Mercurial > hg > from-my-pen-to-your-ears-supplementary-material

annotate results/data/saves/plots.ipynb @ 1:eb3b846ae0ef tip

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second commit
author Emmanouil Theofanis Chourdakis <e.t.chourdakis@qmul.ac.uk>
date Wed, 16 May 2018 18:13:41 +0100
parents 4dad87badb0c
children
rev   line source
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e@0 4 "cell_type": "code",
e@0 5 "execution_count": 1,
e@0 6 "metadata": {},
e@0 7 "outputs": [],
e@0 8 "source": [
e@0 9 "import glob\n",
e@0 10 "import pandas as pd\n",
e@0 11 "\n",
e@0 12 "from matplotlib import rc\n",
e@0 13 "rc('font',**{'family':'sans-serif','sans-serif':['Helvetica']})\n",
e@0 14 "## for Palatino and other serif fonts use:\n",
e@0 15 "#rc('font',**{'family':'serif','serif':['Palatino']})\n",
e@0 16 "rc('text', usetex=True)\n",
e@0 17 "\n",
e@0 18 "import matplotlib.pyplot as plt\n"
e@0 19 ]
e@0 20 },
e@0 21 {
e@0 22 "cell_type": "code",
e@0 23 "execution_count": 2,
e@0 24 "metadata": {},
e@0 25 "outputs": [],
e@0 26 "source": [
e@0 27 "page1_df = pd.read_csv('ratings/page1-default-ratings.csv').set_index('file_keys')\n",
e@0 28 "page2_df = pd.read_csv('ratings/page2-default-ratings.csv').set_index('file_keys')\n",
e@0 29 "page3_df = pd.read_csv('ratings/page3-default-ratings.csv').set_index('file_keys')\n",
e@0 30 "page4_df = pd.read_csv('ratings/page4-default-ratings.csv').set_index('file_keys')\n",
e@0 31 "page5_df = pd.read_csv('ratings/page5-default-ratings.csv').set_index('file_keys')\n",
e@0 32 "page6_df = pd.read_csv('ratings/page6-default-ratings.csv').set_index('file_keys')\n",
e@0 33 "page7_df = pd.read_csv('ratings/page7-default-ratings.csv').set_index('file_keys')\n",
e@0 34 "page8_df = pd.read_csv('ratings/page8-default-ratings.csv').set_index('file_keys')\n",
e@0 35 "page9_df = pd.read_csv('ratings/page9-default-ratings.csv').set_index('file_keys')"
e@0 36 ]
e@0 37 },
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e@0 812 "VyX492RQzqQXRL84PByL9pLt8C5p4c50 0.78 0.52 0.80 0.48 0.21 \n",
e@0 813 "bkHwhN78d7k2kIanOievgityZQD7gVOr 0.66 0.36 0.97 0.21 0.27 \n",
e@0 814 "bKhIcFzfZ3YXPxNiw4E7kFyoTFAqeFTp 0.49 0.00 0.22 1.00 1.00 \n",
e@0 815 "ufohn9b31ZNI2zLGNqmmRYOMtIwiw6o1 0.44 0.33 0.69 0.00 0.00 \n",
e@0 816 "fZGbsBmuEtrB35G2IzQu0IxOCVoljWpz 0.09 0.66 1.00 0.22 0.01 \n",
e@0 817 "YMVW8vVq8kZbGFRMWn9ElJBJ38bVV5GU 0.84 0.75 0.75 0.00 0.00 \n",
e@0 818 "G2WO7k3tSjvBrlMG1Nqz4DsKBO8oaEcQ 0.49 0.33 0.64 0.00 0.70 \n",
e@0 819 "OK2yLWD54tr3klqiS631VXjQlroZfmD3 0.86 0.50 1.00 0.00 0.00 \n",
e@0 820 "t1Ybl1O1EAdpBEbxOLbaU4QlHtAcGCxa 0.51 0.24 0.76 0.23 0.00 \n",
e@0 821 "JZaBaWCeuGjSAyoUrfwdASaIHXkHCZml 0.39 0.69 1.00 0.00 0.00 \n",
e@0 822 "uoBPmOWdbNI4uowtBZRZK8BIEUVvUn1o 1.00 0.49 0.91 0.06 0.00 \n",
e@0 823 "lIOWKvmCLdlUhGFYwE3lOfizSeqtxyNT 0.12 0.50 0.75 0.00 0.00 \n",
e@0 824 "\n",
e@0 825 " b10113 b11013 b11103 b11113 \n",
e@0 826 "file_keys \n",
e@0 827 "IXHrDvdwYoDCO7bvwRMB7jD46hoWAjDi 0.66 0.95 0.56 0.85 \n",
e@0 828 "iWogwaa7GooHWHcp8C0ZjRrTMDgcae0t 0.82 0.86 0.89 0.49 \n",
e@0 829 "bOyRMU1QCcMqMpcjcHNBuVMF45oksQMD 0.50 1.00 0.76 0.75 \n",
e@0 830 "U6mgdJX1DgAfYJ6DR7sKY0CL4YgcwZKq 0.70 0.97 0.44 0.83 \n",
e@0 831 "9UODgpqx7pTDhiiLm7ds39wh59aYBrHK 0.91 1.00 0.39 0.84 \n",
e@0 832 "VyX492RQzqQXRL84PByL9pLt8C5p4c50 0.98 0.59 0.86 0.92 \n",
e@0 833 "bkHwhN78d7k2kIanOievgityZQD7gVOr 0.60 0.84 0.46 0.94 \n",
e@0 834 "bKhIcFzfZ3YXPxNiw4E7kFyoTFAqeFTp 0.09 0.49 0.50 0.00 \n",
e@0 835 "ufohn9b31ZNI2zLGNqmmRYOMtIwiw6o1 1.00 0.79 0.17 1.00 \n",
e@0 836 "fZGbsBmuEtrB35G2IzQu0IxOCVoljWpz 0.99 0.10 0.35 0.63 \n",
e@0 837 "YMVW8vVq8kZbGFRMWn9ElJBJ38bVV5GU 0.71 0.95 0.98 0.87 \n",
e@0 838 "G2WO7k3tSjvBrlMG1Nqz4DsKBO8oaEcQ 0.33 0.58 0.57 0.36 \n",
e@0 839 "OK2yLWD54tr3klqiS631VXjQlroZfmD3 0.88 0.51 0.38 1.00 \n",
e@0 840 "t1Ybl1O1EAdpBEbxOLbaU4QlHtAcGCxa 0.50 0.74 0.25 1.00 \n",
e@0 841 "JZaBaWCeuGjSAyoUrfwdASaIHXkHCZml 0.90 0.41 0.68 1.00 \n",
e@0 842 "uoBPmOWdbNI4uowtBZRZK8BIEUVvUn1o 0.76 0.90 0.64 1.00 \n",
e@0 843 "lIOWKvmCLdlUhGFYwE3lOfizSeqtxyNT 1.00 0.24 0.76 0.51 \n",
e@0 844 "\n",
e@0 845 "[17 rows x 48 columns]"
e@0 846 ]
e@0 847 },
e@0 848 "execution_count": 4,
e@0 849 "metadata": {},
e@0 850 "output_type": "execute_result"
e@0 851 }
e@0 852 ],
e@0 853 "source": [
e@0 854 "big_results = page1_df.join(page2_df).join(page3_df).join(page4_df).join(page5_df).join(page6_df).join(page7_df).join(page8_df)\n",
e@0 855 "big_results"
e@0 856 ]
e@0 857 },
e@0 858 {
e@0 859 "cell_type": "code",
e@0 860 "execution_count": 5,
e@0 861 "metadata": {},
