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nicolaskruchtennicolaskruchten
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tweaks to Plotly formatting
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‎Examples.ipynb

Lines changed: 60 additions & 50 deletions
Original file line numberDiff line numberDiff line change
@@ -19,7 +19,6 @@
1919
"from plotly import figure_factory\n",
2020
"from plotly import graph_objects\n",
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"import plotly.express as px\n",
22-
"import plotly.io as pio\n",
2322
"from IPython.core.magic import Magics, magics_class, cell_magic\n",
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"\n",
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"from IPython.display import Image\n",
@@ -45,16 +44,10 @@
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") # for plotnine\n",
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"\n",
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"\n",
48-
"fig = graph_objects.Figure(layout = dict(width=100, height=100))\n",
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"\n",
50-
"templated_fig = pio.to_templated(fig)\n",
51-
"pio.templates['my_template'] = templated_fig.layout.template\n",
52-
"pio.templates.default = 'my_template'\n",
53-
"px.defaults.width = 100\n",
54-
"px.defaults.height = 100\n",
47+
"import plotly.io as pio\n",
5548
"pio.renderers.default = \"png\"\n",
56-
"pio.renderers[\"png\"].width = 900\n",
57-
"pio.renderers[\"png\"].height = 900\n",
49+
"pio.renderers[\"png\"].width = 750\n",
50+
"pio.renderers[\"png\"].height = 750\n",
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"\n",
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"alt.renderers.enable('png', webdriver='firefox')"
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]
@@ -292,8 +285,10 @@
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},
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"outputs": [],
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"source": [
295-
"px.histogram(mpg, y=\"manufacturer\", \n",
296-
" title='Number of Cars by Make')"
288+
"px.histogram(\n",
289+
" mpg, y=\"manufacturer\", \n",
290+
" title='Number of Cars by Make'\n",
291+
")"
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]
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},
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{
@@ -407,7 +402,9 @@
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},
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"outputs": [],
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"source": [
410-
"px.histogram(mpg, x=\"cty\")"
405+
"px.histogram(\n",
406+
" mpg, x=\"cty\"\n",
407+
")"
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]
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},
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{
@@ -538,12 +535,13 @@
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},
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"outputs": [],
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"source": [
541-
"px.scatter(mpg, x=\"displ\", y=\"hwy\", \n",
542-
" title='Engine Displacement in Liters vs Highway MPG',\n",
543-
" labels=dict(\n",
544-
" displ='Engine Displacement in Liters', \n",
545-
" hwy='Highway MPG')\n",
546-
" )"
538+
"px.scatter(\n",
539+
" mpg, x=\"displ\", y=\"hwy\", \n",
540+
" title='Engine Displacement in Liters vs Highway MPG',\n",
541+
" labels=dict(\n",
542+
" displ='Engine Displacement in Liters', \n",
543+
" hwy='Highway MPG')\n",
544+
")"
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]
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},
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{
@@ -682,7 +680,7 @@
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"fig.add_trace(p2)\n",
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"fig.add_trace(p3)\n",
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"fig.add_trace(p4)\n",
685-
"Image(fig.to_image(format=\"png\", width=900, height=900))"
683+
"Image(fig.to_image(format=\"png\", width=750, height=750))"
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]
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},
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{
@@ -821,12 +819,13 @@
821819
},
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"outputs": [],
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"source": [
824-
"px.scatter(mpg, x=\"displ\", y=\"hwy\", color=\"class\", \n",
825-
" title='Engine Displacement in Liters vs Highway MPG',\n",
826-
" labels=dict(\n",
827-
" displ='Engine Displacement in Liters', \n",
828-
" hwy='Highway MPG')\n",
829-
" )"
822+
"px.scatter(\n",
823+
" mpg, x=\"displ\", y=\"hwy\", color=\"class\", \n",
824+
" title='Engine Displacement in Liters vs Highway MPG',\n",
825+
" labels=dict(\n",
