avgs.index, avgs.matplotlib - 2 * stds.matplotlib, \n",
+    "    avgs.index, avgs.matplotlib - 2 * stds.matplotlib,\n",
     "    avgs.matplotlib + 2 * stds.matplotlib, alpha=0.25\n",
     ")\n",
     "\n",
@@ -34590,7 +34590,7 @@
     "fig, ax = plt.subplots(figsize=(9, 3))\n",
     "ax.plot(\n",
     "    stackoverflow_monthly.index,\n",
-    "    stackoverflow_monthly.matplotlib, \n",
+    "    stackoverflow_monthly.matplotlib,\n",
     "    'ok', label=None, alpha=0.5\n",
     ")"
    ]
@@ -35395,7 +35395,7 @@
    "source": [
     "fig, ax = plt.subplots(figsize=(9, 3))\n",
     "ax.plot(\n",
-    "    x_axis_dates, stackoverflow_monthly.matplotlib, \n",
+    "    x_axis_dates, stackoverflow_monthly.matplotlib,\n",
     "    'ok', label=None, alpha=0.5\n",
     ")"
    ]
@@ -44476,7 +44476,7 @@
    "source": [
     "fig, ax = plt.subplots(figsize=(12, 3))\n",
     "ax.stackplot(\n",
-    "    mdates.date2num(top_libraries_monthly.index), top_libraries_monthly.to_numpy().T, \n",
+    "    mdates.date2num(top_libraries_monthly.index), top_libraries_monthly.to_numpy().T,\n",
     "    labels=top_libraries_monthly.columns\n",
     ")\n",
     "ax.set(xlabel='', ylabel='tagged questions', title='Stack Overflow Questions per Month')\n",
@@ -44509,7 +44509,7 @@
     "    fig, ax = plt.subplots(figsize=(12, 3))\n",
     "    ax.stackplot(\n",
     "        mdates.date2num(data.index),\n",
-    "        data.to_numpy().T, \n",
+    "        data.to_numpy().T,\n",
     "        labels=data.columns\n",
     "    )\n",
     "    ax.set(\n",
@@ -47195,7 +47195,7 @@
     "    fig, ax = plt.subplots(figsize=(12, 3))\n",
     "    ax.stackplot(\n",
     "        mdates.date2num(data.index),\n",
-    "        data.to_numpy().T, \n",
+    "        data.to_numpy().T,\n",
     "        labels=data.columns\n",
     "    )\n",
     "    ax.set(\n",
@@ -49833,7 +49833,7 @@
     "import datetime as dt\n",
     "\n",
     "ax = area_plot(top_libraries_monthly)\n",
-    "    \n",
+    "\n",
     "# mark when seaborn was created\n",
     "seaborn_released = dt.date(2013, 10, 28)\n",
     "ax.axvline(seaborn_released, ymax=0.6, color='gray', linestyle='dashed')\n",
@@ -55159,8 +55159,8 @@
     ")\n",
     "middle = (seaborn_released - first_seaborn_qs) / 2 + first_seaborn_qs\n",
     "ax.annotate(\n",
-    "    'posts retroactively\\ntagged \"seaborn\"', \n",
-    "    xy=(mdates.date2num(middle), 3500), \n",
+    "    'posts retroactively\\ntagged \"seaborn\"',\n",
+    "    xy=(mdates.date2num(middle), 3500),\n",
     "    va='top', ha='center'\n",
     ")"
    ]
@@ -55210,7 +55210,7 @@
     "    fig, ax = plt.subplots(figsize=(12, 3))\n",
     "    ax.stackplot(\n",
     "        mdates.date2num(data.index),\n",
-    "        data.to_numpy().T, \n",
+    "        data.to_numpy().T,\n",
     "        labels=data.columns\n",
     "    )\n",
     "    ax.set(\n",
@@ -63637,7 +63637,7 @@
     "\n",
     "total_qs = top_libraries_monthly.sum()\n",
     "inset_ax.barh(\n",
-    "    total_qs.index, total_qs.to_numpy(), \n",
+    "    total_qs.index, total_qs.to_numpy(),\n",
     "    color=[colors[label] for label in total_qs.index]\n",
     ")\n",
     "inset_ax.yaxis.set_inverted(True)\n",
@@ -68368,7 +68368,7 @@
     "        co_occurring_library = data[library]\n",
     "        ax.barh(libraries, co_occurring_library, label=library, left=last)\n",
     "        last += co_occurring_library\n",
