diff --git a/.travis.yml b/.travis.yml
index c05740d..fa25c6d 100644
--- a/.travis.yml
+++ b/.travis.yml
@@ -9,6 +9,8 @@ python:
- '3.7'
notifications:
email: true
+before_install:
+ - nvm install node
install:
- sudo add-apt-repository --yes ppa:marutter/rrutter3.5
- sudo apt-get update --yes
diff --git a/Examples.ipynb b/Examples.ipynb
index d70a77f..9bd04d0 100644
--- a/Examples.ipynb
+++ b/Examples.ipynb
@@ -18,7 +18,7 @@
"\n",
"from plotly import figure_factory\n",
"from plotly import graph_objects\n",
- "import plotly.io as pio\n",
+ "import plotly.express as px\n",
"from IPython.core.magic import Magics, magics_class, cell_magic\n",
"\n",
"from IPython.display import Image\n",
@@ -44,11 +44,10 @@
") # for plotnine\n",
"\n",
"\n",
- "fig = graph_objects.Figure(layout = dict(width=100, height=100))\n",
- "\n",
- "templated_fig = pio.to_templated(fig)\n",
- "pio.templates['my_template'] = templated_fig.layout.template\n",
- "pio.templates.default = 'my_template'\n",
+ "import plotly.io as pio\n",
+ "pio.renderers.default = \"png\"\n",
+ "pio.renderers[\"png\"].width = 750\n",
+ "pio.renderers[\"png\"].height = 750\n",
"\n",
"alt.renderers.enable('png', webdriver='firefox')"
]
@@ -286,17 +285,10 @@
},
"outputs": [],
"source": [
- "mpgGrouped = mpg.groupby('manufacturer').size()\n",
- "fig = graph_objects.Figure(layout={'title' : 'Number of Cars by Make'})\n",
- "bar = graph_objects.Bar({\n",
- " 'type' : 'bar',\n",
- " 'x' : mpgGrouped.values.tolist(),\n",
- " 'y' : mpgGrouped.index.tolist(),\n",
- " 'orientation' : 'h'\n",
- " \n",
- " })\n",
- "fig.add_trace(bar)\n",
- "Image(fig.to_image(format=\"png\", width=900, height=900))"
+ "px.histogram(\n",
+ " mpg, y=\"manufacturer\", \n",
+ " title='Number of Cars by Make'\n",
+ ")"
]
},
{
@@ -410,13 +402,9 @@
},
"outputs": [],
"source": [
- "fig = graph_objects.Figure()\n",
- "hist = graph_objects.Histogram({\n",
- " 'type' : 'histogram',\n",
- " 'x' : mpg['cty'],\n",
- "})\n",
- "fig.add_trace(hist)\n",
- "Image(fig.to_image(format=\"png\", width=900, height=900))"
+ "px.histogram(\n",
+ " mpg, x=\"cty\"\n",
+ ")"
]
},
{
@@ -547,23 +535,13 @@
},
"outputs": [],
"source": [
- "fig = graph_objects.Figure(layout={\n",
- " 'title' : 'Engine Displacement in Liters vs Highway MPG',\n",
- " 'xaxis' : {\n",
- " 'title' : 'Engine Displacement in Liters'\n",
- " },\n",
- " 'yaxis' : {\n",
- " 'title' : 'Highway MPG'\n",
- " }\n",
- "})\n",
- "scatter = graph_objects.Scatter({\n",
- " 'type' : 'scatter',\n",
- " 'mode' : 'markers',\n",
- " 'x' : mpg.displ,\n",
- " 'y' : mpg.hwy \n",
- "})\n",
- "fig.add_trace(scatter)\n",
- "Image(fig.to_image(format=\"png\", width=900, height=900))"
+ "px.scatter(\n",
+ " mpg, x=\"displ\", y=\"hwy\", \n",
+ " title='Engine Displacement in Liters vs Highway MPG',\n",
+ " labels=dict(\n",
+ " displ='Engine Displacement in Liters', \n",
+ " hwy='Highway MPG')\n",
+ ")"
]
},
{
@@ -702,7 +680,7 @@
"fig.add_trace(p2)\n",
"fig.add_trace(p3)\n",
"fig.add_trace(p4)\n",
- "Image(fig.to_image(format=\"png\", width=900, height=900))"
+ "Image(fig.to_image(format=\"png\", width=750, height=750))"
]
},
{
@@ -841,27 +819,13 @@
},
"outputs": [],
"source": [
- "traces = []\n",
- "for cls in mpg[\"class\"].unique():\n",
- " traces.append(\n",
