{ "metadata": { "name": "" }, "nbformat": 3, "nbformat_minor": 0, "worksheets": [ { "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Inbox count by age\n", "\n", "This code generated \"Figure 3\" in [Three Years of Logging My Inbox Count](http://warkmilson.com/2015/05/15/three-years-of-logging-my-inbox-count.html#email-age).\n", "\n", "1. Run `compute_ages_on_each_day.py` from [gmail-graphs](https://github.com/mddub/gmail-graphs) on the directory containing the JSON output files of [gmail-logger](https://github.com/mddub/gmail-logger). This will generate a JSON object which maps keys like `\"2015-03-01\"` to arrays like `[0, 0, 0, 1, 3, 10, 12, 12]`.\n", "\n", " ```\n", " python compute_ages_on_each_day.py /path/to/your/json/log/files/dir/ > ages.json\n", " ```\n", "\n", "2. Paste the following into an IPython Notebook. Set the value of `AGES_BY_DAY_FILE`. Change other constants as desired.\n", "\n", " (For inline graphs, start IPython Notebook with `ipython notebook --pylab inline`.)" ] }, { "cell_type": "code", "collapsed": false, "input": [ "# Some Pandas/Matplotlib initialization which I more or less blindly copied from an example ipython notebook.\n", "\n", "import pandas as pd\n", "pd.set_option('display.max_columns', 15)\n", "pd.set_option('display.width', 400)\n", "pd.set_option('display.mpl_style', 'default')\n", "rcParams['figure.figsize'] = (12, 5)\n", "import matplotlib\n", "\n", "font = {'family' : 'sans-serif',\n", " 'weight' : 'normal',\n", " 'size' : 14}\n", "\n", "matplotlib.rc('font', **font)" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 1 }, { "cell_type": "code", "collapsed": false, "input": [ "# File containing the output of compute_ages_on_each_day.py\n", "AGES_BY_DAY_FILE = 'ages.json'\n", "\n", "# 'YYYY-MM-DD'. If you don't want a min/max date, set the value to None\n", "MIN_DATE = '2015-02-01'\n", "MAX_DATE = '2015-05-02'\n", "\n", "TITLE = u'Age of messages in inbox at end of day, 2015'\n", "\n", "RANGES = [(0, 1), (2, 4), (5, 8), (9, 16), (17, 32), (33, 99999)]\n", "\n", "# \"RdYlBu\" from http://colorbrewer2.org/\n", "# The length of this list should match that of RANGES.\n", "COLORS = list(reversed([[x/255. for x in c] for c in\n", " [(215,48,39),(252,141,89),(254,224,144),(224,243,248),(145,191,219),(69,117,180)]\n", "]))\n", "\n", "# You will probably need to tweak this\n", "LEGEND_POSITION = (0.05, 0.87)\n", "\n", "##################\n", "\n", "from collections import defaultdict\n", "from datetime import datetime\n", "\n", "import simplejson\n", "\n", "ages_by_day = simplejson.loads(open(AGES_BY_DAY_FILE).read())\n", "# Create a data series (x is date, y is count) for each of the ranges (0-1 days old, 2-4 days old, etc.)\n", "# (There is certainly a better way to do this using Pandas...)\n", "series_by_range = defaultdict(list)\n", "index = sorted(ages_by_day.keys())\n", "if MIN_DATE:\n", " index = [k for k in index if k >= MIN_DATE]\n", "if MAX_DATE:\n", " index = [k for k in index if k <= MAX_DATE] \n", "date_index = [datetime.strptime(k, '%Y-%m-%d') for k in index]\n", "for d, ages in [(k, ages_by_day[k]) for k in index]:\n", " for r in RANGES:\n", " series_by_range[r].append(\n", " sum([r[0] <= age <= r[1] for age in ages])\n", " )\n", "\n", "# Make a Pandas DataFrame out of the series\n", "df = pd.DataFrame(data=series_by_range, index=date_index)\n", "# Resample as daily so that the index includes days without data\n", "df = df.resample('D')\n", "# Plot as stacked bar\n", "ax = df.plot(kind='bar', stacked=True, figsize=(12, 5), width=1, color=COLORS, edgecolor=[(0.6,) * 3])\n", "\n", "# Make the legend. Reverse its default ordering so that the order matches the graph.\n", "format_range_name = lambda r: \"%s-%s\" % (r[0], r[1]) if r[1] != 99999 else \"%s+\" % r[0]\n", "handles, labels = ax.get_legend_handles_labels()\n", "assert labels == map(str, RANGES)\n", "labels = map(format_range_name, RANGES)\n", "legend = ax.legend(reversed(handles), reversed(labels),\n", " loc='upper left', fontsize=12, ncol=2, columnspacing=1, framealpha=0, bbox_to_anchor=LEGEND_POSITION)\n", "legend.set_title('Days old', prop={'size': 12})\n", "\n", "# x axis. Tweak this to show labels more or less often.\n", "ax.xaxis.grid(False)\n", "ax.xaxis.set_ticklabels([d.strftime('%b %d') if d.day in (1, 15) else \"\" for d in df.index], rotation=90, size=12)\n", "\n", "# y axis\n", "ax.yaxis.grid('major', color='black', linestyle='-', alpha=0.2)\n", "ax.set_ylabel('Messages in inbox', size=14, labelpad=10)\n", "\n", "# Clean up the background and borders\n", "for spine in ['top', 'right']:\n", " ax.spines[spine].set_visible(False)\n", "ax.patch.set_alpha(0)\n", "ax.figure.patch.set_alpha(0)\n", "\n", "# Title\n", "ax.set_title(TITLE, fontsize=14, ha='center', va='top', position=(0.5, 1.06), color='#333333')\n", "\n", "# Add dots for dates with missing data\n", "missing_days = [i for i, x in enumerate(df[RANGES[0]]) if str(x) == 'nan']\n", "if missing_days:\n", " for m in missing_days:\n", " ax.text(m - 0.6, 1, \".\", fontdict={'size': 14})\n", "\n", " # You'll have to tweak these to make the \"no data\" text show in the right spot below the legend.\n", " # This only applies if you have missing data.\n", " #\n", " # The correct way to do this would be to add a custom handler to the legend:\n", " # http://matplotlib.org/users/legend_guide.html#legend-handlers\n", " BELOW_X, BELOW_Y = (7, 37)\n", " ax.text(BELOW_X, BELOW_Y, \".\", fontdict={'size': 14}, zorder=99)\n", " ax.text(BELOW_X + 3, BELOW_Y - 0.5, \"no data\", fontdict={'size': 12}, zorder=99)\n", "\n", "# don't show the result of evaluating the last command\n", "pass" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": "iVBORw0KGgoAAAANSUhEUgAAAtoAAAFsCAYAAADylR7GAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nYII=\n", "text": [ "" ] } ], "prompt_number": 2 } ], "metadata": {} } ] }