e@0 862 "outputs": [
e@0 863 {
e@0 864 "data": {
e@0 865 "image/png": 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\n",
e@0 866 "text/plain": [
e@0 867 "<matplotlib.figure.Figure at 0x7fc097d92ef0>"
e@0 868 ]
e@0 869 },
e@0 870 "metadata": {},
e@0 871 "output_type": "display_data"
e@0 872 }
e@0 873 ],
e@0 874 "source": [
e@0 875 "char_df = page1_df.join(page2_df).join(page3_df)\n",
e@0 876 "\n",
e@0 877 "immers_df = page4_df.join(page5_df).join(page6_df)\n",
e@0 878 "renamedict = {k: k[:-1] for k in immers_df.columns}\n",
e@0 879 "immers_df = immers_df.rename(columns=renamedict)\n",
e@0 880 "\n",
e@0 881 "prefer_df = page7_df.join(page8_df).join(page9_df)\n",
e@0 882 "renamedict = {k: k[:-1] for k in prefer_df.columns}\n",
e@0 883 "prefer_df = prefer_df.rename(columns=renamedict)\n",
e@0 884 "\n",
e@0 885 "plt.rc('text', usetex=True)\n",
e@0 886 "plt.rc('font', family='serif')\n",
e@0 887 "char_df.boxplot(grid=False, rot=90,fontsize=15)\n",
e@0 888 "plt.title('Character Identification')\n",
e@0 889 "plt.savefig('characterid.pdf', dpi=300)"
e@0 890 ]
e@0 891 },
e@0 892 {
e@0 893 "cell_type": "code",
e@0 894 "execution_count": 6,
e@0 895 "metadata": {},
e@0 896 "outputs": [
e@0 897 {
e@0 898 "data": {
e@0 899 "image/png": 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\n",
e@0 900 "text/plain": [
e@0 901 "<matplotlib.figure.Figure at 0x7fc097de89e8>"
e@0 902 ]
e@0 903 },
e@0 904 "metadata": {},
e@0 905 "output_type": "display_data"
e@0 906 }
e@0 907 ],
e@0 908 "source": [
e@0 909 "immers_df.boxplot(grid=False, rot=90,fontsize=15)\n",
e@0 910 "plt.title('Immersion')\n",
e@0 911 "plt.savefig('immersion.pdf', dpi=300)"
e@0 912 ]
e@0 913 },
e@0 914 {
e@0 915 "cell_type": "code",
e@0 916 "execution_count": 7,
e@0 917 "metadata": {},
e@0 918 "outputs": [
e@0 919 {
e@0 920 "data": {
e@0 921 "image/png": 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\n",
e@0 922 "text/plain": [
e@0 923 "<matplotlib.figure.Figure at 0x7fc097de82b0>"
e@0 924 ]
e@0 925 },
e@0 926 "metadata": {},
e@0 927 "output_type": "display_data"
e@0 928 }
e@0 929 ],
e@0 930 "source": [
e@0 931 "prefer_df.boxplot(grid=False, rot=90,fontsize=15)\n",
e@0 932 "plt.title('Preference')\n",
e@0 933 "plt.savefig('preference.pdf', dpi=300)"
e@0 934 ]
e@0 935 },
e@0 936 {
e@0 937 "cell_type": "code",
e@0 938 "execution_count": 8,
e@0 939 "metadata": {},
e@0 940 "outputs": [],
e@0 941 "source": [
e@0 942 "import seaborn as sns"
e@0 943 ]
e@0 944 },
e@0 945 {
e@0 946 "cell_type": "code",
e@0 947 "execution_count": null,
e@0 948 "metadata": {},
e@0 949 "outputs": [],
e@0 950 "source": []
e@0 951 },
e@0 952 {
e@0 953 "cell_type": "code",
e@0 954 "execution_count": 9,
e@0 955 "metadata": {},
e@0 956 "outputs": [
e@0 957 {
e@0 958 "data": {
e@0 959 "text/plain": [
e@0 960 "<matplotlib.axes._subplots.AxesSubplot at 0x7fc0b4983898>"
e@0 961 ]
e@0 962 },
e@0 963 "execution_count": 9,
e@0 964 "metadata": {},
e@0 965 "output_type": "execute_result"
e@0 966 },
e@0 967 {
e@0 968 "data": {
e@0 969 "image/png": 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\n",
e@0 970 "text/plain": [
e@0 971 "<matplotlib.figure.Figure at 0x7fc0b4983048>"
e@0 972 ]
e@0 973 },
e@0 974 "metadata": {},
e@0 975 "output_type": "display_data"
e@0 976 }
e@0 977 ],
e@0 978 "source": [
e@0 979 "# columns = \\\n",
e@0 980 "# ['a0000', 'b0000', 'c0000',\n",
e@0 981 "# 'a0011', 'b0011', 'c0011',\n",
e@0 982 "# 'a1011', 'b1011', 'c1011', \n",
e@0 983 "# 'a1110', 'b1110', 'c1110', \n",
e@0 984 "# 'a1111', 'b1111', 'c1111', \n",
e@0 985 "# ]\n",
e@0 986 " \n",
e@0 987 "# br = big_results[columns]\n",
e@0 988 "columns = sorted(big_results.columns)\n",
e@0 989 "br = big_results[columns]\n",
e@0 990 "br.boxplot()\n"
e@0 991 ]
e@0 992 },
e@0 993 {
e@0 994 "cell_type": "code",
e@0 995 "execution_count": 10,
e@0 996 "metadata": {},
e@0 997 "outputs": [
e@0 998 {
e@0 999 "data": {
e@0 1000 "image/png": 