Format: application/octet-stream
1 {
2 "cells": [
3 {
4 "cell_type": "markdown",
5 "metadata": {},
6 "source": [
7 "http://stackoverflow.com/research/developer-survey-2016#most-popular-technologies-per-occupation"
8 ]
9 },
10 {
11 "cell_type": "code",
12 "execution_count": 1,
13 "metadata": {},
14 "outputs": [
15 {
16 "data": {
17 "image/png": 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\n",
18 "text/plain": [
19 "<Figure size 432x288 with 1 Axes>"
20 ]
21 },
22 "metadata": {
23 "needs_background": "light"
24 },
25 "output_type": "display_data"
26 }
27 ],
28 "source": [
29 "import matplotlib.pyplot as plt\n",
30 "import numpy as np\n",
31 "\n",
32 "plt.figure()\n",
33 "\n",
34 "languages =['Python', 'SQL', 'Java', 'C++', 'JavaScript']\n",
35 "pos = np.arange(len(languages))\n",
36 "popularity = [56, 39, 34, 34, 29]\n",
37 "\n",
38 "plt.bar(pos, popularity, align='center')\n",
39 "plt.xticks(pos, languages)\n",
40 "plt.ylabel('% Popularity')\n",
41 "plt.title('Top 5 Languages for Math & Data \\nby % Popularity on Stack Overflow')\n",
42 " \n",
43 "plt.show()"
44 ]
45 },
46 {
47 "cell_type": "code",
48 "execution_count": 6,
49 "metadata": {
50 "scrolled": true
51 },
52 "outputs": [
53 {
54 "data": {
55 "image/png": 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9aX9Su2B5G+Y00qn4STTcfLJKrrGcSDq9hTS4wIh8OrwTqS2xIZ9U6u51SN7erXn6ZOAT+YeqPqT2+lsqrgL5N0nrSdqG1F5eKsMzpGag/pIG0njvcn2Bd4HFkrYi1Zyb401W756UfKo/hdQT4eO5eaiax0gHm08p/Vi8BynhV2tPbpSkAySNzmVWTpq7k9qaq8XZVJex15P2zU55fcNy0i95l9Sb3+6Svlwtpoh4idQf9/fzj5Xd8r76CXB/rD6Q9iRSe/furN5F8dXAGaVtK3V1fECt70sVTXWZ/CDw/3ivtl163lhPml2em1Da3iRSbXMQqSvNP5ZeiIilkm4ntUtOrWFdXyW1Ky7Kzy8m1eyOA8Y3cTnhHaSuWvuRxjy8Pk8fn2P7A2m8wntJX/xyD+X5uwF/iYh/5Ok3kX6MnEA6mIwn/VBazfmk/lI+BTxNSp57NjBvNTcA5ykN7vtgRJSuNplAakf+XkMLRsRypevnzyH9gDqX1Kb8QjO2X7KQlADPJvUBM4/Uhl1KTmvEqUa6jI2I2yRtQDoIlZod/puy5oeIWKh0tc+FklZExG+rxPVj0uhD55Kaht4iffZ+VzHfZNJB+p6Kmu4VpLOCX+cfWEtdzzbat3wjmuoy+SHSvihP4H2Ah9dye12C+0LpYCR9DtgiIlpthBJJ04FjI2JWM5fblJSU9+7A12VvQqp9jo6Id9s7HrPW5CaUDiQ3qxxNvu7Zmie3aZ8MTHbytq7ACbyCykbqbuPtHku6auKeSCPPt0cM7VL2lqA0VNodpBHfmz24Q5HL3hK6cvmLXHY3oVTIl96NaHrOzsdl75plh65d/iKX3TVwM7OCauurUDp8df/CCy+EAsTZGlz2rll26NrlL0jZK++RSBPbuAmlo79JZmYdUdUE7iYUM7OCcgI3MysoJ3Azs4JyAjczKygncDOzgnICNzMrKCdwM7OCcgI3MysoJ3Azs4IqzIAOW53T5AA1hfHCeUe2dwhm1gm4Bm5mVlBO4GZmBeUEbmZWUE7gZmYF5QRuZlZQTuBmZgXlBG5mVlBO4GZmBeUEbmZWUE7gZmYFVZhb6dfF3WcfxNLlK1m6oh6A8yY+xZ0z5tGrezf++6jh7LvdxixdUc9DL77FN6/7F927id+cvDvDNurDi28s4ozLHqJ+ZbBhnx5c+Mk9OPn397FipcdnNrP21SUSOMAXLn2QZ+a8s9q0cw5/H0tX1HPQT6cBsHG/ngDsv8Mg3lq8nLEX3MWPj9+FA3YYxO1PzeWbR+zETyc/7eRtZh1Cl21C6dOzjuN235yf3fLMqmnz3lkGwIr6lfTuUQdA7x51LK9fyd5bb0T9yuCBF+a3S7xmZpW6TA38go/vBsD0F+bzk8lPsdmA3sxftIwzR23Ph7cdyKJl9fx08tNMf3E+d82cx+EfGMrEM0fy8Evzuf/5N/nzaXsx9s8PtnMpzMzeo4g2bQ5Y642tS3eyQzdYj9kLltCzrhvfHjOcvr2688e7n2PCl0fylcsfZvyjr7LrsA35w6kjOPAn03hn6YrVlv/KqO2Y9eZinpmzkC8euB0Av5o6gydnL1yreNydrJk1k6pN7BJNKLMXLAFgWf1K/nLvi4zYcgCvzF/M8vqVjH/0VQAemfUW899dxtYb911t2a0G9mHXYQO47uFX+M6YnfnhxCf54cQn+e6Yndu8HGZm5Tp9Au/do471e73XUjTmg5vyxOy3mb9oOfc++wYjt98YgK037svAfr148Y13V1v+22N25twJTwCp3TwCIqBPzy7T+mRmHVSnz0Ibr9+T352yB90k6rqJGXPe4VvXPwbAf13/L35y/Af5ryN3YkV9cNbfHuHtJe81nxyz62Y8Oustnp+XkvrPb32Giz+zJwA/uPnJti+MmVmZmtrAJb0ALATqgRURMULSRsDfgK2AF4ATI6KpSzTapQ28o3EbuJk10zq3gR8UEbtGxIj8/BxgSkRsD0zJz83MrI2sSxv40cAl+fElwDHrHI2ZmdWs1gQewC2SHpQ0Nk8bEhGzAfL/wdUWlDRW0nRJ08eNG7fuEZuZdTHleTT/jYXaf8TcNyJelTQYuFXSU7VuOCLGAaXM7XvQzcyaqSKPrlJTDTwiXs3/5wLXAXsBcyQNBcj/57ZYtGZm1qQmE7ikvpLWLz0GRgOPAeOBU/NspwI3tFaQZma2plqaUIYA10kqzX9ZREyS9ABwpaTTgJeAE1ovTDMzq9RkAo+I54APVpn+BjCqNYIyM7Omdfpb6c3MOisncDOzgnICNzMrKCdwM7OCcgI3MysoJ3Azs4JyAjczKygncDOzgnICNzMrKCdwM7OCcgI3MysoJ3Azs4JyAjczKygncDOzgnICNzMrKCdwM7OCcgI3MysoJ3Azs4JyAjczKygncDOzgnICNzMrKCdwM7OCcgI3MysoJ3Azs4JyAjczKygncDOzgnICNzMrKCdwM7OCqjmBS6qT9LCkCfn5RpJulTQj/x/QemGamVml5tTAzwSeLHt+DjAlIrYHpuTnZmbWRmpK4JI2B44E/lA2+Wjgkvz4EuCYFo3MzMwaVWsN/Hzg68DKsmlDImI2QP4/uNqCksZKmi5p+rhx49YlVjOzLqk8j+a/sQDda1jwKGBuRDwo6cDmbjgixgGlzB3NXd7MrKuryKOrNJnAgX2Bj0o6AlgP6C/pr8AcSUMjYrakocDcFo3YzMwa1WQTSkR8IyI2j4itgI8Dt0fEKcB44NQ826nADa0WpZmZraGWGnhDzgOulHQa8BJwQsuEZNWc86