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HTML to ipynb for bubble, bar, area, box, error bar and quiver-plots #1048
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af8454f
HTML to ipynb for bubble, bar, area, box, error bar
priyatharsan 4160d0f
added quiver-plots update
priyatharsan e7d739d
changed bubble chart type to basic, edited description, added permali…
a08d04c
Revert "changed bubble chart type to basic, edited description, added…
priyatharsan 4a536a8
updated the titles, import orders and other reviewed changes
priyatharsan cca2025
updated import order and removed the commented texts
priyatharsan 9d83fdc
reference update
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_posts/matplotlib/area/2015-04-09-area_matplotlib_index.html
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,305 @@ | ||
| { | ||
| "cells": [ | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "\n", | ||
| "#### New to Plotly?\n", | ||
| "Plotly's Python library is free and open source! [Get started](https://plot.ly/python/getting-started/) by downloading the client and [reading the primer](https://plot.ly/python/getting-started/).\n", | ||
| "<br>You can set up Plotly to work in [online](https://plot.ly/python/getting-started/#initialization-for-online-plotting) or [offline](https://plot.ly/python/getting-started/#initialization-for-offline-plotting) mode, or in [jupyter notebooks](https://plot.ly/python/getting-started/#start-plotting-online).\n", | ||
| "<br>We also have a quick-reference [cheatsheet](https://images.plot.ly/plotly-documentation/images/python_cheat_sheet.pdf) (new!) to help you get started!" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "#### Version Check\n", | ||
| "Plotly's python package is updated frequently. Run `pip install plotly --upgrade` to use the latest version." | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 1, | ||
| "metadata": {}, | ||
| "outputs": [ | ||
| { | ||
| "data": { | ||
| "text/plain": [ | ||
| "'3.1.1'" | ||
| ] | ||
| }, | ||
| "execution_count": 1, | ||
| "metadata": {}, | ||
| "output_type": "execute_result" | ||
| } | ||
| ], | ||
| "source": [ | ||
| "import plotly\n", | ||
| "plotly.__version__" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "#### Area Plot" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 2, | ||
| "metadata": {}, | ||
| "outputs": [ | ||
| { | ||
| "data": { | ||
| "text/html": [ | ||
| "<iframe id=\"igraph\" scrolling=\"no\" style=\"border:none;\" seamless=\"seamless\" src=\"https://plot.ly/~priyatharsan/687.embed\" height=\"288px\" width=\"432px\"></iframe>" | ||
| ], | ||
| "text/plain": [ | ||
| "<plotly.tools.PlotlyDisplay object>" | ||
| ] | ||
| }, | ||
| "execution_count": 2, | ||
| "metadata": {}, | ||
| "output_type": "execute_result" | ||
| } | ||
| ], | ||
| "source": [ | ||
| "import matplotlib.pyplot as plt\n", | ||
| "import plotly.plotly as py\n", | ||
| "import plotly.tools as tls\n", | ||
| "\n", | ||
| "# Learn about API authentication here: https://plot.ly/python/getting-started\n", | ||
| "# Find your api_key here: https://plot.ly/settings/api\n", | ||
| "\n", | ||
| "fig, ax = plt.subplots()\n", | ||
| "ax.plot([2,1,3,1,2])\n", | ||
| "\n", | ||
| "update = {'data':[{'fill': 'tozeroy'}]} # this updates the trace\n", | ||
| "plotly_fig = tls.mpl_to_plotly( fig )\n", | ||
| "plotly_fig.update(update)\n", | ||
| "py.iplot(plotly_fig, update=update, filename='mpl-basic-area')" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "#### Multiple Line Area Plot" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 3, | ||
| "metadata": {}, | ||
| "outputs": [ | ||
| { | ||
| "data": { | ||
| "text/html": [ | ||