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ee+89SdKDBw+4TwQAIOkINZF8Pr/n/4VCIbTCAAA6y7FvNvzqV7/assIBQQpipUhWiQT26tmbDdthGCWTy7UXVooEjq9hn0g3BogU/TBKpi5vPVaKBIJ3pEWpulWUwyiZuhxAN2jYsQ4AwEEIEQCAMUIEAGCMEAEAGOvpjnUA3W9ra0svt19GOpilqqq+2N6JbP9hCiVEPM+T4ziSpNXVVU1NTUmq3e0ej8dVLBY1MTERxq4BAC0USog8evRIUm1Bq9XVVeXzeSUSCUmSbdtyXVeO48i27TB2DwC+M2fO6M2+E5HPinzydHc2/ITSJ5LJZJTJZCTVpk+xbVurq6v++uyWZalYLIaxawBAC4Uaja7rqr+/X5ZlaXNzc89r5XL50M8uLCzo7t27YRYPANCkUEOkUCj464/EYrFjzVU1OTmpycnJPc+VSiWNjIwEWkYAgLnQhvgWCgW/89xxHA0ODsrzPEm1Gsrw8HBYuwYAtEgoIeI4jubm5jQ6OqrR0VFJUiqV8jvUJdGpDgBdIJTmLNu2tbS09NrzDOsFgO7SnWPOOsTm5mZT65EEsaaJxLomAMwRIhH6xz/+oUqlrNNnTxt9/o0TtdbIFztbxmXY/mzb+LPoXlVV9eKzbX3625XIyvDis21VT0W2exwRIRKx02dP68p/DEW2/yhPEthfO0zTIUmqRrt7dAZCBMC+3jz5ZuQXOG+dYKnidkeIAG2GaTrQSfiWAEDIurmPiRBB09qhDX/rxef6kl5YoOV6NkSiPvFtvfhcVXougZ7Qpz6dPnuqK/uYejZEEJx2aMP/o/MHnXrrZGT7B3pVz4ZI1Ce+Pzp/0Nb255HsGwCC0rMhgu7DDABA6xEi6BrMAAC0HiGCrsIMAEBrESLoGtVq947FB9oVIQKg621tf248nP/lFy8lSadOml8dVFXVdpMXOF9s70iS8UwC259t660EQ3yBA/X1de9YfJhLJBJNfb4+ivLUW2eNt7H9xZuS1NR3Y/uz2sCPt86abeOtxJmmj8V+CBEAXa3ZkXL10Xq3bt0KojgdX45XhbbGOgCg+xEiAABjNGcBbYiO4PA6ghGsng6RKH+oW9ufMyQV+6IjuCasjmAEq2dDJOof6qm3EqpUKszki9fQEYxO0rMh0g4/1Nu3b+vFzhZDUgF0LDrWAQDGCBEAgDFCBABgrGf7RBCsZka6ScGMdgPQeoRIxJoZi9/sOPz6/psdix/EMMwgRrttbm42XQ4Ax0OIRKjZk2+z4/ClYMbiB7GKX5Cj3QC0DiESoXYYZgwAzSBE0FW6oXkQ6CSECLpGtzQPAp2EEEHXoHkQaD3uEwEAGAstRBzH0fj4+J7nCoWCHMdRLpcLa7cAgBYKLURs297z/0Kh4D8fj8flOE5YuwYAtEjLmrNWV1dlWZYkybIsFYvFVu0aABCSlnWsv3o3cblcPvT9CwsLunv3bphFAoC2sLi4qCdPnhz6nkqlNnqwPgBkP5cvX1Y6nQ60bI20LERisZh/EI5icnJSk5OTe57b2dnR8+fPde7cuaCLBwBt7dSp9lyCtGUhMjg4KM/zJEmu62p4ePjY2zhx4oTOnz8fdNEAIFLpdLrlNYighNYnUigUtLa25neop1Ipua7rd6i/2vEOAOg8odVEUqmUUqnUnucmJibC2h0AIALcsd7GGnW2HaWjTYqms+1VQfwt7fB3ANiLEOlg7drRZqKb/haglxAibayTO9te1U1/C4B/IkSADtNNzZzofITIAWjDR6eiaRCtRIgY4oeKqNA0GCwuGJtDiByAHyoAiQvGRggRAD2NC8bmsCgVAMAYIQIAMEaIAACM0SeCnsEoHCB4hAjw/xiFAxwfIYKewSgcIHj0iQAAjBEiAABjhAgAwBghAgAwRogAAIwRIgAAY4QIAMAYIQIAMNZXrVarURcCQOc56jQyiUTiwPcwjUzn4451AKFgGpneQE0EAGCMPhEAgDFCBABgjBABABgjRAAAxggRAIAxQgQAYIwQAQAYI0QAAMYIEQCAMUIEAGCMEAEAGCNEAADGCBEAgDFCBABgjBABABgjRAAAxggRAIAxlseN0M7Ojp4/fx51MQC0yLlz53TiRHeddrvrr+kwz58/18jISNTFANAijx8/1vnz56MuRqAIkQidO3dOUu2LheaNjIxwLAPE8QzWyMiI/5vvJoRIhOrV2m67MokSxzJYHM9gdVtTlkTHOgCgCYQIAMAYIQIAMPbmBx988EHUheh13/72t6MuQtfgWAaL4xmsbjyefdVqtRp1IQAAnYnmLACAMUIEAGCMEAEAGCNEAADGCBEAgDFCBABgrPsmcmkT+Xxey8vLkqSVlRUNDQ1JksbGxpRIJLS4uKipqakoi9jRPM/TyMiIf1wlaWpqSpZlSZKKxSLH+Iimp6fluq4kKZPJKJVKHfhe13X9Y4zXHedYdgvuE2mBq1evamlpyf8/J7jmeZ6n733ve3r48GHURelohUJBrutqYmJCUu24xuPxA9+fzWY1Pz/fquJ1lOMey25Bc1ZEVlZWND09rdHRUUm1YJmenpYk5XI5OY4j13U1PT2tbDbrX93gYLuP1+PHjzU7Oxt1kdpePB73v2v1/0t7j2U+n5dU+17Wv7ee50VW5nZ10LHc77ddLBY1Pj6u2dlZ/xzQqWjOikgikdDMzIxmZ2flOI4SicS+73McRw8fPuyJK5rjqp/oJMmyLKVSKf94EbpHY9u2PM/TzZs35Xme7ty5o2QyKcuyNDMzI6lWk85kMpqYmJDjOP7z2OugY3mYqakp/xxg23aLShosQiQi9Xbl/v7+Q99n2zYBcoDdJzqpFiocr+NLpVJKpVJyXVc3b970mwiLxaLW1tYiLl1nOehY7ueo54B2R3NWG9p9FR2LxSIsSefheB3P7u/a7tpwPp+X4zi6du0aoXxEBx3Lg97TLaiJtIlkMqm1tTXNzs6qXC5HXRz0CM/zND4+rlgsplKppJ/+9KeSalfJc3Nz+34Xs9nsnpFwqDnoWHb7b5vRWQAAYzRnAQCMESIAAGOECADAGCEChKje2Qp0K0IEAGCMEAEAGCNEgBCMj49rdHRUH330kf+c53nKZrP+P6l2z0WxWNzzOtBJCBEgYPl8XgMDA3r48KHGxsb85+PxuObn5/1ZcB3H0djYmD/BYT6fVzqdjqTMgClCBAhYsVjU8PCwpNenv3BdV/l8XqVSSZ7nybZtf34qx3F6Yv0JdBdCBAhYMpn0m6h2z5VUKBSUy+V07dq1PYtpDQ0NqVAoMI0IOhIhAgQsk8nIcRyNj49rcXHRnxTSsiw5jqO5uTk9ffrUn9hwbGxMc3Nz1ELQkZg7C2gD4+Pjun//ftTFAI6NmggQMc/zNDAwEHUxACNMBQ9EKJ/Pa3l5WR9++GHURQGM0JwFADBGcxYAwBghAgAwRogAAIwRIgAAY4QIAMAYIQIAMPZ/3PiwclUSVMMAAAAASUVORK5CYII=\n",
e@0 1001 "text/plain": [
e@0 1002 "<matplotlib.figure.Figure at 0x7fc0b4890ba8>"
e@0 1003 ]
e@0 1004 },
e@0 1005 "metadata": {},
e@0 1006 "output_type": "display_data"
e@0 1007 }
e@0 1008 ],
e@0 1009 "source": [
e@0 1010 "import seaborn as sns\n",
e@0 1011 "sns.set(style=\"ticks\")\n",
e@0 1012 "\n",
e@0 1013 "# Load the example tips dataset\n",
e@0 1014 "tips = sns.load_dataset(\"tips\")\n",
e@0 1015 "\n",
e@0 1016 "# Draw a nested boxplot to show bills by day and sex\n",
e@0 1017 "sns.boxplot(x=\"day\", y=\"total_bill\", hue=\"sex\", data=tips, palette=\"PRGn\")\n",
e@0 1018 "sns.despine(offset=10, trim=True)"
e@0 1019 ]
e@0 1020 },
e@0 1021 {
e@0 1022 "cell_type": "code",
e@0 1023 "execution_count": 13,
e@0 1024 "metadata": {},
e@0 1025 "outputs": [],
e@0 1026 "source": [
e@0 1027 "renamedict = {k: k[1:] for k in page1_df.columns}\n",
e@0 1028 "page1 = page1_df.rename(columns=renamedict)\n",
e@0 1029 "page1['story'] = 'a'\n",
e@0 1030 "renamedict = {k: k[1:] for k in page2_df.columns}\n",
e@0 1031 "page2 = page2_df.rename(columns=renamedict)\n",
e@0 1032 "page2['story'] = 'b'\n",
e@0 1033 "renamedict = {k: k[1:] for k in page3_df.columns}\n",
e@0 1034 "page3 = page3_df.rename(columns=renamedict)\n",
e@0 1035 "page3['story'] = 'c'"
e@0 1036 ]
e@0 1037 },
e@0 1038 {
e@0 1039 "cell_type": "code",
e@0 1040 "execution_count": 19,
e@0 1041 "metadata": {},
e@0 1042 "outputs": [],
e@0 1043 "source": [
e@0 1044 "chara = page1.append(page2).append(page3)"
e@0 1045 ]
e@0 1046 },
e@0 1047 {
e@0 1048 "cell_type": "code",
e@0 1049 "execution_count": 22,
e@0 1050 "metadata": {},
e@0 1051 "outputs": [
e@0 1052 {
e@0 1053 "ename": "ValueError",
e@0 1054 "evalue": "Cannot use `hue` without `x` or `y`",
