{ "metadata": { "name": "", "signature": "sha256:26161b06285113e30fa6627e1e608dff9317251f5a67ac6ee04951510510d270" }, "nbformat": 3, "nbformat_minor": 0, "worksheets": [ { "cells": [ { "cell_type": "heading", "level": 1, "metadata": {}, "source": [ "How to make beautiful
\n", "data visualizations " ] }, { "cell_type": "heading", "level": 2, "metadata": {}, "source": [ "in Python with matplotlib and Plotly" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This notebook comes in response to this twitter conversation about converting a certain matplotlib figure featured in Randal S. Olson blog post (link here and embedded below).\n", "\n", "
\n", "**July 07 2014 EDIT**: \n", "\n", "Plotly's matplotlib converter has been upgraded in the past week and is now distributed in the new latest version of Plotly's Python package `plotly 1.1.2`. These upgrades make the conversion of this particular matplotlib plot (shown below) significantly easier.\n", "\n", "
" ] }, { "cell_type": "code", "collapsed": false, "input": [ "from IPython.display import IFrame\n", "IFrame(\"http://www.randalolson.com/2014/06/28/\"\n", " \"how-to-make-beautiful-data-visualizations-in-python-with-matplotlib/\", \n", " 720, 400)" ], "language": "python", "metadata": {}, "outputs": [ { "html": [ "\n", " \n", " " ], "metadata": {}, "output_type": "pyout", "prompt_number": 1, "text": [ "" ] } ], "prompt_number": 1 }, { "cell_type": "markdown", "metadata": {}, "source": [ "For this particular figure, " ] }, { "cell_type": "code", "collapsed": false, "input": [ "IFrame(\"http://www.randalolson.com/wp-content/uploads/\"\n", " \"percent-bachelors-degrees-women-usa.png\",\n", " 1000, 1000)" ], "language": "python", "metadata": {}, "outputs": [ { "html": [ "\n", " \n", " " ], "metadata": {}, "output_type": "pyout", "prompt_number": 2, "text": [ "" ] } ], "prompt_number": 2 }, { "cell_type": "markdown", "metadata": {}, "source": [ "
\n", "\n", "\n", "In brief, we will show you how programmatically remake what Plotly user Dreamshot made here.\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "
\n", "
\n", "
" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "First, check the version which version of the Python API installed on your machine:" ] }, { "cell_type": "code", "collapsed": false, "input": [ "import plotly\n", "plotly.__version__" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 3, "text": [ "'1.1.2'" ] } ], "prompt_number": 3 }, { "cell_type": "markdown", "metadata": {}, "source": [ "If not the latest (version 1.1.2), upgrade using `pip`:\n", "\n", " $ pip install plotly --upgrade" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Next, if you have a plotly account as well as a credentials file set up on your machine, singing in to Plotly's servers is done automatically while importing `plotly.plotly`:" ] }, { "cell_type": "code", "collapsed": false, "input": [ "import plotly.plotly as py " ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 4 }, { "cell_type": "markdown", "metadata": {}, "source": [ "For more info on how to sign up or sign in to Plotly, see Plotly's Python API User Guide\n", "\n", "If more convenient, you can manually sign in to Plotly by typing:\n", " >>> py.sign_in('your_username','your_api_key')\n", " \n", "We also make use of Plotly's `tools` module in this notebook; import it here:" ] }, { "cell_type": "code", "collapsed": false, "input": [ "import plotly.tools as tls" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 5 }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "Original matplotlib figure" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "First, remake the original matplotlib figure. The following code cell was copied verbatim from the Randal S. Olsen's blog post with the exception of the last line where we grab the underlying figure object and link it to a variable named `dataviz1`." ] }, { "cell_type": "code", "collapsed": false, "input": [ "%pylab inline \n", "from pandas import read_csv \n", " \n", "# Read the data into a pandas DataFrame. \n", "gender_degree_data = read_csv(\"http://www.randalolson.com/wp-content/uploads/\"\n", " \"percent-bachelors-degrees-women-usa.csv\") \n", " \n", "# These are the \"Tableau 20\" colors as RGB. \n", "tableau20 = [(31, 119, 180), (174, 199, 232), (255, 127, 14), (255, 187, 120), \n", " (44, 160, 44), (152, 223, 138), (214, 39, 40), (255, 152, 150), \n", " (148, 103, 189), (197, 176, 213), (140, 86, 75), (196, 156, 148), \n", " (227, 119, 