- " graph_objects.Scatter(\n",
- " {\n",
- " \"mode\": \"markers\",\n",
- " \"x\": mpg.displ[mpg[\"class\"] == cls],\n",
- " \"y\": mpg.hwy[mpg[\"class\"] == cls],\n",
- " \"name\": cls,\n",
- " }\n",
- " )\n",
- " )\n",
- "fig = graph_objects.Figure(\n",
- " layout={\n",
- " \"title\": \"Engine Displacement in Liters vs Highway MPG\",\n",
- " \"xaxis\": {\"title\": \"Engine Displacement in Liters\",},\n",
- " \"yaxis\": {\"title\": \"Highway MPG\"},\n",
- " },\n",
- " data=traces,\n",
- ")\n",
- "Image(fig.to_image(format=\"png\", width=900, height=900))"
+ "px.scatter(\n",
+ " mpg, x=\"displ\", y=\"hwy\", color=\"class\", \n",
+ " title='Engine Displacement in Liters vs Highway MPG',\n",
+ " labels=dict(\n",
+ " displ='Engine Displacement in Liters', \n",
+ " hwy='Highway MPG')\n",
+ ")"
]
},
{
@@ -904,7 +868,7 @@
"(\n",
" alt.Chart(\n",
" mpg,\n",
- " title=\"Engine Displacement in Liters vs Highway MPG\",\n",
+ " title=\"City MPG vs Highway MPG\",\n",
" )\n",
" .mark_circle(opacity=0.3)\n",
" .encode(\n",
@@ -942,8 +906,8 @@
" y='hwy', \n",
" s=10*mpg['cyl'],\n",
" alpha=.5))\n",
- "ax.set_title('Engine Displacement in Liters vs Highway MPG')\n",
- "ax.set_xlabel('Engine Displacement in Liters')\n",
+ "ax.set_title('City MPG vs Highway MPG')\n",
+ "ax.set_xlabel('City MPG')\n",
"ax.set_ylabel('Highway MPG');"
]
},
@@ -976,29 +940,12 @@
},
"outputs": [],
"source": [
- "traces = [\n",
- " graph_objects.Scatter(\n",
- " {\n",
- " \"mode\": \"markers\",\n",
- " \"x\": mpg.cty,\n",
- " \"y\": mpg.hwy,\n",
- " \"marker\": {\"size\": mpg.cyl, \"color\": \"rgba(54,54,54,0.5)\"},\n",
- " \"name\": cls,\n",
- " }\n",
- " )\n",
- "]\n",
- "\n",
- "fig = graph_objects.Figure(\n",
- " **{\n",
- " \"data\": traces,\n",
- " \"layout\": {\n",
- " \"title\": \"Engine Displacement in Liters vs Highway MPG\",\n",
- " \"xaxis\": {\"title\": \"Engine Displacement in Liters\",},\n",
- " \"yaxis\": {\"title\": \"Highway MPG\"},\n",
- " },\n",
- " }\n",
- ")\n",
- "Image(fig.to_image(format=\"png\", width=900, height=900))"
+ "px.scatter(\n",
+ " mpg, x=\"cty\", y=\"hwy\", \n",
+ " size=\"cyl\", size_max=10,\n",
+ " title='City MPG vs Highway MPG',\n",
+ " labels=dict(cty='City MPG', hwy='Highway MPG')\n",
+ ")"
]
},
{
@@ -1099,8 +1046,10 @@
},
"outputs": [],
"source": [
- "fig = figure_factory.create_facet_grid(df=mpg, x=\"displ\", y=\"cty\", facet_col=\"class\")\n",
- "Image(fig.to_image(format=\"png\", width=900, height=900))"
+ "px.scatter(\n",
+ " mpg, x=\"displ\", y=\"hwy\", \n",
+ " facet_col=\"class\", facet_col_wrap=4\n",
+ ")"
]
},
{
@@ -1205,14 +1154,11 @@
},
"outputs": [],
"source": [
- "fig = figure_factory.create_facet_grid(\n",
- " df=mpg, \n",
- " x=\"displ\", \n",
- " y=\"cty\", \n",
- " facet_col=\"cyl\", \n",
- " facet_row=\"drv\"\n",
- ")\n",
- "Image(fig.to_image(format=\"png\", width=900, height=900))"
+ "px.scatter(\n",
+ " mpg, x=\"displ\", y=\"hwy\", \n",
+ " facet_col=\"cyl\", facet_row=\"drv\",\n",
+ " category_orders=dict(cyl=[4,5,6,8])\n",
+ ")"
]
},
{
@@ -1362,7 +1308,7 @@
" }\n",
" }\n",
"})\n",
- "Image(fig.to_image(format=\"png\", width=900, height=900))"
+ "Image(fig.to_image(format=\"png\", width=750, height=750))"
]
},
{
@@ -1450,24 +1396,12 @@
},
"outputs": [],
"source": [