e@0 1055 "output_type": "error",
e@0 1056 "traceback": [
e@0 1057 "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
e@0 1058 "\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)",
e@0 1059 "\u001b[0;32m<ipython-input-22-8b50c36471b3>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0msns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mboxplot\u001b[0m\u001b[0;34m(\u001b[0m \u001b[0mhue\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"story\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mchara\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mpalette\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"PRGn\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
e@0 1060 "\u001b[0;32m~/Projects/Public/PhD/stage3/openrgf/venvs/openrgf-venv/lib/python3.6/site-packages/seaborn/categorical.py\u001b[0m in \u001b[0;36mboxplot\u001b[0;34m(x, y, hue, data, order, hue_order, orient, color, palette, saturation, width, dodge, fliersize, linewidth, whis, notch, ax, **kwargs)\u001b[0m\n\u001b[1;32m 2209\u001b[0m plotter = _BoxPlotter(x, y, hue, data, order, hue_order,\n\u001b[1;32m 2210\u001b[0m \u001b[0morient\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcolor\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mpalette\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msaturation\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2211\u001b[0;31m width, dodge, fliersize, linewidth)\n\u001b[0m\u001b[1;32m 2212\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2213\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0max\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
e@0 1061 "\u001b[0;32m~/Projects/Public/PhD/stage3/openrgf/venvs/openrgf-venv/lib/python3.6/site-packages/seaborn/categorical.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, x, y, hue, data, order, hue_order, orient, color, palette, saturation, width, dodge, fliersize, linewidth)\u001b[0m\n\u001b[1;32m 439\u001b[0m width, dodge, fliersize, linewidth):\n\u001b[1;32m 440\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 441\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mestablish_variables\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mhue\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0morient\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0morder\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mhue_order\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 442\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mestablish_colors\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcolor\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mpalette\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msaturation\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 443\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
e@0 1062 "\u001b[0;32m~/Projects/Public/PhD/stage3/openrgf/venvs/openrgf-venv/lib/python3.6/site-packages/seaborn/categorical.py\u001b[0m in \u001b[0;36mestablish_variables\u001b[0;34m(self, x, y, hue, data, orient, order, hue_order, units)\u001b[0m\n\u001b[1;32m 42\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mhue\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 43\u001b[0m \u001b[0merror\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m\"Cannot use `hue` without `x` or `y`\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 44\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0merror\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 45\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 46\u001b[0m \u001b[0;31m# No hue grouping with wide inputs\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
e@0 1063 "\u001b[0;31mValueError\u001b[0m: Cannot use `hue` without `x` or `y`"
e@0 1064 ]
e@0 1065 }
e@0 1066 ],
e@0 1067 "source": [
e@0 1068 "sns.boxplot( hue=\"story\", data=chara, palette=\"PRGn\")"
e@0 1069 ]
e@0 1070 },
e@0 1071 {
e@0 1072 "cell_type": "code",
e@0 1073 "execution_count": 18,
e@0 1074 "metadata": {},
e@0 1075 "outputs": [
e@0 1076 {
e@0 1077 "data": {
e@0 1078 "text/html": [
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e@0 1128 " <th>2</th>\n",
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e@0 1138 " <th>3</th>\n",
e@0 1139 " <td>23.68</td>\n",
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e@0 1141 " <td>Male</td>\n",
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e@0 1148 " <th>4</th>\n",
e@0 1149 " <td>24.59</td>\n",
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e@0 1168 " <th>6</th>\n",