194), (247, 182, 210), (127, 127, 127), (199, 199, 199), \n", " (188, 189, 34), (219, 219, 141), (23, 190, 207), (158, 218, 229)] \n", " \n", "# Scale the RGB values to the [0, 1] range, which is the format matplotlib accepts. \n", "for i in range(len(tableau20)): \n", " r, g, b = tableau20[i] \n", " tableau20[i] = (r / 255., g / 255., b / 255.) \n", " \n", "# You typically want your plot to be ~1.33x wider than tall. This plot is a rare \n", "# exception because of the number of lines being plotted on it. \n", "# Common sizes: (10, 7.5) and (12, 9) \n", "figure(figsize=(12, 14)) \n", " \n", "# Remove the plot frame lines. They are unnecessary chartjunk. \n", "ax = subplot(111) \n", "ax.spines[\"top\"].set_visible(False) \n", "ax.spines[\"bottom\"].set_visible(False) \n", "ax.spines[\"right\"].set_visible(False) \n", "ax.spines[\"left\"].set_visible(False) \n", " \n", "# Ensure that the axis ticks only show up on the bottom and left of the plot. \n", "# Ticks on the right and top of the plot are generally unnecessary chartjunk. \n", "ax.get_xaxis().tick_bottom() \n", "ax.get_yaxis().tick_left() \n", " \n", "# Limit the range of the plot to only where the data is. \n", "# Avoid unnecessary whitespace. \n", "ylim(0, 90) \n", "xlim(1968, 2014) \n", " \n", "# Make sure your axis ticks are large enough to be easily read. \n", "# You don't want your viewers squinting to read your plot. \n", "yticks(range(0, 91, 10), [str(x) + \"%\" for x in range(0, 91, 10)], fontsize=14) \n", "xticks(fontsize=14) \n", " \n", "# Provide tick lines across the plot to help your viewers trace along \n", "# the axis ticks. Make sure that the lines are light and small so they \n", "# don't obscure the primary data lines. \n", "for y in range(10, 91, 10): \n", " plot(range(1968, 2012), [y] * len(range(1968, 2012)), \"--\", \n", " lw=0.5, color=\"black\", alpha=0.3) \n", " \n", "# Remove the tick marks; they are unnecessary with the tick lines we just plotted. \n", "plt.tick_params(axis=\"both\", which=\"both\", bottom=\"off\", top=\"off\", \n", " labelbottom=\"on\", left=\"off\", right=\"off\", labelleft=\"on\") \n", " \n", "# Now that the plot is prepared, it's time to actually plot the data! \n", "# Note that I plotted the majors in order of the highest % in the final year. \n", "majors = ['Health Professions', 'Public Administration', 'Education', 'Psychology', \n", " 'Foreign Languages', 'English', 'Communications\\nand Journalism', \n", " 'Art and Performance', 'Biology', 'Agriculture', \n", " 'Social Sciences and History', 'Business', 'Math and Statistics', \n", " 'Architecture', 'Physical Sciences', 'Computer Science', \n", " 'Engineering'] \n", " \n", "for rank, column in enumerate(majors): \n", " # Plot each line separately with its own color, using the Tableau 20 \n", " # color set in order. \n", " plot(gender_degree_data.Year.values, \n", " gender_degree_data[column.replace(\"\\n\", \" \")].values, \n", " lw=2.5, color=tableau20[rank]) \n", " \n", " # Add a text label to the right end of every line. Most of the code below \n", " # is adding specific offsets y position because some labels overlapped. \n", " y_pos = gender_degree_data[column.replace(\"\\n\", \" \")].values[-1] - 0.5 \n", " if column == \"Foreign Languages\": \n", " y_pos += 0.5 \n", " elif column == \"English\": \n", " y_pos -= 0.5 \n", " elif column == \"Communications\\nand Journalism\": \n", " y_pos += 0.75 \n", " elif column == \"Art and Performance\": \n", " y_pos -= 0.25 \n", " elif column == \"Agriculture\": \n", " y_pos += 1.25 \n", " elif column == \"Social Sciences and History\": \n", " y_pos += 0.25 \n", " elif column == \"Business\": \n", " y_pos -= 0.75 \n", " elif column == \"Math and Statistics\": \n", " y_pos += 0.75 \n", " elif column == \"Architecture\": \n", " y_pos -= 0.75 \n", " elif column == \"Computer Science\": \n", " y_pos += 0.75 \n", " elif column == \"Engineering\": \n", " y_pos -= 0.25 \n", " \n", " # Again, make sure that all labels are large enough to be easily read \n", " # by the viewer. \n", " text(2011.5, y_pos, column, fontsize=14, color=tableau20[rank]) \n", " \n", "# matplotlib's title() call centers the title on the plot, but not the graph, \n", "# so I used the text() call to customize where the title goes. \n", " \n", "# Make the title big enough so it spans the entire plot, but don't make it \n", "# so big that it requires two lines to show. \n", " \n", "# Note that if the title is descriptive enough, it is unnecessary to include \n", "# axis labels; they are self-evident, in this plot's case. \n", "text(1995, 93, \"Percentage of Bachelor's degrees conferred to women in the U.S.A.