| "<iframe id=\"igraph\" scrolling=\"no\" style=\"border:none;\" seamless=\"seamless\" src=\"https://plot.ly/~priyatharsan/685.embed\" height=\"288px\" width=\"432px\"></iframe>" | ||
| ], | ||
| "text/plain": [ | ||
| "<plotly.tools.PlotlyDisplay object>" | ||
| ] | ||
| }, | ||
| "execution_count": 3, | ||
| "metadata": {}, | ||
| "output_type": "execute_result" | ||
| } | ||
| ], | ||
| "source": [ | ||
| "import numpy as np\n", | ||
| "import matplotlib.pyplot as plt\n", | ||
| "import plotly.plotly as py\n", | ||
| "import plotly.tools as tls\n", | ||
| "\n", | ||
| "# Learn about API authentication here: https://plot.ly/python/getting-started\n", | ||
| "# Find your api_key here: https://plot.ly/settings/api\n", | ||
| "\n", | ||
| "x = np.linspace(0, 2*np.pi, 100)\n", | ||
| "fig, ax = plt.subplots()\n", | ||
| "ax.plot(np.sin(x), label='sin'); ax.plot(np.cos(x), label='cos')\n", | ||
| "\n", | ||
| "update = {'data':[{'fill': 'tozeroy'}]} # this updates BOTH traces now\n", | ||
| "plotly_fig = tls.mpl_to_plotly( fig )\n", | ||
| "plotly_fig.update(update)\n", | ||
| "py.iplot(plotly_fig, filename='mpl-multi-fill')" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "#### Stacked Line Plot" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 4, | ||
| "metadata": {}, | ||
| "outputs": [ | ||
| { | ||
| "data": { | ||
| "text/html": [ | ||
| "<iframe id=\"igraph\" scrolling=\"no\" style=\"border:none;\" seamless=\"seamless\" src=\"https://plot.ly/~priyatharsan/683.embed\" height=\"288px\" width=\"432px\"></iframe>" | ||
| ], | ||
| "text/plain": [ | ||
| "<plotly.tools.PlotlyDisplay object>" | ||
| ] | ||
| }, | ||
| 10000 "execution_count": 4, | ||
| "metadata": {}, | ||
| "output_type": "execute_result" | ||
| } | ||
| ], | ||
| "source": [ | ||
| "import numpy as np\n", | ||
| "import matplotlib.pyplot as plt\n", | ||
| "import plotly.plotly as py\n", | ||
| "import plotly.tools as tls\n", | ||
| "\n", | ||
| "# Learn about API authentication here: https://plot.ly/python/getting-started\n", | ||
| "# Find your api_key here: https://plot.ly/settings/api\n", | ||
| "\n", | ||
| "# create our stacked data manually\n", | ||
| "y0 = np.random.rand(100)\n", | ||
| "y1 = y0 + np.random.rand(100)\n", | ||
| "y2 = y1 + np.random.rand(100)\n", | ||
| "capacity = 3*np.ones(100)\n", | ||
| "\n", | ||
| "# make the mpl plot (no fill yet)\n", | ||
| "fig, ax = plt.subplots()\n", | ||
| "ax.plot(y0, label='y0')\n", | ||
| "ax.plot(y1, label='y1')\n", | ||
| "ax.plot(y2, label='y2')\n", | ||
| "ax.plot(capacity, label='capacity')\n", | ||
| "\n", | ||
| "# set all traces' \"fill\" so that it fills to the next 'y' trace\n", | ||
| "update = {'data':[{'fill': 'tonexty'}]}\n", | ||
| "\n", | ||
| "# strip style just lets Plotly make the styling choices (e.g., colors)\n", | ||
| "plotly_fig = tls.mpl_to_plotly( fig )\n", | ||
| "plotly_fig.update(update)\n", | ||
| "py.iplot(plotly_fig, strip_style=True, filename='mpl-stacked-line')" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "#### Reference\n", | ||
| "See https://plot.ly/python/filled-area-plots/ for more information and chart attribute options!" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 5, | ||
| "metadata": {}, | ||
| "outputs": [ | ||
| { | ||
| "data": { | ||
| "text/html": [ | ||
| "<link href=\"//fonts.googleapis.com/css?family=Open+Sans:600,400,300,200|Inconsolata|Ubuntu+Mono:400,700\" rel=\"stylesheet\" type=\"text/css\" />" | ||
| ], | ||
| "text/plain": [ | ||
| "<IPython.core.display.HTML object>" | ||
| ] | ||
| }, | ||
| "metadata": {}, | ||
| "output_type": "display_data" | ||
| }, | ||
| { | ||
| "data": { | ||
| "text/html": [ | ||