e@0 1169 " <td>8.77</td>\n",
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e@0 1171 " <td>Male</td>\n",
e@0 1172 " <td>No</td>\n",
e@0 1173 " <td>Sun</td>\n",
e@0 1174 " <td>Dinner</td>\n",
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e@0 1176 " </tr>\n",
e@0 1177 " <tr>\n",
e@0 1178 " <th>7</th>\n",
e@0 1179 " <td>26.88</td>\n",
e@0 1180 " <td>3.12</td>\n",
e@0 1181 " <td>Male</td>\n",
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e@0 1187 " <tr>\n",
e@0 1188 " <th>8</th>\n",
e@0 1189 " <td>15.04</td>\n",
e@0 1190 " <td>1.96</td>\n",
e@0 1191 " <td>Male</td>\n",
e@0 1192 " <td>No</td>\n",
e@0 1193 " <td>Sun</td>\n",
e@0 1194 " <td>Dinner</td>\n",
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e@0 1198 " <th>9</th>\n",
e@0 1199 " <td>14.78</td>\n",
e@0 1200 " <td>3.23</td>\n",
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e@0 1208 " <th>10</th>\n",
e@0 1209 " <td>10.27</td>\n",
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e@0 1213 " <td>Sun</td>\n",
e@0 1214 " <td>Dinner</td>\n",
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e@0 1216 " </tr>\n",
e@0 1217 " <tr>\n",
e@0 1218 " <th>11</th>\n",
e@0 1219 " <td>35.26</td>\n",
e@0 1220 " <td>5.00</td>\n",
e@0 1221 " <td>Female</td>\n",
e@0 1222 " <td>No</td>\n",
e@0 1223 " <td>Sun</td>\n",
e@0 1224 " <td>Dinner</td>\n",
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e@0 1226 " </tr>\n",
e@0 1227 " <tr>\n",
e@0 1228 " <th>12</th>\n",
e@0 1229 " <td>15.42</td>\n",
e@0 1230 " <td>1.57</td>\n",
e@0 1231 " <td>Male</td>\n",
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e@0 1233 " <td>Sun</td>\n",
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e@0 1237 " <tr>\n",
e@0 1238 " <th>13</th>\n",
e@0 1239 " <td>18.43</td>\n",
e@0 1240 " <td>3.00</td>\n",
e@0 1241 " <td>Male</td>\n",
e@0 1242 " <td>No</td>\n",
e@0 1243 " <td>Sun</td>\n",
e@0 1244 " <td>Dinner</td>\n",
e@0 1245 " <td>4</td>\n",
e@0 1246 " </tr>\n",
e@0 1247 " <tr>\n",
e@0 1248 " <th>14</th>\n",
e@0 1249 " <td>14.83</td>\n",
e@0 1250 " <td>3.02</td>\n",
e@0 1251 " <td>Female</td>\n",
e@0 1252 " <td>No</td>\n",
e@0 1253 " <td>Sun</td>\n",
e@0 1254 " <td>Dinner</td>\n",
e@0 1255 " <td>2</td>\n",
e@0 1256 " </tr>\n",
e@0 1257 " <tr>\n",
e@0 1258 " <th>15</th>\n",
e@0 1259 " <td>21.58</td>\n",
e@0 1260 " <td>3.92</td>\n",
e@0 1261 " <td>Male</td>\n",
e@0 1262 " <td>No</td>\n",
e@0 1263 " <td>Sun</td>\n",
e@0 1264 " <td>Dinner</td>\n",
e@0 1265 " <td>2</td>\n",
e@0 1266 " </tr>\n",
e@0 1267 " <tr>\n",
e@0 1268 " <th>16</th>\n",
e@0 1269 " <td>10.33</td>\n",
e@0 1270 " <td>1.67</td>\n",
e@0 1271 " <td>Female</td>\n",
e@0 1272 " <td>No</td>\n",
e@0 1273 " <td>Sun</td>\n",
e@0 1274 " <td>Dinner</td>\n",
e@0 1275 " <td>3</td>\n",
e@0 1276 " </tr>\n",
e@0 1277 " <tr>\n",
e@0 1278 " <th>17</th>\n",
e@0 1279 " <td>16.29</td>\n",
e@0 1280 " <td>3.71</td>\n",
e@0 1281 " <td>Male</td>\n",
e@0 1282 " <td>No</td>\n",
e@0 1283 " <td>Sun</td>\n",
e@0 1284 " <td>Dinner</td>\n",
e@0 1285 " <td>3</td>\n",
e@0 1286 " </tr>\n",
e@0 1287 " <tr>\n",
e@0 1288 " <th>18</th>\n",
e@0 1289 " <td>16.97</td>\n",
e@0 1290 " <td>3.50</td>\n",
e@0 1291 " <td>Female</td>\n",
e@0 1292 " <td>No</td>\n",
e@0 1293 " <td>Sun</td>\n",
e@0 1294 " <td>Dinner</td>\n",
e@0 1295 " <td>3</td>\n",
e@0 1296 " </tr>\n",
e@0 1297 " <tr>\n",
e@0 1298 " <th>19</th>\n",
e@0 1299 " <td>20.65</td>\n",
e@0 1300 " <td>3.35</td>\n",
e@0 1301 " <td>Male</td>\n",
e@0 1302 " <td>No</td>\n",
e@0 1303 " <td>Sat</td>\n",
e@0 1304 " <td>Dinner</td>\n",
e@0 1305 " <td>3</td>\n",
e@0 1306 " </tr>\n",
e@0 1307 " <tr>\n",
e@0 1308 " <th>20</th>\n",
e@0 1309 " <td>17.92</td>\n",
e@0 1310 " <td>4.08</td>\n",
e@0 1311 " <td>Male</td>\n",
e@0 1312 " <td>No</td>\n",
e@0 1313 " <td>Sat</td>\n",
e@0 1314 " <td>Dinner</td>\n",
e@0 1315 " <td>2</td>\n",
e@0 1316 " </tr>\n",
e@0 1317 " <tr>\n",
e@0 1318 " <th>21</th>\n",
e@0 1319 " <td>20.29</td>\n",
e@0 1320 " <td>2.75</td>\n",
e@0 1321 " <td>Female</td>\n",
e@0 1322 " <td>No</td>\n",
e@0 1323 " <td>Sat</td>\n",
e@0 1324 " <td>Dinner</td>\n",
e@0 1325 " <td>2</td>\n",
e@0 1326 " </tr>\n",
e@0 1327 " <tr>\n",
e@0 1328 " <th>22</th>\n",
e@0 1329 " <td>15.77</td>\n",
e@0 1330 " <td>2.23</td>\n",
e@0 1331 " <td>Female</td>\n",
e@0 1332 " <td>No</td>\n",
e@0 1333 " <td>Sat</td>\n",
e@0 1334 " <td>Dinner</td>\n",
e@0 1335 " <td>2</td>\n",
e@0 1336 " </tr>\n",
e@0 1337 " <tr>\n",
e@0 1338 " <th>23</th>\n",
e@0 1339 " <td>39.42</td>\n",
e@0 1340 " <td>7.58</td>\n",
e@0 1341 " <td>Male</td>\n",
e@0 1342 " <td>No</td>\n",
e@0 1343 " <td>Sat</td>\n",