-    "    \n",
+    "\n",
     "    ax.yaxis.set_inverted(True)\n",
     "    return despine(ax)"
    ]
@@ -73752,7 +73752,7 @@
     "        co_occurring_library = data[library]\n",
     "        ax.barh(libraries, co_occurring_library, label=library, left=last)\n",
     "        last += co_occurring_library\n",
-    "    \n",
+    "\n",
     "    ax.yaxis.set_inverted(True)\n",
     "    ax.legend(bbox_to_anchor=(1.35, 0.5), loc='center right', framealpha=0.5)\n",
     "    ax.set(xlabel='percentage of questions with co-occurrences', xlim=(0, 1))\n",
@@ -76160,11 +76160,11 @@
     "    for i, library in enumerate(libraries):\n",
     "        co_occurring_library = data[library]\n",
     "        ax.barh(\n",
-    "            libraries, co_occurring_library, \n",
+    "            libraries, co_occurring_library,\n",
     "            label=library, left=last, color=cmap(i)\n",
     "        )\n",
     "        last += co_occurring_library\n",
-    "    \n",
+    "\n",
     "    ax.yaxis.set_inverted(True)\n",
     "    ax.legend(bbox_to_anchor=(1.35, 0.5), loc='center right', framealpha=0.5)\n",
     "    ax.set(xlabel='percentage of questions with co-occurrences', xlim=(0, 1))\n",
@@ -78628,7 +78628,7 @@
    ],
    "source": [
     "subway = pd.read_csv(\n",
-    "    '../data/NYC_subway_daily.csv', parse_dates=['Datetime'], \n",
+    "    '../data/NYC_subway_daily.csv', parse_dates=['Datetime'],\n",
     "    index_col=['Borough', 'Datetime']\n",
     ")\n",
     "subway_daily = subway.unstack(0)\n",
@@ -84537,7 +84537,7 @@
     "\n",
     "    axes[0].set_ylabel('Frequency')\n",
     "    fig.suptitle('Histogram of Daily Subway Entries in Manhattan')\n",
-    "    \n",
+    "\n",
     "    return fig, axes"
    ]
   },

slides/1-getting_started_with_matplotlib.ipynb

@@ -1620,7 +1620,7 @@
    ],
    "source": [
     "stackoverflow_monthly.matplotlib.plot(\n",
-    "    figsize=(8, 2), xlabel='creation date', ylabel='total questions', \n",
+    "    figsize=(8, 2), xlabel='creation date', ylabel='total questions',\n",
     "    title='Matplotlib Questions per Month\\n(since the creation of Stack Overflow)'\n",
     ")"
    ]
@@ -1774,7 +1774,7 @@
     "The `Figure` object is the container for all components of our visualization. It contains one or more `Axes` objects, which can be thought of as the (sub)plots, as well as other [*Artists*](https://matplotlib.org/stable/tutorials/intermediate/artists.html), which draw on the plot canvas (x-axis, y-axis, legend, lines, etc.). The following image from the Matplotlib documentation illustrates the different components of a figure:\n",
     "\n",
     "<div style=\"text-align: center;\">\n",
-    "    <img width=\"40%\" src=\"https://raw.githubusercontent.com/stefmolin/python-data-viz-workshop/main/media/figure_anatomy.svg\" alt=\"Matplotlib figure anatomy\" style=\"min-width: 400px\">\n",
+    "    <img width=\"40%\" src=\"media/figure_anatomy.svg\" alt=\"Matplotlib figure anatomy\" style=\"min-width: 400px\">\n",
     "    <div><small><em><a href=\"https://matplotlib.org/stable/tutorials/introductory/quick_start.html#parts-of-a-figure\">Source</a></em></small></div>\n",
     "</div>"
    ]
@@ -5750,7 +5750,7 @@
    ],
    "source": [
     "ax = stackoverflow_monthly.matplotlib.plot(\n",
-    "    figsize=(8, 2), xlabel='creation date', ylabel='total questions', \n",