826+
" displ='Engine Displacement in Liters', \n",
827+
" hwy='Highway MPG')\n",
828+
")"
830829
]
831830
},
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{
@@ -869,7 +868,7 @@
869868
"(\n",
870869
" alt.Chart(\n",
871870
" mpg,\n",
872-
" title=\"Engine Displacement in Liters vs Highway MPG\",\n",
871+
" title=\"City MPG vs Highway MPG\",\n",
873872
" )\n",
874873
" .mark_circle(opacity=0.3)\n",
875874
" .encode(\n",
@@ -907,8 +906,8 @@
907906
" y='hwy', \n",
908907
" s=10*mpg['cyl'],\n",
909908
" alpha=.5))\n",
910-
"ax.set_title('Engine Displacement in Liters vs Highway MPG')\n",
911-
"ax.set_xlabel('Engine Displacement in Liters')\n",
909+
"ax.set_title('City MPG vs Highway MPG')\n",
910+
"ax.set_xlabel('City MPG')\n",
912911
"ax.set_ylabel('Highway MPG');"
913912
]
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},
@@ -941,10 +940,12 @@
941940
},
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"outputs": [],
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"source": [
944-
"px.scatter(mpg, x=\"cty\", y=\"hwy\", size=\"cyl\", size_max=10,\n",
945-
" title='City MPG vs Highway MPG',\n",
946-
" labels=dict(cty='City MPG', hwy='Highway MPG')\n",
947-
" )"
943+
"px.scatter(\n",
944+
" mpg, x=\"cty\", y=\"hwy\", \n",
945+
" size=\"cyl\", size_max=10,\n",
946+
" title='City MPG vs Highway MPG',\n",
947+
" labels=dict(cty='City MPG', hwy='Highway MPG')\n",
948+
")"
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]
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},
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{
@@ -1045,7 +1046,10 @@
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},
10461047
"outputs": [],
10471048
"source": [
1048-
"px.scatter(mpg, x=\"displ\", y=\"hwy\", facet_col=\"class\", facet_col_wrap=4)"
1049+
"px.scatter(\n",
1050+
" mpg, x=\"displ\", y=\"hwy\", \n",
1051+
" facet_col=\"class\", facet_col_wrap=4\n",
1052+
")"
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]
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},
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{
@@ -1150,9 +1154,11 @@
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},
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"outputs": [],
11521156
"source": [
1153-
"px.scatter(mpg, x=\"displ\", y=\"hwy\", \n",
1154-
" facet_col=\"cyl\", facet_row=\"drv\",\n",
1155-
" category_orders=dict(cyl=[4,5,6,8]))"
1157+
"px.scatter(\n",
1158+
" mpg, x=\"displ\", y=\"hwy\", \n",
1159+
" facet_col=\"cyl\", facet_row=\"drv\",\n",
1160+
" category_orders=dict(cyl=[4,5,6,8])\n",
1161+
")"
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]
11571163
},
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{
@@ -1302,7 +1308,7 @@
13021308
" }\n",
13031309
" }\n",
13041310
"})\n",
1305-
"Image(fig.to_image(format=\"png\", width=900, height=900))"
1311+
"Image(fig.to_image(format=\"png\", width=750, height=750))"
13061312
]
13071313
},
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{
@@ -1390,11 +1396,12 @@
13901396
},
13911397
"outputs": [],
13921398
"source": [
1393-
"px.histogram(diamonds, x=\"cut\", color=\"clarity\",\n",
1394-
" category_orders=dict(cut=[\n",
1395-
" \"Fair\", \"Good\", \"Very Good\", \n",
1396-
" \"Premium\", \"Ideal\"])\n",
1397-
" )"
1399+
"px.histogram(\n",
1400+
" diamonds, x=\"cut\", color=\"clarity\",\n",
1401+
" category_orders=dict(cut=[\n",
1402+
" \"Fair\", \"Good\", \"Very Good\", \n",
1403+
" \"Premium\", \"Ideal\"])\n",
1404+
")"
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]
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},
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{
@@ -1485,11 +1492,12 @@
14851492
},
14861493
"outputs": [],
14871494
"source": [
1488-
"px.histogram(diamonds, x=\"cut\", color=\"clarity\", barmode=\"group\",\n",
1489-
" category_orders=dict(cut=[\n",
1490-
" \"Fair\", \"Good\", \"Very Good\", \n",
1491-
" \"Premium\", \"Ideal\"])\n",
1492-
" )"
1495+
"px.histogram(\n",
1496+
" diamonds, x=\"cut\", color=\"clarity\", barmode=\"group\",\n",
1497+
" category_orders=dict(cut=[\n",
1498+
" \"Fair\", \"Good\", \"Very Good\", \n",
1499+
" \"Premium\", \"Ideal\"])\n",
1500+
")"
14931501
]
14941502
},
14951503
{
@@ -1624,7 +1632,7 @@
16241632
")\n",
16251633
"for d in fig[\"data\"]:\n",
16261634
" d.update({\"fill\": \"tozeroy\"})\n",
1627-
"Image(fig.to_image(format=\"png\", width=900, height=900))"
1635+
"Image(fig.to_image(format=\"png\", width=750, height=750))"
16281636
]
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},
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{
@@ -1687,7 +1695,9 @@
16871695
},
16881696
"outputs": [],
16891697
"source": [
1690-
"px.line(ts, x=\"date\", y=\"value\")"
1698+
"px.line(\n",
1699+
" ts, x=\"date\", y=\"value\"\n",
1700+
")"
16911701
]
16921702
},
16931703
{

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