e@0 1344 " <td>Dinner</td>\n",
e@0 1345 " <td>4</td>\n",
e@0 1346 " </tr>\n",
e@0 1347 " <tr>\n",
e@0 1348 " <th>24</th>\n",
e@0 1349 " <td>19.82</td>\n",
e@0 1350 " <td>3.18</td>\n",
e@0 1351 " <td>Male</td>\n",
e@0 1352 " <td>No</td>\n",
e@0 1353 " <td>Sat</td>\n",
e@0 1354 " <td>Dinner</td>\n",
e@0 1355 " <td>2</td>\n",
e@0 1356 " </tr>\n",
e@0 1357 " <tr>\n",
e@0 1358 " <th>25</th>\n",
e@0 1359 " <td>17.81</td>\n",
e@0 1360 " <td>2.34</td>\n",
e@0 1361 " <td>Male</td>\n",
e@0 1362 " <td>No</td>\n",
e@0 1363 " <td>Sat</td>\n",
e@0 1364 " <td>Dinner</td>\n",
e@0 1365 " <td>4</td>\n",
e@0 1366 " </tr>\n",
e@0 1367 " <tr>\n",
e@0 1368 " <th>26</th>\n",
e@0 1369 " <td>13.37</td>\n",
e@0 1370 " <td>2.00</td>\n",
e@0 1371 " <td>Male</td>\n",
e@0 1372 " <td>No</td>\n",
e@0 1373 " <td>Sat</td>\n",
e@0 1374 " <td>Dinner</td>\n",
e@0 1375 " <td>2</td>\n",
e@0 1376 " </tr>\n",
e@0 1377 " <tr>\n",
e@0 1378 " <th>27</th>\n",
e@0 1379 " <td>12.69</td>\n",
e@0 1380 " <td>2.00</td>\n",
e@0 1381 " <td>Male</td>\n",
e@0 1382 " <td>No</td>\n",
e@0 1383 " <td>Sat</td>\n",
e@0 1384 " <td>Dinner</td>\n",
e@0 1385 " <td>2</td>\n",
e@0 1386 " </tr>\n",
e@0 1387 " <tr>\n",
e@0 1388 " <th>28</th>\n",
e@0 1389 " <td>21.70</td>\n",
e@0 1390 " <td>4.30</td>\n",
e@0 1391 " <td>Male</td>\n",
e@0 1392 " <td>No</td>\n",
e@0 1393 " <td>Sat</td>\n",
e@0 1394 " <td>Dinner</td>\n",
e@0 1395 " <td>2</td>\n",
e@0 1396 " </tr>\n",
e@0 1397 " <tr>\n",
e@0 1398 " <th>29</th>\n",
e@0 1399 " <td>19.65</td>\n",
e@0 1400 " <td>3.00</td>\n",
e@0 1401 " <td>Female</td>\n",
e@0 1402 " <td>No</td>\n",
e@0 1403 " <td>Sat</td>\n",
e@0 1404 " <td>Dinner</td>\n",
e@0 1405 " <td>2</td>\n",
e@0 1406 " </tr>\n",
e@0 1407 " <tr>\n",
e@0 1408 " <th>...</th>\n",
e@0 1409 " <td>...</td>\n",
e@0 1410 " <td>...</td>\n",
e@0 1411 " <td>...</td>\n",
e@0 1412 " <td>...</td>\n",
e@0 1413 " <td>...</td>\n",
e@0 1414 " <td>...</td>\n",
e@0 1415 " <td>...</td>\n",
e@0 1416 " </tr>\n",
e@0 1417 " <tr>\n",
e@0 1418 " <th>214</th>\n",
e@0 1419 " <td>28.17</td>\n",
e@0 1420 " <td>6.50</td>\n",
e@0 1421 " <td>Female</td>\n",
e@0 1422 " <td>Yes</td>\n",
e@0 1423 " <td>Sat</td>\n",
e@0 1424 " <td>Dinner</td>\n",
e@0 1425 " <td>3</td>\n",
e@0 1426 " </tr>\n",
e@0 1427 " <tr>\n",
e@0 1428 " <th>215</th>\n",
e@0 1429 " <td>12.90</td>\n",
e@0 1430 " <td>1.10</td>\n",
e@0 1431 " <td>Female</td>\n",
e@0 1432 " <td>Yes</td>\n",
e@0 1433 " <td>Sat</td>\n",
e@0 1434 " <td>Dinner</td>\n",
e@0 1435 " <td>2</td>\n",
e@0 1436 " </tr>\n",
e@0 1437 " <tr>\n",
e@0 1438 " <th>216</th>\n",
e@0 1439 " <td>28.15</td>\n",
e@0 1440 " <td>3.00</td>\n",
e@0 1441 " <td>Male</td>\n",
e@0 1442 " <td>Yes</td>\n",
e@0 1443 " <td>Sat</td>\n",
e@0 1444 " <td>Dinner</td>\n",
e@0 1445 " <td>5</td>\n",
e@0 1446 " </tr>\n",
e@0 1447 " <tr>\n",
e@0 1448 " <th>217</th>\n",
e@0 1449 " <td>11.59</td>\n",
e@0 1450 " <td>1.50</td>\n",
e@0 1451 " <td>Male</td>\n",
e@0 1452 " <td>Yes</td>\n",
e@0 1453 " <td>Sat</td>\n",
e@0 1454 " <td>Dinner</td>\n",
e@0 1455 " <td>2</td>\n",
e@0 1456 " </tr>\n",
e@0 1457 " <tr>\n",
e@0 1458 " <th>218</th>\n",
e@0 1459 " <td>7.74</td>\n",
e@0 1460 " <td>1.44</td>\n",
e@0 1461 " <td>Male</td>\n",
e@0 1462 " <td>Yes</td>\n",
e@0 1463 " <td>Sat</td>\n",
e@0 1464 " <td>Dinner</td>\n",
e@0 1465 " <td>2</td>\n",
e@0 1466 " </tr>\n",
e@0 1467 " <tr>\n",
e@0 1468 " <th>219</th>\n",
e@0 1469 " <td>30.14</td>\n",
e@0 1470 " <td>3.09</td>\n",
e@0 1471 " <td>Female</td>\n",
e@0 1472 " <td>Yes</td>\n",
e@0 1473 " <td>Sat</td>\n",
e@0 1474 " <td>Dinner</td>\n",
e@0 1475 " <td>4</td>\n",
e@0 1476 " </tr>\n",
e@0 1477 " <tr>\n",
e@0 1478 " <th>220</th>\n",
e@0 1479 " <td>12.16</td>\n",
e@0 1480 " <td>2.20</td>\n",
e@0 1481 " <td>Male</td>\n",
e@0 1482 " <td>Yes</td>\n",
e@0 1483 " <td>Fri</td>\n",
e@0 1484 " <td>Lunch</td>\n",
e@0 1485 " <td>2</td>\n",
e@0 1486 " </tr>\n",
e@0 1487 " <tr>\n",
e@0 1488 " <th>221</th>\n",
e@0 1489 " <td>13.42</td>\n",
e@0 1490 " <td>3.48</td>\n",
e@0 1491 " <td>Female</td>\n",
e@0 1492 " <td>Yes</td>\n",
e@0 1493 " <td>Fri</td>\n",
e@0 1494 " <td>Lunch</td>\n",
e@0 1495 " <td>2</td>\n",
e@0 1496 " </tr>\n",
e@0 1497 " <tr>\n",
e@0 1498 " <th>222</th>\n",
e@0 1499 " <td>8.58</td>\n",
e@0 1500 " <td>1.92</td>\n",
e@0 1501 " <td>Male</td>\n",
e@0 1502 " <td>Yes</td>\n",
e@0 1503 " <td>Fri</td>\n",
e@0 1504 " <td>Lunch</td>\n",
e@0 1505 " <td>1</td>\n",
e@0 1506 " </tr>\n",
e@0 1507 " <tr>\n",
e@0 1508 " <th>223</th>\n",
e@0 1509 " <td>15.98</td>\n",
e@0 1510 " <td>3.00</td>\n",
e@0 1511 " <td>Female</td>\n",
e@0 1512 " <td>No</td>\n",