- "traces = []\n",
- "newDiamond = diamonds.groupby(['cut','clarity']).size().unstack()\n",
- "for c in newDiamond.columns:\n",
- " traces.append(graph_objects.Bar({\n",
- " 'x' : newDiamond.index,\n",
- " 'y' : newDiamond[c],\n",
- " 'name' : c\n",
- " }))\n",
- "fig = graph_objects.Figure(**{\n",
- " 'data' : traces,\n",
- " 'layout' : {\n",
- " 'barmode' : 'stack',\n",
- " 'xaxis' : {\n",
- " 'title' : 'cut'\n",
- " }, \n",
- " }\n",
- "})\n",
- "Image(fig.to_image(format=\"png\", width=900, height=900))"
+ "px.histogram(\n",
+ " diamonds, x=\"cut\", color=\"clarity\",\n",
+ " category_orders=dict(cut=[\n",
+ " \"Fair\", \"Good\", \"Very Good\", \n",
+ " \"Premium\", \"Ideal\"])\n",
+ ")"
]
},
{
@@ -1558,24 +1492,12 @@
},
"outputs": [],
"source": [
- "traces = []\n",
- "newDiamond = diamonds.groupby(['cut','clarity']).size().unstack()\n",
- "for c in newDiamond.columns:\n",
- " traces.append(graph_objects.Bar({\n",
- " 'x' : newDiamond.index,\n",
- " 'y' : newDiamond[c],\n",
- " 'name' : c\n",
- " }))\n",
- "fig = graph_objects.Figure(**{\n",
- " 'data' : traces,\n",
- " 'layout' : {\n",
- " 'barmode' : 'group',\n",
- " 'xaxis' : {\n",
- " 'title' : 'cut'\n",
- " }, \n",
- " }\n",
- "})\n",
- "Image(fig.to_image(format=\"png\", width=900, height=900))"
+ "px.histogram(\n",
+ " diamonds, x=\"cut\", color=\"clarity\", barmode=\"group\",\n",
+ " category_orders=dict(cut=[\n",
+ " \"Fair\", \"Good\", \"Very Good\", \n",
+ " \"Premium\", \"Ideal\"])\n",
+ ")"
]
},
{
@@ -1710,7 +1632,7 @@
")\n",
"for d in fig[\"data\"]:\n",
" d.update({\"fill\": \"tozeroy\"})\n",
- "Image(fig.to_image(format=\"png\", width=900, height=900))"
+ "Image(fig.to_image(format=\"png\", width=750, height=750))"
]
},
{
@@ -1773,14 +1695,9 @@
},
"outputs": [],
"source": [
- "fig = graph_objects.Figure(layout={'xaxis' : { 'title' : 'date'}})\n",
- "scatter = graph_objects.Scatter({\n",
- " 'mode' :'lines',\n",
- " 'x' : ts.date,\n",
- " 'y' : ts.value\n",
- "})\n",
- "fig.add_trace(scatter)\n",
- "Image(fig.to_image(format=\"png\", width=900, height=900))"
+ "px.line(\n",
+ " ts, x=\"date\", y=\"value\"\n",
+ ")"
]
},
{
@@ -1818,7 +1735,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.7.0"
+ "version": "3.7.7"
}
},
"nbformat": 4,
diff --git a/INTRO.md b/INTRO.md
index 3027c2d..ea93ade 100644
--- a/INTRO.md
+++ b/INTRO.md
@@ -8,9 +8,7 @@ In particular, I make a lot of bar charts (including histograms), line plots (in
Python plotting libraries are manifold. Most well known is Matplotlib.
-"[Matplotlib](https://matplotlib.org/ "Matplotlib: Python plotting") is a Python 2D plotting library which produces publication quality figures in a variety of hardcopy formats and interactive environments across platforms." Native Matplotlib is the cause of [frustration](https://stackoverflow.com/questions/tagged/matplotlib) to many data analysts due to the complex syntax. Much of that frustration would be alleviated if it were recognized as a library of lower level plotting primitives on which other tools can be built.[^frustration]
-
-[^frustration]: If you are frustrated by Matplotlib and haven't read [Effectively Using Matplotlib](http://pbpython.com/effective-matplotlib.html) by [Chris Moffitt](https://twitter.com/chris1610), go read it.