+    "    figsize=(8, 2), xlabel='creation date', ylabel='total questions',\n",
     "    title='Matplotlib Questions per Month\\n(since the creation of Stack Overflow)'\n",
     ")\n",
     "ax.set_ylim(0, None) # this can also be done with pandas\n",
@@ -21101,7 +21101,7 @@
     "fig, ax = plt.subplots(figsize=(8, 2))\n",
     "ax.plot(avgs.index, avgs.matplotlib)\n",
     "ax.fill_between(\n",
-    "    avgs.index, avgs.matplotlib - 2 * stds.matplotlib, \n",
+    "    avgs.index, avgs.matplotlib - 2 * stds.matplotlib,\n",
     "    avgs.matplotlib + 2 * stds.matplotlib, alpha=0.25\n",
     ")"
    ]
@@ -33882,7 +33882,7 @@
     "fig, ax = plt.subplots(figsize=(8, 2))\n",
     "ax.plot(avgs.index, avgs.matplotlib)\n",
     "ax.fill_between(\n",
-    "    avgs.index, avgs.matplotlib - 2 * stds.matplotlib, \n",
+    "    avgs.index, avgs.matplotlib - 2 * stds.matplotlib,\n",
     "    avgs.matplotlib + 2 * stds.matplotlib, alpha=0.25\n",
     ")\n",
     "\n",
@@ -34658,7 +34658,7 @@
     "fig, ax = plt.subplots(figsize=(9, 3))\n",
     "ax.plot(\n",
     "    stackoverflow_monthly.index,\n",
-    "    stackoverflow_monthly.matplotlib, \n",
+    "    stackoverflow_monthly.matplotlib,\n",
     "    'ok', label=None, alpha=0.5\n",
     ")"
    ]
@@ -35463,7 +35463,7 @@
    "source": [
     "fig, ax = plt.subplots(figsize=(9, 3))\n",
     "ax.plot(\n",
-    "    x_axis_dates, stackoverflow_monthly.matplotlib, \n",
+    "    x_axis_dates, stackoverflow_monthly.matplotlib,\n",
     "    'ok', label=None, alpha=0.5\n",
     ")"
    ]
@@ -40384,7 +40384,7 @@
     "    ax.xaxis.set_major_formatter(mdates.DateFormatter('%b\\n%Y'))\n",
     "\n",
     "    ax.fill_between(\n",
-    "        la_tavg.index, la_tavg, nyc_tavg, where=nyc_tavg > la_tavg, \n",
+    "        la_tavg.index, la_tavg, nyc_tavg, where=nyc_tavg > la_tavg,\n",
     "        hatch='///', facecolor='gray', alpha=0.5, label='NYC hotter than LA'\n",
     "    )\n",
     "    ax.legend(ncols=3, loc='lower center')\n",
@@ -47037,7 +47037,7 @@
    "source": [
     "fig, ax = plt.subplots(figsize=(12, 3))\n",
     "ax.stackplot(\n",
-    "    mdates.date2num(top_libraries_monthly.index), top_libraries_monthly.to_numpy().T, \n",
+    "    mdates.date2num(top_libraries_monthly.index), top_libraries_monthly.to_numpy().T,\n",
     "    labels=top_libraries_monthly.columns\n",
     ")\n",
     "ax.set(xlabel='', ylabel='tagged questions', title='Stack Overflow Questions per Month')\n",
@@ -47070,7 +47070,7 @@
     "    fig, ax = plt.subplots(figsize=(12, 3))\n",
     "    ax.stackplot(\n",
     "        mdates.date2num(data.index),\n",
-    "        data.to_numpy().T, \n",
+    "        data.to_numpy().T,\n",
     "        labels=data.columns\n",
     "    )\n",
     "    ax.set(\n",
@@ -49756,7 +49756,7 @@
     "    fig, ax = plt.subplots(figsize=(12, 3))\n",
     "    ax.stackplot(\n",
     "        mdates.date2num(data.index),\n",
-    "        data.to_numpy().T, \n",
+    "        data.to_numpy().T,\n",
     "        labels=data.columns\n",
     "    )\n",
     "    ax.set(\n",
@@ -52394,7 +52394,7 @@
     "import datetime as dt\n",
     "\n",
     "ax = area_plot(top_libraries_monthly)\n",
-    "    \n",
+    "\n",
     "# mark when seaborn was created\n",
     "seaborn_released = dt.date(2013, 10, 28)\n",
     "ax.axvline(seaborn_released, ymax=0.6, color='gray', linestyle='dashed')\n",
@@ -57720,8 +57720,8 @@
     ")\n",