e@0 1513 " <td>Fri</td>\n",
e@0 1514 " <td>Lunch</td>\n",
e@0 1515 " <td>3</td>\n",
e@0 1516 " </tr>\n",
e@0 1517 " <tr>\n",
e@0 1518 " <th>224</th>\n",
e@0 1519 " <td>13.42</td>\n",
e@0 1520 " <td>1.58</td>\n",
e@0 1521 " <td>Male</td>\n",
e@0 1522 " <td>Yes</td>\n",
e@0 1523 " <td>Fri</td>\n",
e@0 1524 " <td>Lunch</td>\n",
e@0 1525 " <td>2</td>\n",
e@0 1526 " </tr>\n",
e@0 1527 " <tr>\n",
e@0 1528 " <th>225</th>\n",
e@0 1529 " <td>16.27</td>\n",
e@0 1530 " <td>2.50</td>\n",
e@0 1531 " <td>Female</td>\n",
e@0 1532 " <td>Yes</td>\n",
e@0 1533 " <td>Fri</td>\n",
e@0 1534 " <td>Lunch</td>\n",
e@0 1535 " <td>2</td>\n",
e@0 1536 " </tr>\n",
e@0 1537 " <tr>\n",
e@0 1538 " <th>226</th>\n",
e@0 1539 " <td>10.09</td>\n",
e@0 1540 " <td>2.00</td>\n",
e@0 1541 " <td>Female</td>\n",
e@0 1542 " <td>Yes</td>\n",
e@0 1543 " <td>Fri</td>\n",
e@0 1544 " <td>Lunch</td>\n",
e@0 1545 " <td>2</td>\n",
e@0 1546 " </tr>\n",
e@0 1547 " <tr>\n",
e@0 1548 " <th>227</th>\n",
e@0 1549 " <td>20.45</td>\n",
e@0 1550 " <td>3.00</td>\n",
e@0 1551 " <td>Male</td>\n",
e@0 1552 " <td>No</td>\n",
e@0 1553 " <td>Sat</td>\n",
e@0 1554 " <td>Dinner</td>\n",
e@0 1555 " <td>4</td>\n",
e@0 1556 " </tr>\n",
e@0 1557 " <tr>\n",
e@0 1558 " <th>228</th>\n",
e@0 1559 " <td>13.28</td>\n",
e@0 1560 " <td>2.72</td>\n",
e@0 1561 " <td>Male</td>\n",
e@0 1562 " <td>No</td>\n",
e@0 1563 " <td>Sat</td>\n",
e@0 1564 " <td>Dinner</td>\n",
e@0 1565 " <td>2</td>\n",
e@0 1566 " </tr>\n",
e@0 1567 " <tr>\n",
e@0 1568 " <th>229</th>\n",
e@0 1569 " <td>22.12</td>\n",
e@0 1570 " <td>2.88</td>\n",
e@0 1571 " <td>Female</td>\n",
e@0 1572 " <td>Yes</td>\n",
e@0 1573 " <td>Sat</td>\n",
e@0 1574 " <td>Dinner</td>\n",
e@0 1575 " <td>2</td>\n",
e@0 1576 " </tr>\n",
e@0 1577 " <tr>\n",
e@0 1578 " <th>230</th>\n",
e@0 1579 " <td>24.01</td>\n",
e@0 1580 " <td>2.00</td>\n",
e@0 1581 " <td>Male</td>\n",
e@0 1582 " <td>Yes</td>\n",
e@0 1583 " <td>Sat</td>\n",
e@0 1584 " <td>Dinner</td>\n",
e@0 1585 " <td>4</td>\n",
e@0 1586 " </tr>\n",
e@0 1587 " <tr>\n",
e@0 1588 " <th>231</th>\n",
e@0 1589 " <td>15.69</td>\n",
e@0 1590 " <td>3.00</td>\n",
e@0 1591 " <td>Male</td>\n",
e@0 1592 " <td>Yes</td>\n",
e@0 1593 " <td>Sat</td>\n",
e@0 1594 " <td>Dinner</td>\n",
e@0 1595 " <td>3</td>\n",
e@0 1596 " </tr>\n",
e@0 1597 " <tr>\n",
e@0 1598 " <th>232</th>\n",
e@0 1599 " <td>11.61</td>\n",
e@0 1600 " <td>3.39</td>\n",
e@0 1601 " <td>Male</td>\n",
e@0 1602 " <td>No</td>\n",
e@0 1603 " <td>Sat</td>\n",
e@0 1604 " <td>Dinner</td>\n",
e@0 1605 " <td>2</td>\n",
e@0 1606 " </tr>\n",
e@0 1607 " <tr>\n",
e@0 1608 " <th>233</th>\n",
e@0 1609 " <td>10.77</td>\n",
e@0 1610 " <td>1.47</td>\n",
e@0 1611 " <td>Male</td>\n",
e@0 1612 " <td>No</td>\n",
e@0 1613 " <td>Sat</td>\n",
e@0 1614 " <td>Dinner</td>\n",
e@0 1615 " <td>2</td>\n",
e@0 1616 " </tr>\n",
e@0 1617 " <tr>\n",
e@0 1618 " <th>234</th>\n",
e@0 1619 " <td>15.53</td>\n",
e@0 1620 " <td>3.00</td>\n",
e@0 1621 " <td>Male</td>\n",
e@0 1622 " <td>Yes</td>\n",
e@0 1623 " <td>Sat</td>\n",
e@0 1624 " <td>Dinner</td>\n",
e@0 1625 " <td>2</td>\n",
e@0 1626 " </tr>\n",
e@0 1627 " <tr>\n",
e@0 1628 " <th>235</th>\n",
e@0 1629 " <td>10.07</td>\n",
e@0 1630 " <td>1.25</td>\n",
e@0 1631 " <td>Male</td>\n",
e@0 1632 " <td>No</td>\n",
e@0 1633 " <td>Sat</td>\n",
e@0 1634 " <td>Dinner</td>\n",
e@0 1635 " <td>2</td>\n",
e@0 1636 " </tr>\n",
e@0 1637 " <tr>\n",
e@0 1638 " <th>236</th>\n",
e@0 1639 " <td>12.60</td>\n",
e@0 1640 " <td>1.00</td>\n",
e@0 1641 " <td>Male</td>\n",
e@0 1642 " <td>Yes</td>\n",
e@0 1643 " <td>Sat</td>\n",
e@0 1644 " <td>Dinner</td>\n",
e@0 1645 " <td>2</td>\n",
e@0 1646 " </tr>\n",
e@0 1647 " <tr>\n",
e@0 1648 " <th>237</th>\n",
e@0 1649 " <td>32.83</td>\n",
e@0 1650 " <td>1.17</td>\n",
e@0 1651 " <td>Male</td>\n",
e@0 1652 " <td>Yes</td>\n",
e@0 1653 " <td>Sat</td>\n",
e@0 1654 " <td>Dinner</td>\n",
e@0 1655 " <td>2</td>\n",
e@0 1656 " </tr>\n",
e@0 1657 " <tr>\n",
e@0 1658 " <th>238</th>\n",
e@0 1659 " <td>35.83</td>\n",
e@0 1660 " <td>4.67</td>\n",
e@0 1661 " <td>Female</td>\n",
e@0 1662 " <td>No</td>\n",
e@0 1663 " <td>Sat</td>\n",
e@0 1664 " <td>Dinner</td>\n",
e@0 1665 " <td>3</td>\n",
e@0 1666 " </tr>\n",
e@0 1667 " <tr>\n",
e@0 1668 " <th>239</th>\n",
e@0 1669 " <td>29.03</td>\n",
e@0 1670 " <td>5.92</td>\n",
e@0 1671 " <td>Male</td>\n",
e@0 1672 " <td>No</td>\n",
e@0 1673 " <td>Sat</td>\n",
e@0 1674 " <td>Dinner</td>\n",
e@0 1675 " <td>3</td>\n",
e@0 1676 " </tr>\n",
e@0 1677 " <tr>\n",
e@0 1678 " <th>240</th>\n",
e@0 1679 " <td>27.18</td>\n",
e@0 1680 " <td>2.00</td>\n",
e@0 1681 " <td>Female</td>\n",