PO8fvBeWePbe8QzDqNZiXwiJgGTMuP3wBGtXxIZmZWC9+JaWZWUE7gZmYF5QRuZlZQTuBmZgXlBG5mVlBO4GZmBeUEbmZWUE7gZmYF5QRuZlZQ63IrvRXEJ48dzUYbrk9EsHTZcsbfdg+z577BjtsMY/TIPamr68aixUu46uY7mL9gId26iZOPPoSNNlyfN+a/zWU33MbKCPqs14tPfmw0v79iAitXumNJs/bmBN4FXHnTVJYuWw7A8O225PjDD+APV0zgxCMP4rd/vYF58xew6/DtOGb0flx81UR22HoYi5cs5YKLb+H4ww9gh22G8dSzL3HEQR9i8p0POHmbdRBuQukCSskbYL1ePYkIBg7YgHcWLWLe/AUAPP3cLHbcZhh9eveifuVKevRIx/YePbpTX1/P1sOGsjJW8sLLr7VLGcxsTa6BdxHHHbY/22+9OQAXXTWRBW+/Q7++fdh8k0G8/Nrr7DZ8OwA27N+Pmc+/zAd23JozP3McL706l+dnvcZp/+8I/nztLe1ZBDOr4ATeRVwz6U4Adtt5e444cG/+dPUkLr9hCkeN+jDd6+p4+vlZLF6ylPr6lQRw7aS7Vi07ap/duf/RpxjQvx/HHjoSgKn3PMTs199sj6KYWeYE3sU8/PgMPnboSPqs14uZL77CzBdfAaBfn97sv9cuvLlg4WrzDxzQn2GbDmbKPQ/x+U+M4coJU0HihCMOYNzlE9qjCGaWuQ28k+vZozsbrN931fOdtt2CRUuWsmjJUvr17Q2AgEMP2JP7HnmS5ctXrLb8mFH7MGHKvXldPQggIujZs0dbFcHMGuAaeCfXs0cPTj7mYHr26MHKlStZvGQpl1wzCYBDR+7JlpsPoa5bHTNeeJlJ0+5fbdldh2/HrNlzV/3Qeevd0/nMCYcBcPPU+9qsDJ1lNCJo/ohEXbns1jQn8E7unUWL+c1fqg9XWmoXb8gjT8xc7flTz77EU8++1GKxmdm6cROKmVlBOYGbmRWUE7iZWUE5gZuZFZQTuJlZQTmBm5kVlBO4mVlBOYGbmRWUE7iZWUH5Tkzr1Boajahk1L67c8h+I/jFH69izrz5nWo0oq5c9q6iyQQuaT3gTqBXnv/qiPiOpI2AvwFbAS8AJ0bE/NYL1az5qo1G9MtLrgVg0yED2WLTwcwv64GxM41G1JXL3lXU0oSyFPhIRHwQ2BU4TNKHgHOAKRGxPTAlPzfrUKqNRgRQV9eNow/Zj+tv+ftq83em0Yi6ctm7iiZr4JH2+jv5aY/8F8DRwIF5+iXANODsFo/QbB1VjkYEcMh+I3j48Rmr1UCBTjcaUVcue1dQUxu4pDrgQWA74NcRcZ+kIRExGyAiZksa3MCyY4GxABdeeCFjx7pLSWtblaMR3X7PQwwbOohJd9y/xrydbTSirlz2zqQ8j2bjImJcTVehRER9ROwKbA7sJen9tW44IsZFxIiIGOHkbe3p4cdnsO0Wm7LtlpsxaKMNOfv0kzj79JPov35fPnviEWy/1WarzV8ajejhx2cw5uB9mDj1H0ycdh9jDt6nnUqw9rpy2TuD8jya/8ZBM69CiYi3JE0DDgPmSBqaa99DgbktH7bZ2uvZozu91+vFgoXvAu+NRjT13oeZeu/Dq+Y7+/ST+NPVk5gzb/Xf4KuNRkRBRiPqymXvSmq5CmUQsDwn797AwcCPgPHAqcB5+X/1UQPM2kljoxE1paOMRrS2unLZu5JaauBDgUtyO3g34MqImCDpXuBKSacBLwEntGKcZs3W2GhE5X70u8vXmFb00Yg6S9k9pFzjarkK5Z/AblWmvwGMavGIzMysJr6V3sysoJzAzcwKygnczKygnMDNzArKCdzMrKCcwM3MCsoJ3MysoJzAzcwKygnczKygPKSamXU6fdbrxYlHHcTADfuzor6eN+a/zXWT7+LdxUvYcZthjB65J3V13Vi0eAlX3XwH8xcsLOSQcq6Bm1mnE8Cd9z3Kz/5wJRdcfA1vvPU2hx24F7179eTEIw/i8vFTOP+iq7n/0ac4ZvR+QPmQctewZOkydthmGECHHlLOCdzMOp3FS5by3KzZq57PenUuG/bvx8ABG/DOokWrelp8+rlZ7LjNMPr07lXIIeWcwM2sUxOw92478eTMF3n9zbfo17cPm28yCIDdhm8HwIb9+zHz+ZdZumwZZ37mOJYsXcbzs15j9MgRTJy25uhFHYXbwM2sU/voIfuybNkK7n3wcQK4/IYpHDXqw3Svq+Pp52exeMlS6utXFnJIOSdwM+u0jjhobwYO2IBLrplEqQV75ouvMPPFVwDo16c3+++1C29WDPBcGlJuyj0P8flPjOHKCVNB4oQjDmDc5RPauBQNcxOKmXVKo0fuyWZDBvGXaydTX79y1fR+fXsDqWnl0AP25L5HnmT58hWrLVttSLnogEPKuQZuZp3O4I0H8JF9duP1N97iC6ccDcD8BQv5y3W3cujIPdly8yHUdatjxgsvM6mijbtIQ8o5gZtZpzN33vwGh2O7ZtKdjS7bkYaUa4qbUMzMCsoJ3MysoJzAzcwKygnczKygnMDNzArKCdzMrKCcwM3MCsoJ3MysoJzAzcwKygnczKygmkzgkoZJmirpSUmPSzozT99I0q2SZuT/A1o/XDMzK6mlBr4C+FpE7AR8CDhD0nDgHGBKRGwPTMnPzcysjTSZwCNidkQ8lB8vBJ4ENgOOBi7Js10CHNNKMZqZWRXNagOXtBWwG3AfMCQiZkNK8sDgBpYZK2m6pOnjxlXvHczMzBpWnkfz31hoRneykvoB1wBfjYi3JdW0XESMA0qZu+MN62xm1sFV5NFVaqqBS+pBSt6XRsS1efIcSUPz60OBuS0Uq5mZ1aCWq1AE/BF4MiJ+XvbSeODU/PhU4IaWD8/MzBpSSxPKvsAngX9JeiRP+yZwHnClpNOAl4ATWiVCMzOrqskEHhF3k8b/rGZUy4ZjZma18p2YZmYF5QRuZlZQTuBmZgXlBG5mVlBO4GZmBeUEbmZWUE7gZmYF5QRuZlZQTuBmZgXlBG5mVlBO4GZmBeUEbmZWUE7gZmYF5QRuZlZQTuBmZgXlBG5mVlBO4GZmBeUEbmZWUE7gZmYF5QRuZlZQTuBmZgXlBG5mVlBO4GZmBeUEbmZWUE7gZmYF5QRuZlZQTuBmZgXlBG5mVlBNJnBJF0maK+mxsmkbSbpV0oz8f0DrhmlmZpVqqYH/CTisYto5wJSI2B6Ykp+bmVkbajKBR8SdwJsVk48GLsmPLwGOadmwzMysKWvbBj4kImYD5P+DG5pR0lhJ0yVNHzdu3Fpuzsys6yrPo/lvLED31t5wRIwDSpk7Wnt7ZmadTUUeXWVta+BzJA0FyP/nrkNsZma2FtY2gY8HTs2PTwVuaJlwzMysVrVcRng5cC+wo6SXJZ0GnAccImkGcEh+bmZmbajJNvCIOKmBl0a1cCxmZtYMvhPTzKygnMDNzArKCdzMrKCcwM3MCsoJ3MysoJzAzcwKygnczKygnMDNzArKCdzMrKCcwM3MCsoJ3MysoJzAzcwKygnczKygnMDNzArKCdzMrKCcwM3MCsoJ3MysoJzAzcwKygnczKygnMDNzArKCdzMrKCcwM3MCsoJ3MysoJzAzcwKygnczKygnMDNzArKCdzMrKCcwM3MCmqdErikwyQ9LWmmpHNaKigzM2vaWidwSXXAr4HDgeHASZKGt1RgZmbWuHWpge8FzIyI5yJiGXAFcHTLhGVmZk1RRKzdgtLxwGER8W/5+SeBvSPiSxXzjQXG5qfjImLcOsTb6iSN7egxthaXvWuWHbp2+YtQ9oo8CjmXrksCPwE4tCKB7xURX17naNuRpOkRMaK942gPLnvXLDt07fIXuezr0oTyMjCs7PnmwKvrFo6ZmdVqXRL4A8D2kraW1BP4ODC+ZcIyM7OmdF/bBSNihaQvAZOBOuCiiHi8xSJrPx26LayVuexdV1cuf2HLvtZt4GZm1r58J6aZWUE5gZuZFVSnSuCS7pd0maQrJf1I0nqNzLuppMPKno+R9PW2ibR9SPpsfm+uyO/T+yX1kPQ1STdIul7S+ZI2KVvmrvaMuSV0hjKsDUkDJf0g79urJP2fpC3aO6610dL7sNp3oRnLDpL04ybmWT9fat2q1vpHzA5qaUR8AkDS94HjgEsbmHcocBgwqY1ia1eSdgFGAqdExDJJGwI9gDOAvsCxEbFS0keBn0s6JSJWtl/Eti4kCfgpMCEivpmn7QAMBF7Kz8cAQxu7iUXSjRExpg1CbjONfBdqWbYuIl4HmqrsrQ+cAFy1LrE2pbMl8HIPky5z/ALwVkRcDiDpi8CbpOS9taTLgAnAQmCQpF+SrmmfGhH/l5c5FPgsIODusul3AZeTPgxLgbMi4s02LGNzbEx6H5YBRMRb+Qzlo8CYUrKOiPE5ie8F/KPdom1hkvoAPwP6kz73v4mIOyR9BZgdEVfl+cYCi4Brq83fLsGvnRHAioi4pjQhIp5px3jWWQvuwzW+C2XbGA78B9AbWA6cDowC9gN6Ar0lfQ84PyJOzAfBg0gHgM2ASfmA+CVg85xf7ouIC1rlTYmITvMH3JX/1wE/B44HNgUuzdO7ATcAGwB75J1QWnYM6Tr2fnlHTQCGAIOAm4ABeb2/Aw7My0wH9s+PvwKc1t7vQSPvTR/gMtKH+hxgd2B74LIq854FfKL8PS3yH3BX3nd98/MNgetJB+QdSbcll+a9CtikofnbuyzNKPPHSRWKxuYZA4xtYp4b27ssLb0Pq30X8jw9cg4Ynp/3zesYA9wM9M/TNwWuLHsPJ+ec0gu4ktS536p5WvOvs9XAe+UjHsAjwA0RsVzSAkk7kk4fn46IBekMcw33R8Q7AJKeIzWzbAA8GBHz8/SJpOQ3jXSELrXNPQXs3SqlagERsUjSKcBupNrZecDFQLXrSKu+OQUn4AxJuwMrgcHARhHxtKSNJA0iHaQXRsRrkrpXmx94o53ibxGSNgB+m59uAPSQdGB+/u2ImCnpbOCDedqgsu/UbRFxUZsFu6YW2YcR8UbldyGfeT8JzIuIJwAi4l2AnCvui4i3G4jrvohYkOe9HdiVlB9aXWdL4KvawCtcTzpSDiTVwBuyrOzxStLRt7FktiLyYRioz/N3WJGaSR4EHpQ0k/QbwVBJfSJiUdms7wOmtEeMrehw0pf7lEg3od1IqjFBKuso0udjcg3zF8FzpDKtJiea0u9EVdvAI+JHpce5Dbzad6o9tNg+rPJdOIpUCWvoxpjFjcRVuUyb3VzTqa5CacRUYB9gZ+DePG0R6VSqKY8Bu0vaUFI34FDSji8USVtWXIGwI/ACqanorFw2JB1JOpA92uZBtq5+wPz8RR5BOrsqmQyMJiWAKTXMXwQPAD0lHVuaIGl4ro0WVYvswwa+C7NJ34dBuR0cSX2Uxj1oyt6S+kvqBRxI+u68S235ZZ10thp4VbkZZTrp1Kp0ZcUMoF7S5cCNpB8xqy07T9KvgAt570fMIv2YVdIH+E9J65POFmYB/0s6kJ0JXJs/gPOBz5SdWawn6eay9VwaEQ1d2dPh5C/gcmAi8AtJfwGeIX1ZAYiI5yT1BV6PiHl5coPzF0FEhKT/AL4m6dOkH9lnk37UK5RW2IdVvws5T5wDfD1/F5YCX6whxEeAc0md+00qNcFIelTSlcDfo5V+xOwSt9Ln2uVfgXMi4qX2jqejkjQQ+CVwdURc297xtIR86dy3IuJT7R2LrZ2OvA9zM9ROEdHodeGtpdPXwCVtA5xPuizQybsREfEGuX20M5B0HOlqjMLVOi3xPmxcl6iBm5l1Rl3lR0wzs07HCdzMrKCcwM3MCsoJ3MysoJzAzcwK6v8DtBXla1E3AegAAAAASUVORK5CYII=\n",
56 "text/plain": [
57 "<Figure size 432x288 with 1 Axes>"
58 ]
59 },
60 "metadata": {
61 "needs_background": "light"
62 },
63 "output_type": "display_data"
64 }
65 ],
66 "source": [
67 "import matplotlib.pyplot as plt\n",