+"[Matplotlib](https://matplotlib.org/ "Matplotlib: Python plotting") is a Python 2D plotting library which produces publication quality figures in a variety of hardcopy formats and interactive environments across platforms." Native Matplotlib is the cause of [frustration](https://stackoverflow.com/questions/tagged/matplotlib) to many data analysts due to the complex syntax. Much of that frustration would be alleviated if it were recognized as a library of lower level plotting primitives on which other tools can be built. (If you are frustrated by Matplotlib and haven't read [Effectively Using Matplotlib](http://pbpython.com/effective-matplotlib.html) by [Chris Moffitt](https://twitter.com/chris1610), go read it.)
#### Matplotlib-Based Libraries
@@ -18,19 +16,16 @@ Many excellent plotting tools are built on top of Matplotlib.
[Pandas plots](https://pandas.pydata.org/pandas-docs/stable/visualization.html "pandas documentation") provides the "basics to easily create decent looking plots" from data frames. It provides about 70% of what I want to do day-to-day. Importantly, it lacks robust faceting capabilities.
-"[plotnine](https://plotnine.readthedocs.io/en/stable/) is an implementation of a grammar of graphics in Python, it is based on ggplot2." plotnine is a recent attempt to directly translate ggplot2 to Python; despite some quirks and bugs, it works very well for a young product.[^ggpy]
+"[plotnine](https://plotnine.readthedocs.io/en/stable/) is an implementation of a grammar of graphics in Python, it is based on ggplot2." plotnine is a attempt to directly translate ggplot2 to Python; despite some quirks and bugs, it works very well for a young product.
"[Seaborn](https://seaborn.pydata.org/ "Seaborn: statistical data visualization") is a Python visualization library based on matplotlib. It provides a high-level interface for drawing attractive statistical graphics." Seaborn makes beautiful plots but is geared toward specific statistical plots, not general purpose plotting. It does have a powerful [faceting utility function](http://seaborn.pydata.org/tutorial/axis_grids.html) that I use regularly.
-[^ggpy]: There is also [ggpy](https://github.com/yhat/ggpy "ggplot port for python"), a ggplot2 port, from the company formerly known as yhat. It appears to be abandoned.
-
#### Interactive Plotting Libraries
There are several tools that can make the kinds of plots described here. At present, I have little experience with them. If anyone would like to help add examples, please [get in touch](https://github.com/tdhopper/pythonplot.com).
-"[Altair](https://altair-viz.github.io/ "Declarative Visualization in Python") is a declarative statistical visualization library for Python, based on [Vega-Lite](https://vega.github.io/vega-lite/ "Vega-Lite: A High-Level Visualization Grammar for Interactive Graphics")." According to Jake Vanderplas, "Declarative visualization lets you think about data and relationships, rather than incidental details."[^jake] I provide Altair examples rendered as static images.
+"[Altair](https://altair-viz.github.io/ "Declarative Visualization in Python") is a declarative statistical visualization library for Python, based on [Vega-Lite](https://vega.github.io/vega-lite/ "Vega-Lite: A High-Level Visualization Grammar for Interactive Graphics")." According to [Jake Vanderplas](https://speakerdeck.com/jakevdp/visualization-in-python-with-altair), "Declarative visualization lets you think about data and relationships, rather than incidental details." I provide Altair examples rendered as static images.
-[^jake]: See [here](https://speakerdeck.com/jakevdp/visualization-in-python-with-altair).
"[plotly](https://plot.ly/ "Plotly - Make charts and dashboards online")'s Python graphing library makes interactive, publication-quality graphs online. Examples of how to make line plots, scatter plots, area charts, bar charts, error bars, box plots, histograms, heatmaps, subplots, multiple-axes, polar charts, and bubble charts." I provide plotly examples rendered as static images.
diff --git a/requirements.txt b/requirements.txt
index 44159dd..b8b7027 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -4,7 +4,7 @@ ipython
pandas
jupyter
seaborn
-plotnine
+plotnine<0.7.0
jinja2
jinja2-highlight
markdown
@@ -12,11 +12,13 @@ scikit-misc
boto3
pytest
chart-studio
-statsmodels==0.10.0rc2 --pre
+statsmodels==0.11.1
rpy2
psutil
-plotly
+plotly==4.10.0
+kaleido
tzlocal
simplegeneric
altair
+altair-saver
selenium
diff --git a/templates/t_index.html b/templates/t_index.html
index 01df5d6..2ab1978 100644
--- a/templates/t_index.html
+++ b/templates/t_index.html
@@ -33,12 +33,8 @@
-
-
-
+
-
-
@@ -58,22 +54,21 @@
-