\" \n", " \", by major (1970-2012)\", fontsize=17, ha=\"center\") \n", " \n", "# Always include your data source(s) and copyright notice! And for your \n", "# data sources, tell your viewers exactly where the data came from, \n", "# preferably with a direct link to the data. Just telling your viewers \n", "# that you used data from the \"U.S. Census Bureau\" is completely useless: \n", "# the U.S. Census Bureau provides all kinds of data, so how are your \n", "# viewers supposed to know which data set you used? \n", "text(1966, -8, \"Data source: nces.ed.gov/programs/digest/2013menu_tables.asp\" \n", " \"\\nAuthor: Randy Olson (randalolson.com / @randal_olson)\" \n", " \"\\nNote: Some majors are missing because the historical data \" \n", " \"is not available for them\", fontsize=10) \n", " \n", "# Finally, save the figure as a PNG. \n", "# You can also save it as a PDF, JPEG, etc. \n", "# Just change the file extension in this call. \n", "# bbox_inches=\"tight\" removes all the extra whitespace on the edges of your plot. \n", "#savefig(\"percent-bachelors-degrees-women-usa.png\", bbox_inches=\"tight\"); \n", "\n", "# (!) Grab figure object and link it to variable (must be in same cell as figure)\n", "dataviz1 = gcf()" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "Populating the interactive namespace from numpy and matplotlib\n" ] }, { "metadata": {}, "output_type": "display_data", "png": 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PBTjXQBqIao8wX/MMqzHeNkQejkI60BvMj7/r+M62O3z+W6Ypw83iWMxHTGeWMbixTzO/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pt+GbfMu4WilHG0sPc5RcSsbgt4OmO3pRRA3krImA3q4ds8tLvbuWfTPXxQ/wEgPsvqeav5+oKv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HerSe5cxP46JbpxJjl9azoRIKBqjYupmydas5sPkTQoHAoI8N+nw4fT5obRnU/tbY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/0gQOV/lFNUnjru+GjB6xjkwN/+jCwFsSQmsfTO+xCjLO1UQ+NKoq9jiFMH2gkGVFMCS5yR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\nxYopCTQNjWhCeyePILJPY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RdlbsETneBVswP0pZmaQNPQ0NDQuCCaSItCZL+f1ocfxnuo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\n512PNXPwkfp1ntXGpOvNnxPquQRA+6eewO3zL2mcaDRKZ2cnoC+e9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/xOIWX1RqiqyqVL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\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0YO57gCv7+KPAfwB+FPhd4B+A4uxjuegB3M/fwnWIdRAYGTG+t6dT5JdXkYynyB0JYc7W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"text": [ "" ] } ], "prompt_number": 6 }, { "cell_type": "markdown", "metadata": {}, "source": [ "
\n", "\n", "Plotly allows you to convert a matplotlib figure object (`dataviz1` in our case here) into a Plotly figure with one line of code:" ] }, { "cell_type": "code", "collapsed": false, "input": [ "py.iplot_mpl(dataviz1, resize=False, filename='dataviz1', width=960, height=1120)" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stderr", "text": [ "/usr/local/lib/python2.7/dist-packages/plotly/matplotlylib/renderer.py:506: UserWarning:\n", "\n", "Looks like the annotation(s) you are trying \n", "to draw lies/lay outside the given figure size.\n", "\n", "Therefore, the resulting Plotly figure may not be \n", "large enough to view the full text. To adjust \n", "the size of the figure, use the 'width' and \n", "'height' keys in the Layout object. Alternatively,\n", "use the Margin object to adjust the figure's margins.\n", "\n", "/usr/local/lib/python2.7/dist-packages/plotly/tools.py:534: UserWarning:\n", "\n", "Looks like you used a newline character: '\\n'.\n", "\n", "Plotly uses a subset of HTML escape characters\n", "to do things like newline (
), bold (),\n", "italics (), etc. Your newline characters \n", "have been converted to '