68 "import numpy as np\n",
69 "\n",
70 "plt.figure()\n",
71 "\n",
72 "languages =['Python', 'SQL', 'Java', 'C++', 'JavaScript']\n",
73 "pos = np.arange(len(languages))\n",
74 "popularity = [56, 39, 34, 34, 29]\n",
75 "\n",
76 "# change the bar color to be less bright blue\n",
77 "bars = plt.bar(pos, popularity, align='center', linewidth=0, color='lightslategrey')\n",
78 "# change one bar, the python bar, to a contrasting color\n",
79 "bars[0].set_color('#1F77B4')\n",
80 "\n",
81 "# soften all labels by turning grey\n",
82 "plt.xticks(pos, languages, alpha=0.8)\n",
83 "# remove the Y label since bars are directly labeled\n",
84 "#plt.ylabel('% Popularity', alpha=0.8)\n",
85 "plt.title('Top 5 Languages for Math & Data \\nby % popularity on Stack Overflow', alpha=0.8)\n",
86 "\n",
87 "# remove all the ticks (both axes), and tick labels on the Y axis\n",
88 "plt.tick_params(top='off', bottom='off', left='off', right='off', labelleft='off', labelbottom='on')\n",
89 "\n",
90 "# remove the frame of the chart\n",
91 "for spine in plt.gca().spines.values():\n",
92 " spine.set_visible(False)\n",
93 " \n",
94 "# direct label each bar with Y axis values\n",
95 "for bar in bars:\n",
96 " height = bar.get_height()\n",
97 " plt.gca().text(bar.get_x() + bar.get_width()/2, bar.get_height() - 5, str(int(height)) + '%', \n",
98 " ha='center', color='w', fontsize=11)\n",
99 "plt.show()"
100 ]
101 },
102 {
103 "cell_type": "code",
104 "execution_count": null,
105 "metadata": {
106 "collapsed": true
107 },
108 "outputs": [],
109 "source": []
110 }
111 ],
112 "metadata": {
113 "anaconda-cloud": {},
114 "kernelspec": {
115 "display_name": "Python 3",
116 "language": "python",
117 "name": "python3"
118 },
119 "language_info": {
120 "codemirror_mode": {
121 "name": "ipython",
122 "version": 3
123 },
124 "file_extension": ".py",
125 "mimetype": "text/x-python",
126 "name": "python",
127 "nbconvert_exporter": "python",
128 "pygments_lexer": "ipython3",
129 "version": "3.8.8"
130 }
131 },
132 "nbformat": 4,
133 "nbformat_minor": 2
134 }
135