     "middle = (seaborn_released - first_seaborn_qs) / 2 + first_seaborn_qs\n",
     "ax.annotate(\n",
-    "    'posts retroactively\\ntagged \"seaborn\"', \n",
-    "    xy=(mdates.date2num(middle), 3500), \n",
+    "    'posts retroactively\\ntagged \"seaborn\"',\n",
+    "    xy=(mdates.date2num(middle), 3500),\n",
     "    va='top', ha='center'\n",
     ")"
    ]
@@ -57773,7 +57773,7 @@
     "    fig, ax = plt.subplots(figsize=(12, 3))\n",
     "    ax.stackplot(\n",
     "        mdates.date2num(data.index),\n",
-    "        data.to_numpy().T, \n",
+    "        data.to_numpy().T,\n",
     "        labels=data.columns\n",
     "    )\n",
     "    ax.set(\n",
@@ -66200,7 +66200,7 @@
     "\n",
     "total_qs = top_libraries_monthly.sum()\n",
     "inset_ax.barh(\n",
-    "    total_qs.index, total_qs.to_numpy(), \n",
+    "    total_qs.index, total_qs.to_numpy(),\n",
     "    color=[colors[label] for label in total_qs.index]\n",
     ")\n",
     "inset_ax.yaxis.set_inverted(True)\n",
@@ -72555,7 +72555,7 @@
     "        co_occurring_library = data[library]\n",
     "        ax.barh(libraries, co_occurring_library, label=library, left=last)\n",
     "        last += co_occurring_library\n",
-    "    \n",
+    "\n",
     "    ax.yaxis.set_inverted(True)\n",
     "    return despine(ax)"
    ]
@@ -77939,7 +77939,7 @@
     "        co_occurring_library = data[library]\n",
     "        ax.barh(libraries, co_occurring_library, label=library, left=last)\n",
     "        last += co_occurring_library\n",
-    "    \n",
+    "\n",
     "    ax.yaxis.set_inverted(True)\n",
     "    ax.legend(bbox_to_anchor=(1.35, 0.5), loc='center right', framealpha=0.5)\n",
     "    ax.set(xlabel='percentage of questions with co-occurrences', xlim=(0, 1))\n",
@@ -80347,11 +80347,11 @@
     "    for i, library in enumerate(libraries):\n",
     "        co_occurring_library = data[library]\n",
     "        ax.barh(\n",
-    "            libraries, co_occurring_library, \n",
+    "            libraries, co_occurring_library,\n",
     "            label=library, left=last, color=cmap(i)\n",
     "        )\n",
     "        last += co_occurring_library\n",
-    "    \n",
+    "\n",
     "    ax.yaxis.set_inverted(True)\n",
     "    ax.legend(bbox_to_anchor=(1.35, 0.5), loc='center right', framealpha=0.5)\n",
     "    ax.set(xlabel='percentage of questions with co-occurrences', xlim=(0, 1))\n",
@@ -82836,7 +82836,7 @@
     "        )\n",
     "        last += prcp\n",
     "\n",
-    "    ax.set_xlabel('2020 total precipitation (inches)') \n",
+    "    ax.set_xlabel('2020 total precipitation (inches)')\n",
     "    ax.set_title('Total Precipitation per City in 2020', y=1.1)\n",
     "    ax.axvline(total_prcp['Seattle'], linestyle='--', color='gray')\n",
     "    ax.legend(bbox_to_anchor=(0.5, 1.15), loc='upper center', ncols=4, frameon=False)\n",
@@ -84824,7 +84824,7 @@
    ],
    "source": [
     "subway = pd.read_csv(\n",
-    "    '../data/NYC_subway_daily.csv', parse_dates=['Datetime'], \n",
+    "    '../data/NYC_subway_daily.csv', parse_dates=['Datetime'],\n",
     "    index_col=['Borough', 'Datetime']\n",
     ")\n",
     "subway_daily = subway.unstack(0)\n",
@@ -90733,7 +90733,7 @@
     "\n",
     "    axes[0].set_ylabel('Frequency')\n",
     "    fig.suptitle('Histogram of Daily Subway Entries in Manhattan')\n",
-    "    \n",
+    "\n",
     "    return fig, axes"
    ]
   },