' so they will show \n", "up right on your Plotly figure!\n", "\n" ] }, { "html": [ "" ], "metadata": {}, "output_type": "display_data", "text": [ "" ] } ], "prompt_number": 7 }, { "cell_type": "markdown", "metadata": {}, "source": [ "where the `resize=False` keyword argument tells Plotly to not set the figure's size to the default Plotly dimensions. Keyword argument `width` and `height` set the dimensions of the display box shown in this notebook.\n", "\n", "To view the graph in a different tab, click on the *data and graph* button on the bottom right corner of the plot which leads you to the figure's unique URL.\n", "\n", "While plotting, `py.iplot_mpl()` spew out two warnings:\n", "\n", "* *Looks like the annotation(s) you are trying to draw lies/lay outside the given figure size.*\n", "\n", "This means that the original matplotlib figure contain annotation(s) lying outside the figure's margins. Upon printing (either using `savefig()` or in the `matplotlib inline`) matplotlib adjusts the margins to fit all the annotations. In contrast, running `show()` would yield truncation annotation(s). \n", "\n", "So, we will have to adjust the margin slightly. \n", "\n", "* *Looks like you used a newline character: '\\n'.*\n", "\n", "Plotly uses a subset of HTML syntax to do insert new line in strings. In version 1.1.2 of the Python API, all `\\n ` escape sequences are converted went sent to Plotly to `
` so that multi-line string render as desired.\n", "\n", "Moreover, looking more closely at the Plotly figure, \n", "\n", "* Converting ticks (or the lack of ticks) is still an issue (that we are currently trying to fix), so we will have to remove them in this Python session.\n", "\n", "* The title is not exactly at the same position as on the original matplotlib figure. Therefore, we will add a Plotly title which addiontinally will make the figure's URL more descriptive.\n", "\n", "* And finally, we will make full use of Plotly's interactibility by adding hover text to the data traces." ] }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "Plotly version" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "So, first let's convert the matplotlib figure object to a Plotly figure object:" ] }, { "cell_type": "code", "collapsed": false, "input": [ "dataviz1_plotly = tls.mpl_to_plotly(dataviz1)\n", "\n", "print dataviz1_plotly.to_string() # show plotly figure object in notebook" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "Figure(\n", " data=Data([\n", " Scatter(\n", " x=[1968.0, 1969.0, 1970.0, 1971.0, 1972.0, 1973.0, 1974.0, 1975...],\n", " y=[10.0, 10.0, 10.0, 10.0, 10.0, 10.0, 10.0, 10.0, 10.0, 10.0, ...],\n", " mode='lines',\n", " name='_line0',\n", " line=Line(\n", " color='#000000',\n", " width=0.5,\n", " dash='dash',\n", " opacity=0.3\n", " ),\n", " xaxis='x1',\n", " yaxis='y1'\n", " ),\n", " Scatter(\n", " x=[1968.0, 1969.0, 1970.0, 1971.0, 1972.0, 1973.0, 1974.0, 1975...],\n", " y=[20.0, 20.0, 20.0, 20.0, 20.0, 20.0, 20.0, 20.0, 20.0, 20.0, ...],\n", " mode='lines',\n", " name='_line1',\n", " line=Line(\n", " color='#000000',\n", " width=0.5,\n", " dash='dash',\n", " opacity=0.3\n", " ),\n", " xaxis='x1',\n", " yaxis='y1'\n", " ),\n", " Scatter(\n", " x=[1968.0, 1969.0, 1970.0, 1971.0, 1972.0, 1973.0, 1974.0, 1975...],\n", " y=[30.0, 30.0, 30.0, 30.0, 30.0, 30.0, 30.0, 30.0, 30.0, 30.0, ...],\n", " mode='lines',\n", " name='_line2',\n", " line=Line(\n", " color='#000000',\n", " width=0.5,\n", " dash='dash',\n", " opacity=0.3\n", " ),\n", " xaxis='x1',\n", " yaxis='y1'\n", " ),\n", " Scatter(\n", " x=[1968.0, 1969.0, 1970.0, 1971.0, 1972.0, 1973.0, 1974.0, 1975...],\n", " y=[40.0, 40.0, 40.0, 40.0, 40.0, 40.0, 40.0, 40.0, 40.0, 40.0, ...],\n", " mode='lines',\n", " name='_line3',\n", " line=Line(\n", " color='#000000',\n", " width=0.5,\n", " dash='dash',\n", " opacity=0.3\n", " ),\n", " xaxis='x1',\n", " yaxis='y1'\n", " ),\n", " Scatter(\n", " x=[1968.0, 1969.0, 1970.0, 1971.0, 1972.0, 1973.0, 1974.0, 1975...],\n", " y=[50.0, 50.0, 50.0, 50.0, 50.0, 50.0, 50.0, 50.0, 50.0, 50.0, ...],\n", " mode='lines',\n", " name='_line4',\n", " line=Line(\n", " color='#000000',\n", " width=0.5,\n", " dash='dash',\n", " opacity=0.3\n", " ),\n", " xaxis='x1',\n", " yaxis='y1'\n", " ),\n", " Scatter(\n", " x=[1968.0, 1969.0, 1970.0, 1971.0, 1972.0, 1973.0, 1974.0, 1975...],\n", " y=[60.0, 60.0, 60.0, 60.0, 60.0, 60.0, 60.0, 60.0, 60.0, 60.0, ...],\n", " mode='lines',\n", " name='_line5',\n", " line=Line(\n", " color='#000000',\n", " width=0.5,\n", " dash='dash',\n", " opacity=0.3\n", " ),\n", " xaxis='x1',\n", " yaxis='y1'\n", " ),\n", " Scatter(\n", " x=[1968.0, 1969.0, 1970.0, 1971.0, 1972.0, 1973.0, 1974.0, 1975...],\n", " y=[70.0, 70.0, 70.0, 70.0, 70.0, 70.0, 70.0, 70.0, 70.0, 70.0, ...],\n", " mode='lines',\n", " name='_line6',\n", " line=Line(\n", " color='#000000',\n", " width=0.5,\n", " dash='dash',\n", " opacity=0.3\n", " ),\n", " xaxis='x1',\n", " yaxis='y1'\n", " ),\n", " Scatter(\n", " x=[1968.0, 1969.0, 1970.0, 1971.0, 1972.0, 1973.0, 1974.0, 