| "<link rel=\"stylesheet\" type=\"text/css\" href=\"http://help.plot.ly/documentation/all_static/css/ipython-notebook-custom.css\">" | ||
| ], | ||
| "text/plain": [ | ||
| "<IPython.core.display.HTML object>" | ||
| ] | ||
| }, | ||
| "metadata": {}, | ||
| "output_type": "display_data" | ||
| }, | ||
| { | ||
| "name": "stdout", | ||
| "output_type": "stream", | ||
| "text": [ | ||
| "Collecting git+https://github.com/plotly/publisher.git\n", | ||
| " Cloning https://github.com/plotly/publisher.git to c:\\users\\thars\\appdata\\local\\temp\\pip-req-build-j1q7bm\n", | ||
| "Building wheels for collected packages: publisher\n", | ||
| " Running setup.py bdist_wheel for publisher: started\n", | ||
| " Running setup.py bdist_wheel for publisher: finished with status 'done'\n", | ||
| " Stored in directory: c:\\users\\thars\\appdata\\local\\temp\\pip-ephem-wheel-cache-d3mdxz\\wheels\\99\\3e\\a0\\fbd22ba24cca72bdbaba53dbc23c1768755fb17b3af0f33966\n", | ||
| "Successfully built publisher\n", | ||
| "Installing collected packages: publisher\n", | ||
| " Found existing installation: publisher 0.11\n", | ||
| " Uninstalling publisher-0.11:\n", | ||
| " Successfully uninstalled publisher-0.11\n", | ||
| "Successfully installed publisher-0.11\n" | ||
| ] | ||
| }, | ||
| { | ||
| "name": "stderr", | ||
| "output_type": "stream", | ||
| "text": [ | ||
| "C:\\Anaconda\\Anaconda2\\lib\\site-packages\\IPython\\nbconvert.py:13: ShimWarning:\n", | ||
| "\n", | ||
| "The `IPython.nbconvert` package has been deprecated since IPython 4.0. You should import from nbconvert instead.\n", | ||
| "\n", | ||
| "C:\\Anaconda\\Anaconda2\\lib\\site-packages\\publisher\\publisher.py:53: UserWarning:\n", | ||
| "\n", | ||
| "Did you \"Save\" this notebook before running this command? Remember to save, always save.\n", | ||
| "\n" | ||
| ] | ||
| } | ||
| ], | ||
| "source": [ | ||
| "from IPython.display import display, HTML\n", | ||
| "\n", | ||
| "display(HTML('<link href=\"//fonts.googleapis.com/css?family=Open+Sans:600,400,300,200|Inconsolata|Ubuntu+Mono:400,700\" rel=\"stylesheet\" type=\"text/css\" />'))\n", | ||
| "display(HTML('<link rel=\"stylesheet\" type=\"text/css\" href=\"http://help.plot.ly/documentation/all_static/css/ipython-notebook-custom.css\">'))\n", | ||
| "\n", | ||
| "! pip install git+https://github.com/plotly/publisher.git --upgrade\n", | ||
| "import publisher\n", | ||
| "publisher.publish(\n", | ||
| " 'matplotlib_area.ipynb', 'matplotlib/filled-area-pl 95F0 ots/', 'Filled Area Plots',\n", | ||
| " 'How to make a filled area plot in matplotlib. An area chart displays a solid color between the traces of a graph.',\n", | ||
| " title = 'Matplotlib Filled Area Plots | Plotly',\n", | ||
| " has_thumbnail='true', thumbnail='thumbnail/area.jpg',\n", | ||
| " language='matplotlib',\n", | ||
| " page_type='example_index',\n", | ||
| " display_as='basic', ipynb='~notebook_demo/246')" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [] | ||
| } | ||
| ], | ||
| "metadata": { | ||
| "kernelspec": { | ||
| "display_name": "Python 2", | ||
| "language": "python", | ||
| "name": "python2" | ||
| }, | ||
| "language_info": { | ||
| "codemirror_mode": { | ||
| "name": "ipython", | ||
| "version": 2 | ||
| }, | ||
| "file_extension": ".py", | ||
| "mimetype": "text/x-python", | ||
| "name": "python", | ||
| "nbconvert_exporter": "python", | ||
| "pygments_lexer": "ipython2", | ||
| "version": "2.7.14" | ||
| } | ||
| }, | ||
| "nbformat": 4, | ||
| "nbformat_minor": 2 | ||
| } | ||
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Looking at it again, I don't think that we require these commented lines anymore. They seem redundant given that this information is contained in the New to Plotly? section.