e@0 1682 " <td>Yes</td>\n",
e@0 1683 " <td>Sat</td>\n",
e@0 1684 " <td>Dinner</td>\n",
e@0 1685 " <td>2</td>\n",
e@0 1686 " </tr>\n",
e@0 1687 " <tr>\n",
e@0 1688 " <th>241</th>\n",
e@0 1689 " <td>22.67</td>\n",
e@0 1690 " <td>2.00</td>\n",
e@0 1691 " <td>Male</td>\n",
e@0 1692 " <td>Yes</td>\n",
e@0 1693 " <td>Sat</td>\n",
e@0 1694 " <td>Dinner</td>\n",
e@0 1695 " <td>2</td>\n",
e@0 1696 " </tr>\n",
e@0 1697 " <tr>\n",
e@0 1698 " <th>242</th>\n",
e@0 1699 " <td>17.82</td>\n",
e@0 1700 " <td>1.75</td>\n",
e@0 1701 " <td>Male</td>\n",
e@0 1702 " <td>No</td>\n",
e@0 1703 " <td>Sat</td>\n",
e@0 1704 " <td>Dinner</td>\n",
e@0 1705 " <td>2</td>\n",
e@0 1706 " </tr>\n",
e@0 1707 " <tr>\n",
e@0 1708 " <th>243</th>\n",
e@0 1709 " <td>18.78</td>\n",
e@0 1710 " <td>3.00</td>\n",
e@0 1711 " <td>Female</td>\n",
e@0 1712 " <td>No</td>\n",
e@0 1713 " <td>Thur</td>\n",
e@0 1714 " <td>Dinner</td>\n",
e@0 1715 " <td>2</td>\n",
e@0 1716 " </tr>\n",
e@0 1717 " </tbody>\n",
e@0 1718 "</table>\n",
e@0 1719 "<p>244 rows × 7 columns</p>\n",
e@0 1720 "</div>"
e@0 1721 ],
e@0 1722 "text/plain": [
e@0 1723 " total_bill tip sex smoker day time size\n",
e@0 1724 "0 16.99 1.01 Female No Sun Dinner 2\n",
e@0 1725 "1 10.34 1.66 Male No Sun Dinner 3\n",
e@0 1726 "2 21.01 3.50 Male No Sun Dinner 3\n",
e@0 1727 "3 23.68 3.31 Male No Sun Dinner 2\n",
e@0 1728 "4 24.59 3.61 Female No Sun Dinner 4\n",
e@0 1729 "5 25.29 4.71 Male No Sun Dinner 4\n",
e@0 1730 "6 8.77 2.00 Male No Sun Dinner 2\n",
e@0 1731 "7 26.88 3.12 Male No Sun Dinner 4\n",
e@0 1732 "8 15.04 1.96 Male No Sun Dinner 2\n",
e@0 1733 "9 14.78 3.23 Male No Sun Dinner 2\n",
e@0 1734 "10 10.27 1.71 Male No Sun Dinner 2\n",
e@0 1735 "11 35.26 5.00 Female No Sun Dinner 4\n",
e@0 1736 "12 15.42 1.57 Male No Sun Dinner 2\n",
e@0 1737 "13 18.43 3.00 Male No Sun Dinner 4\n",
e@0 1738 "14 14.83 3.02 Female No Sun Dinner 2\n",
e@0 1739 "15 21.58 3.92 Male No Sun Dinner 2\n",
e@0 1740 "16 10.33 1.67 Female No Sun Dinner 3\n",
e@0 1741 "17 16.29 3.71 Male No Sun Dinner 3\n",
e@0 1742 "18 16.97 3.50 Female No Sun Dinner 3\n",
e@0 1743 "19 20.65 3.35 Male No Sat Dinner 3\n",
e@0 1744 "20 17.92 4.08 Male No Sat Dinner 2\n",
e@0 1745 "21 20.29 2.75 Female No Sat Dinner 2\n",
e@0 1746 "22 15.77 2.23 Female No Sat Dinner 2\n",
e@0 1747 "23 39.42 7.58 Male No Sat Dinner 4\n",
e@0 1748 "24 19.82 3.18 Male No Sat Dinner 2\n",
e@0 1749 "25 17.81 2.34 Male No Sat Dinner 4\n",
e@0 1750 "26 13.37 2.00 Male No Sat Dinner 2\n",
e@0 1751 "27 12.69 2.00 Male No Sat Dinner 2\n",
e@0 1752 "28 21.70 4.30 Male No Sat Dinner 2\n",
e@0 1753 "29 19.65 3.00 Female No Sat Dinner 2\n",
e@0 1754 ".. ... ... ... ... ... ... ...\n",
e@0 1755 "214 28.17 6.50 Female Yes Sat Dinner 3\n",
e@0 1756 "215 12.90 1.10 Female Yes Sat Dinner 2\n",
e@0 1757 "216 28.15 3.00 Male Yes Sat Dinner 5\n",
e@0 1758 "217 11.59 1.50 Male Yes Sat Dinner 2\n",
e@0 1759 "218 7.74 1.44 Male Yes Sat Dinner 2\n",
e@0 1760 "219 30.14 3.09 Female Yes Sat Dinner 4\n",
e@0 1761 "220 12.16 2.20 Male Yes Fri Lunch 2\n",
e@0 1762 "221 13.42 3.48 Female Yes Fri Lunch 2\n",
e@0 1763 "222 8.58 1.92 Male Yes Fri Lunch 1\n",
e@0 1764 "223 15.98 3.00 Female No Fri Lunch 3\n",
e@0 1765 "224 13.42 1.58 Male Yes Fri Lunch 2\n",
e@0 1766 "225 16.27 2.50 Female Yes Fri Lunch 2\n",
e@0 1767 "226 10.09 2.00 Female Yes Fri Lunch 2\n",
e@0 1768 "227 20.45 3.00 Male No Sat Dinner 4\n",
e@0 1769 "228 13.28 2.72 Male No Sat Dinner 2\n",
e@0 1770 "229 22.12 2.88 Female Yes Sat Dinner 2\n",
e@0 1771 "230 24.01 2.00 Male Yes Sat Dinner 4\n",
e@0 1772 "231 15.69 3.00 Male Yes Sat Dinner 3\n",
e@0 1773 "232 11.61 3.39 Male No Sat Dinner 2\n",
e@0 1774 "233 10.77 1.47 Male No Sat Dinner 2\n",
e@0 1775 "234 15.53 3.00 Male Yes Sat Dinner 2\n",
e@0 1776 "235 10.07 1.25 Male No Sat Dinner 2\n",
e@0 1777 "236 12.60 1.00 Male Yes Sat Dinner 2\n",
e@0 1778 "237 32.83 1.17 Male Yes Sat Dinner 2\n",
e@0 1779 "238 35.83 4.67 Female No Sat Dinner 3\n",
e@0 1780 "239 29.03 5.92 Male No Sat Dinner 3\n",
e@0 1781 "240 27.18 2.00 Female Yes Sat Dinner 2\n",
e@0 1782 "241 22.67 2.00 Male Yes Sat Dinner 2\n",
e@0 1783 "242 17.82 1.75 Male No Sat Dinner 2\n",
e@0 1784 "243 18.78 3.00 Female No Thur Dinner 2\n",
e@0 1785 "\n",
e@0 1786 "[244 rows x 7 columns]"
e@0 1787 ]
e@0 1788 },
e@0 1789 "execution_count": 18,
e@0 1790 "metadata": {},
e@0 1791 "output_type": "execute_result"
e@0 1792 }
e@0 1793 ],
e@0 1794 "source": [
e@0 1795 "tips"
e@0 1796 ]
e@0 1797 }
e@0 1798 ],
e@0 1799 "metadata": {
e@0 1800 "kernelspec": {
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