1975...],\n", " y=[80.0, 80.0, 80.0, 80.0, 80.0, 80.0, 80.0, 80.0, 80.0, 80.0, ...],\n", " mode='lines',\n", " name='_line7',\n", " line=Line(\n", " color='#000000',\n", " width=0.5,\n", " dash='dash',\n", " opacity=0.3\n", " ),\n", " xaxis='x1',\n", " yaxis='y1'\n", " ),\n", " Scatter(\n", " x=[1968.0, 1969.0, 1970.0, 1971.0, 1972.0, 1973.0, 1974.0, 1975...],\n", " y=[90.0, 90.0, 90.0, 90.0, 90.0, 90.0, 90.0, 90.0, 90.0, 90.0, ...],\n", " mode='lines',\n", " name='_line8',\n", " line=Line(\n", " color='#000000',\n", " width=0.5,\n", " dash='dash',\n", " opacity=0.3\n", " ),\n", " xaxis='x1',\n", " yaxis='y1'\n", " ),\n", " Scatter(\n", " x=[1970.0, 1971.0, 1972.0, 1973.0, 1974.0, 1975.0, 1976.0, 1977...],\n", " y=[77.099999999999994, 75.5, 76.900000000000006, 77.40000000000...],\n", " mode='lines',\n", " name='_line9',\n", " line=Line(\n", " color='#1F77B4',\n", " width=2.5,\n", " dash='solid',\n", " opacity=1\n", " ),\n", " xaxis='x1',\n", " yaxis='y1'\n", " ),\n", " Scatter(\n", " x=[1970.0, 1971.0, 1972.0, 1973.0, 1974.0, 1975.0, 1976.0, 1977...],\n", " y=[68.400000000000006, 65.5, 62.600000000000001, 64.29999999999...],\n", " mode='lines',\n", " name='_line10',\n", " line=Line(\n", " color='#AEC7E8',\n", " width=2.5,\n", " dash='solid',\n", " opacity=1\n", " ),\n", " xaxis='x1',\n", " yaxis='y1'\n", " ),\n", " Scatter(\n", " x=[1970.0, 1971.0, 1972.0, 1973.0, 1974.0, 1975.0, 1976.0, 1977...],\n", " y=[74.535327580000001, 74.149203689999993, 73.554519959999993, ...],\n", " mode='lines',\n", " name='_line11',\n", " line=Line(\n", " color='#FF7F0E',\n", " width=2.5,\n", " dash='solid',\n", " opacity=1\n", " ),\n", " xaxis='x1',\n", " yaxis='y1'\n", " ),\n", " Scatter(\n", " x=[1970.0, 1971.0, 1972.0, 1973.0, 1974.0, 1975.0, 1976.0, 1977...],\n", " y=[44.399999999999999, 46.200000000000003, 47.600000000000001, ...],\n", " mode='lines',\n", " name='_line12',\n", " line=Line(\n", " color='#FFBB78',\n", " width=2.5,\n", " dash='solid',\n", " opacity=1\n", " ),\n", " xaxis='x1',\n", " yaxis='y1'\n", " ),\n", " Scatter(\n", " x=[1970.0, 1971.0, 1972.0, 1973.0, 1974.0, 1975.0, 1976.0, 1977...],\n", " y=[73.799999999999997, 73.900000000000006, 74.599999999999994, ...],\n", " mode='lines',\n", " name='_line13',\n", " line=Line(\n", " color='#2CA02C',\n", " width=2.5,\n", " dash='solid',\n", " opacity=1\n", " ),\n", " xaxis='x1',\n", " yaxis='y1'\n", " ),\n", " Scatter(\n", " x=[1970.0, 1971.0, 1972.0, 1973.0, 1974.0, 1975.0, 1976.0, 1977...],\n", " y=[65.570923429999993, 64.556485159999994, 63.664263200000001, ...],\n", " mode='lines',\n", " name='_line14',\n", " line=Line(\n", " color='#98DF8A',\n", " width=2.5,\n", " dash='solid',\n", " opacity=1\n", " ),\n", " xaxis='x1',\n", " yaxis='y1'\n", " ),\n", " Scatter(\n", " x=[1970.0, 1971.0, 1972.0, 1973.0, 1974.0, 1975.0, 1976.0, 1977...],\n", " y=[35.299999999999997, 35.5, 36.600000000000001, 38.39999999999...],\n", " mode='lines',\n", " name='_line15',\n", " line=Line(\n", " color='#D62728',\n", " width=2.5,\n", " dash='solid',\n", " opacity=1\n", " ),\n", " xaxis='x1',\n", " yaxis='y1'\n", " ),\n", " Scatter(\n", " x=[1970.0, 1971.0, 1972.0, 1973.0, 1974.0, 1975.0, 1976.0, 1977...],\n", " y=[59.700000000000003, 59.899999999999999, 60.399999999999999, ...],\n", " mode='lines',\n", " name='_line16',\n", " line=Line(\n", " color='#FF9896',\n", " width=2.5,\n", " dash='solid',\n", " opacity=1\n", " ),\n", " xaxis='x1',\n", " yaxis='y1'\n", " ),\n", " Scatter(\n", " x=[1970.0, 1971.0, 1972.0, 1973.0, 1974.0, 1975.0, 1976.0, 1977...],\n", " y=[29.088362969999999, 29.394402849999999, 29.810221049999999, ...],\n", " mode='lines',\n", " name='_line17',\n", " line=Line(\n", " color='#9467BD',\n", " width=2.5,\n", " dash='solid',\n", " opacity=1\n", " ),\n", " xaxis='x1',\n", " yaxis='y1'\n", " ),\n", " Scatter(\n", " x=[1970.0, 1971.0, 1972.0, 1973.0, 1974.0, 1975.0, 1976.0, 1977...],\n", " y=[4.2297979799999998, 5.452796685, 7.4207102200000001, 9.65360...],\n", " mode='lines',\n", " name='_line18',\n", " line=Line(\n", " color='#C5B0D5',\n", " width=2.5,\n", " dash='solid',\n", " opacity=1\n", " ),\n", " xaxis='x1',\n", " yaxis='y1'\n", " ),\n", " Scatter(\n", " x=[1970.0, 1971.0, 1972.0, 1973.0, 1974.0, 1975.0, 1976.0, 1977...],\n", " y=[36.799999999999997, 36.200000000000003, 36.100000000000001, ...],\n", " mode='lines',\n", " name='_line19',\n", " line=Line(\n", " color='#8C564B',\n", " width=2.5,\n", " dash='solid',\n", " opacity=1\n", " ),\n", " xaxis='x1',\n", " yaxis='y1'\n", " ),\n", " Scatter(\n", " x=[1970.0, 1971.0, 1972.0, 1973.0, 1974.0, 1975.0, 1976.0, 1977...],\n", " y=[9.0644389749999998, 9.5031865939999989, 10.5589621, 12.80460...],\n", " mode='lines',\n", " name='_line20',\n", " line=Line(\n", " color='#C49C94',\n", " width=2.5,\n", " dash='solid',\n", " opacity=1\n", " ),\n", " xaxis='x1',\n", " yaxis='y1'\n", " ),\n", " Scatter(\n", " x=[1970.0, 1971.0, 1972.0, 1973.0, 1974.0, 1975.0, 1976.0, 1977...],\n", " y=[38.0, 39.0, 40.200000000000003, 40.899999999999999, 41.79999...],\n", " mode='lines',\n", " name='_line21',\n", " line=Line(\n", " color='#E377C2',\n", " width=2.5,\n", " dash='solid',\n", " opacity=1\n", " ),\n", " xaxis='x1',\n", " yaxis='y1'\n", " ),\n", " Scatter(\n", " x=[1970.0, 1971.0, 1972.0, 1973.0, 1974.0, 1975.0, 1976.0, 1977...],\n", " y=[11.921005389999999, 12.003105590000001, 13.21459351, 14.7916...],\n", " mode='lines',\n", " name='_line22',\n", " line=Line(\n", " color='#F7B6D2',\n", " width=2.5,\n", " dash='solid',\n", " opacity=1\n", " ),\n", " xaxis='x1',\n", " yaxis='y1'\n", " ),\n", " Scatter(\n", " x=[1970.0, 1971.0, 1972.0, 1973.0, 1974.0, 1975.0, 1976.0, 1977...],\n", " y=[13.800000000000001, 14.9, 14.800000000000001, 16.5, 18.19999...],\n", " mode='lines',\n", " name='_line23',\n", " line=Line(\n", " color='#7F7F7F',\n", " width=2.5,\n", " dash='solid',\n", " opacity=1\n", " ),\n", " xaxis='x1',\n", " yaxis='y1'\n", " ),\n", " Scatter(\n", " x=[1970.0, 1971.0, 1972.0, 1973.0, 1974.0, 1975.0, 1976.0, 1977...],\n", " y=[13.6, 13.6, 14.9, 16.399999999999999, 18.899999999999999, 19...],\n", " mode='lines',\n", " name='_line24',\n", " line=Line(\n", " color='#C7C7C7',\n", " width=2.5,\n", " dash='solid',\n", " opacity=1\n", " ),\n", " xaxis='x1',\n", " yaxis='y1'\n", " ),\n", " Scatter(\n", " x=[1970.0, 1971.0, 1972.0, 1973.0, 1974.0, 1975.0, 1976.0, 1977...],\n", " y=[0.80000000000000004, 1.0, 1.2, 1.6000000000000001, 2.2000000...],\n", " mode='lines',\n", " name='_line25',\n", " line=Line(\n", " color='#BCBD22',\n", " width=2.5,\n", " dash='solid',\n", " opacity=1\n", " ),\n", " xaxis='x1',\n", " yaxis='y1'\n", " )\n", " ]),\n", " layout=Layout(\n", " showlegend=False,\n", " autosize=False,\n", " width=960,\n", " height=1120,\n", " annotations=Annotations([\n", " Annotation(\n", " x=2011.5,\n", " y=84.3,\n", " xref='x1',\n", " yref='y1',\n", " text='Health Professions',\n", " font=Font(\n", " size=14.0,\n", " color='#1F77B4'\n", " ),\n", " align='left',\n", " showarrow=False,\n", " opacity=1,\n", " xanchor='left',\n", " yanchor='bottom'\n", " ),\n", " Annotation(\n", " x=2011.5,\n", " y=81.4,\n", " xref='x1',\n", " yref='y1',\n", " text='Public Administration',\n", " font=Font(\n", " size=14.0,\n", " color='#AEC7E8'\n", " ),\n", " align='left',\n", " showarrow=False,\n", " opacity=1,\n", " xanchor='left',\n", " yanchor='bottom'\n", " ),\n", " Annotation(\n", " x=2011.5,\n", " y=78.93281184,\n", " xref='x1',\n", " yref='y1',\n", " text='Education',\n", " font=Font(\n", " size=14.0,\n", " color='#FF7F0E'\n", " ),\n", " align='left',\n", " showarrow=False,\n", " opacity=1,\n", " xanchor='left',\n", " yanchor='bottom'\n", " ),\n", " Annotation(\n", " x=2011.5,\n", " y=76.2,\n", " xref='x1',\n", " yref='y1',\n", " text='Psychology',\n", " font=Font(\n", " size=14.0,\n", " color='#FFBB78'\n", " ),\n", " align='left',\n", " showarrow=False,\n", " opacity=1,\n", " xanchor='left',\n", " yanchor='bottom'\n", " ),\n", " Annotation(\n", " x=2011.5,\n", " y=69.5,\n", " xref='x1',\n", " yref='y1',\n", " text='Foreign Languages',\n", " font=Font(\n", " size=14.0,\n", " color='#2CA02C'\n", " ),\n", " align='left',\n", " showarrow=False,\n", " opacity=1,\n", " xanchor='left',\n", " yanchor='bottom'\n", " ),\n", " Annotation(\n", " x=2011.5,\n", " y=67.42673015,\n", " xref='x1',\n", " yref='y1',\n", " text='English',\n", " font=Font(\n", " size=14.0,\n", " color='#98DF8A'\n", " ),\n", " align='left',\n", " showarrow=False,\n", " opacity=1,\n", " xanchor='left',\n", " yanchor='bottom'\n", " ),\n", " Annotation(\n", " x=2011.5,\n", " y=62.45,\n", " xref='x1',\n", " yref='y1',\n", " text='Communications\\nand Journalism',\n", " font=Font(\n", " size=14.0,\n", " color='#D62728'\n", " ),\n", " align='left',\n", " showarrow=False,\n", " opacity=1,\n", " xanchor='left',\n", " yanchor='bottom'\n", " ),\n", " Annotation(\n", " x=2011.5,\n", " y=60.45,\n", " xref='x1',\n", " yref='y1',\n", " text='Art and Performance',\n", " font=Font(\n", " size=14.0,\n", " color='#FF9896'\n", " ),\n", " align='left',\n", " showarrow=False,\n", " opacity=1,\n", " xanchor='left',\n", " yanchor='bottom'\n", " ),\n", " Annotation(\n", " x=2011.5,\n", " y=58.2423969,\n", " xref='x1',\n", " yref='y1',\n", " text='Biology',\n", " font=Font(\n", " size=14.0,\n", " color='#9467BD'\n", " ),\n", " align='left',\n", " showarrow=False,\n", " opacity=1,\n", " xanchor='left',\n", " yanchor='bottom'\n", " ),\n", " Annotation(\n", " x=2011.5,\n", " y=50.78718193,\n", " xref='x1',\n", " yref='y1',\n", " text='Agriculture',\n", " font=Font(\n", " size=14.0,\n", " color='#C5B0D5'\n", " ),\n", " align='left',\n", " showarrow=False,\n", " opacity=1,\n", " xanchor='left',\n", " yanchor='bottom'\n", " ),\n", " Annotation(\n", " x=2011.5,\n", " y=48.95,\n", " xref='x1',\n", " yref='y1',\n", " text='Social Sciences and History',\n", " font=Font(\n", " size=14.0,\n", " color='#8C564B'\n", " ),\n", " align='left',\n", " showarrow=False,\n", " opacity=1,\n", " xanchor='left',\n", " yanchor='bottom'\n", " ),\n", " Annotation(\n", " x=2011.5,\n", " y=46.93041792,\n", " xref='x1',\n", " yref='y1',\n", " text='Business',\n", " font=Font(\n", " size=14.0,\n", " color='#C49C94'\n", " ),\n", " align='left',\n", " showarrow=False,\n", " opacity=1,\n", " xanchor='left',\n", " yanchor='bottom'\n", " ),\n", " Annotation(\n", " x=2011.5,\n", " y=43.35,\n", " xref='x1',\n", " yref='y1',\n", " text='Math and Statistics',\n", " font=Font(\n", " size=14.0,\n", " color='#E377C2'\n", " ),\n", " align='left',\n", " showarrow=False,\n", " opacity=1,\n", " xanchor='left',\n", " yanchor='bottom'\n", " ),\n", " Annotation(\n", " x=2011.5,\n", " y=41.5234375,\n", " xref='x1',\n", " yref='y1',\n", " text='Architecture',\n", " font=Font(\n", " size=14.0,\n", " color='#F7B6D2'\n", " ),\n", " align='left',\n", " showarrow=False,\n", " opacity=1,\n", " xanchor='left',\n", " yanchor='bottom'\n", " ),\n", " Annotation(\n", " x=2011.5,\n", " y=39.6,\n", " xref='x1',\n", " yref='y1',\n", " text='Physical Sciences',\n", " font=Font(\n", " size=14.0,\n", " color='#7F7F7F'\n", " ),\n", " align='left',\n", " showarrow=False,\n", " opacity=1,\n", " xanchor='left',\n", " yanchor='bottom'\n", " ),\n", " Annotation(\n", " x=2011.5,\n", " y=18.45,\n", " xref='x1',\n", " yref='y1',\n", " text='Computer Science',\n", " font=Font(\n", " size=14.0,\n", " color='#C7C7C7'\n", " ),\n", " align='left',\n", " showarrow=False,\n", " opacity=1,\n", " xanchor='left',\n", " yanchor='bottom'\n", " ),\n", " Annotation(\n", " x=2011.5,\n", " y=16.75,\n", " xref='x1',\n", " yref='y1',\n", " text='Engineering',\n", " font=Font(\n", " size=14.0,\n", " color='#BCBD22'\n", " ),\n", " align='left',\n", " showarrow=False,\n", " opacity=1,\n", " xanchor='left',\n", " yanchor='bottom'\n", " ),\n", " Annotation(\n", " x=0.58616866063612849,\n", " y=1.032144227080936,\n", " xref='paper',\n", " yref='paper',\n", " text=\"Percentage of Bachelor's degrees conferred to women i...\",\n", " font=Font(\n", " size=17.0,\n", " color='#000000'\n", " ),\n", " align='center',\n", " showarrow=False,\n", " opacity=1,\n", " xanchor='center',\n", " yanchor='bottom'\n", " ),\n", " Annotation(\n", " x=-0.043419900787855584,\n", " y=-0.088786600179005234,\n", " xref='paper',\n", " yref='paper',\n", " text='Data source: nces.ed.gov/programs/digest/2013menu_tab...',\n", " font=Font(\n", " size=10.0,\n", " color='#000000'\n", " ),\n", " align='left',\n", " showarrow=False,\n", " opacity=1,\n", " xanchor='left',\n", " yanchor='bottom'\n", " )\n", " ]),\n", " margin=Margin(\n", " l=120,\n", " r=95,\n", " b=140,\n", " t=111,\n", " pad=0\n", " ),\n", " hovermode='closest',\n", " xaxis1=XAxis(\n", " range=[1968.0, 2014.0],\n", " domain=[0.0, 1.0],\n", " type='linear',\n", " showgrid=False,\n", " zeroline=False,\n", " showline=False,\n", " nticks=7,\n", " ticks='inside',\n", " tickfont=Font(\n", " size=14.0\n", " ),\n", " anchor='y1',\n", " side='bottom',\n", " mirror=False\n", " ),\n", " yaxis1=YAxis(\n", " range=[0.0, 90.0],\n", " domain=[0.0, 1.0],\n", " type='linear',\n", " showgrid=False,\n", " zeroline=False,\n", " showline=False,\n", " autotick=False,\n", " ticks='inside',\n", " tick0=0,\n", " dtick=10,\n", " tickfont=Font(\n", " size=14.0\n", " ),\n", " anchor='x1',\n", " side='left',\n", " mirror=False\n", " )\n", " )\n", ")\n" ] } ], "prompt_number": 8 }, { "cell_type": "code", "collapsed": false, "input": [ "# List of all annotation texts, show it in notebook\n", "annos_text = [anno['text'] for anno in dataviz1_plotly['layout']['annotations']]\n", "annos_text" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 9, "text": [ "['Health Professions',\n", " 'Public Administration',\n", " 'Education',\n", " 'Psychology',\n", " 'Foreign Languages',\n", " 'English',\n", " 'Communications\\nand Journalism',\n", " 'Art and Performance',\n", " 'Biology',\n", " 'Agriculture',\n", " 'Social Sciences and History',\n", " 'Business',\n", " 'Math and Statistics',\n", " 'Architecture',\n", " 'Physical Sciences',\n", " 'Computer Science',\n", " 'Engineering',\n", " \"Percentage of Bachelor's degrees conferred to women in the U.S.A., by major (1970-2012)\",\n", " 'Data source: nces.ed.gov/programs/digest/2013menu_tables.asp\\nAuthor: Randy Olson (randalolson.com / @randal_olson)\\nNote: Some majors are missing because the historical data is not available for them']" ] } ], "prompt_number": 9 }, { "cell_type": "code", "collapsed": false, "input": [ "# List all majors in dataset, show it in notebook\n", "majors = annos_text[:-2]\n", "majors" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 10, "text": [ "['Health Professions',\n", " 'Public Administration',\n", " 'Education',\n", " 'Psychology',\n", " 'Foreign Languages',\n", " 'English',\n", " 'Communications\\nand Journalism',\n", " 'Art and Performance',\n", " 'Biology',\n", " 'Agriculture',\n", " 'Social Sciences and History',\n", " 'Business',\n", " 'Math and Statistics',\n", " 'Architecture',\n", " 'Physical Sciences',\n", " 'Computer Science',\n", " 'Engineering']" ] } ], "prompt_number": 10 }, { "cell_type": "markdown", "metadata": {}, "source": [ "And now make a few updates on the Plotly figure object:" ] }, { "cell_type": "code", "collapsed": false, "input": [ "# (1) Adjust margins (use our web GUI to easier find the appropriate values)\n", "dataviz1_plotly['layout']['margin'].update(\n", " l=50, # left margin in pixels\n", " r=160, # right \" \" \"\n", " b=100, # bottom \" \" \"\n", " t=100 # top \" \" \"\n", ")\n", "\n", "# (2) Add title (appears in figure's URL, nice for sharing), remove title annotation\n", "dataviz1_plotly['layout'].update(\n", " title=annos_text[-2],\n", " titlefont=dict(size=20) # increase font size\n", ")\n", "dataviz1_plotly['layout']['annotations'][-2].update(text=' ')\n", "\n", "# (3) Remove tick lines\n", "dataviz1_plotly['layout']['xaxis1'].update(ticks='')\n", "dataviz1_plotly['layout']['yaxis1'].update(ticks='')\n", "\n", "# (4) Add hover label to data trace, remove hover label from grid traces\n", "N_traces = len(dataviz1_plotly['data'])\n", "N_majors = len(majors)\n", "update_name = [{'name': ' '} for i in range(N_traces)]\n", "update_name[N_traces-N_majors:] = [{'name': major} for major in majors]\n", "dataviz1_plotly['data'].update(update_name)\n", "\n", "# (5) Make every y coordinate show when hovering over a given x coordinate\n", "dataviz1_plotly['layout'].update(hovermode='x')" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 11 }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "Send updated Plotly figure object to Plotly!" ] }, { "cell_type": "code", "collapsed": false, "input": [ "py.iplot(dataviz1_plotly, filename='dataviz1_updated', width=960, height=1120)" ], "language": "python", "metadata": {}, "outputs": [ { "html": [ "" ], "metadata": {}, "output_type": "display_data", "text": [ "" ] } ], "prompt_number": 12 }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "To learn more about Plotly's Python API" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Refer to\n", "\n", "* our online documentation page or\n", "* our User Guide." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "
\n", "
\n", "
" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "
\n", " \n", "
\n", "\n", "

Got Questions or Feedback?

\n", "\n", "About Plotly\n", "\n", "* email: feedback@plot.ly \n", "* tweet: \n", "@plotlygraphs\n", "\n", "

Notebook styling ideas

\n", "\n", "Big thanks to\n", "\n", "* Cam Davidson-Pilon\n", "* Lorena A. Barba\n", "\n", "
" ] }, { "cell_type": "code", "collapsed": false, "input": [ "from IPython.display import display, HTML\n", "import urllib2\n", "url = 'https://raw.githubusercontent.com/plotly/python-user-guide/master/custom.css'\n", "display(HTML(urllib2.urlopen(url).read()))" ], "language": "python", "metadata": {}, "outputs": [ { "html": [ "\n", "\n" ], "metadata": {}, "output_type": "display_data", "text": [ "" ] } ], "prompt_number": 13 } ], "metadata": {} } ] }