Pandas Groupby and Python Graphs Exercise

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ExerciseforPandasGroupby-Pivot-Graphs-Charts.zip
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BostonHousing.csv

CRIM ZN INDUS CHAS NOX RM AGE DIS RAD TAX PTRATIO LSTAT MEDV
0.00632 18 2.31 0 0.538 6.575 65.2 4.09 1 296 15.3 4.98 24
0.02731 0 7.07 0 0.469 6.421 78.9 4.9671 2 242 17.8 9.14 21.6
0.02729 0 7.07 0 0.469 7.185 61.1 4.9671 2 242 17.8 4.03 34.7
0.03237 0 2.18 0 0.458 6.998 45.8 6.0622 3 222 18.7 2.94 33.4
0.06905 0 2.18 0 0.458 7.147 54.2 6.0622 3 222 18.7 5.33 36.2
0.02985 0 2.18 0 0.458 6.43 58.7 6.0622 3 222 18.7 5.21 28.7
0.08829 12.5 7.87 0 0.524 6.012 66.6 5.5605 5 311 15.2 12.43 22.9
0.14455 12.5 7.87 0 0.524 6.172 96.1 5.9505 5 311 15.2 19.15 27.1
0.21124 12.5 7.87 0 0.524 5.631 100 6.0821 5 311 15.2 29.93 16.5
0.17004 12.5 7.87 0 0.524 6.004 85.9 6.5921 5 311 15.2 17.1 18.9
0.22489 12.5 7.87 0 0.524 6.377 94.3 6.3467 5 311 15.2 20.45 15
0.11747 12.5 7.87 0 0.524 6.009 82.9 6.2267 5 311 15.2 13.27 18.9
0.09378 12.5 7.87 0 0.524 5.889 39 5.4509 5 311 15.2 15.71 21.7
0.62976 0 8.14 0 0.538 5.949 61.8 4.7075 4 307 21 8.26 20.4
0.63796 0 8.14 0 0.538 6.096 84.5 4.4619 4 307 21 10.26 18.2
0.62739 0 8.14 0 0.538 5.834 56.5 4.4986 4 307 21 8.47 19.9
1.05393 0 8.14 0 0.538 5.935 29.3 4.4986 4 307 21 6.58 23.1
0.7842 0 8.14 0 0.538 5.99 81.7 4.2579 4 307 21 14.67 17.5
0.80271 0 8.14 0 0.538 5.456 36.6 3.7965 4 307 21 11.69 20.2
0.7258 0 8.14 0 0.538 5.727 69.5 3.7965 4 307 21 11.28 18.2
1.25179 0 8.14 0 0.538 5.57 98.1 3.7979 4 307 21 21.02 13.6
0.85204 0 8.14 0 0.538 5.965 89.2 4.0123 4 307 21 13.83 19.6
1.23247 0 8.14 0 0.538 6.142 91.7 3.9769 4 307 21 18.72 15.2
0.98843 0 8.14 0 0.538 5.813 100 4.0952 4 307 21 19.88 14.5
0.75026 0 8.14 0 0.538 5.924 94.1 4.3996 4 307 21 16.3 15.6
0.84054 0 8.14 0 0.538 5.599 85.7 4.4546 4 307 21 16.51 13.9
0.67191 0 8.14 0 0.538 5.813 90.3 4.682 4 307 21 14.81 16.6
0.95577 0 8.14 0 0.538 6.047 88.8 4.4534 4 307 21 17.28 14.8
0.77299 0 8.14 0 0.538 6.495 94.4 4.4547 4 307 21 12.8 18.4
1.00245 0 8.14 0 0.538 6.674 87.3 4.239 4 307 21 11.98 21
1.13081 0 8.14 0 0.538 5.713 94.1 4.233 4 307 21 22.6 12.7
1.35472 0 8.14 0 0.538 6.072 100 4.175 4 307 21 13.04 14.5
1.38799 0 8.14 0 0.538 5.95 82 3.99 4 307 21 27.71 13.2
1.15172 0 8.14 0 0.538 5.701 95 3.7872 4 307 21 18.35 13.1
1.61282 0 8.14 0 0.538 6.096 96.9 3.7598 4 307 21 20.34 13.5
0.06417 0 5.96 0 0.499 5.933 68.2 3.3603 5 279 19.2 9.68 18.9
0.09744 0 5.96 0 0.499 5.841 61.4 3.3779 5 279 19.2 11.41 20
0.08014 0 5.96 0 0.499 5.85 41.5 3.9342 5 279 19.2 8.77 21
0.17505 0 5.96 0 0.499 5.966 30.2 3.8473 5 279 19.2 10.13 24.7
0.02763 75 2.95 0 0.428 6.595 21.8 5.4011 3 252 18.3 4.32 30.8
0.03359 75 2.95 0 0.428 7.024 15.8 5.4011 3 252 18.3 1.98 34.9
0.12744 0 6.91 0 0.448 6.77 2.9 5.7209 3 233 17.9 4.84 26.6
0.1415 0 6.91 0 0.448 6.169 6.6 5.7209 3 233 17.9 5.81 25.3
0.15936 0 6.91 0 0.448 6.211 6.5 5.7209 3 233 17.9 7.44 24.7
0.12269 0 6.91 0 0.448 6.069 40 5.7209 3 233 17.9 9.55 21.2
0.17142 0 6.91 0 0.448 5.682 33.8 5.1004 3 233 17.9 10.21 19.3
0.18836 0 6.91 0 0.448 5.786 33.3 5.1004 3 233 17.9 14.15 20
0.22927 0 6.91 0 0.448 6.03 85.5 5.6894 3 233 17.9 18.8 16.6
0.25387 0 6.91 0 0.448 5.399 95.3 5.87 3 233 17.9 30.81 14.4
0.21977 0 6.91 0 0.448 5.602 62 6.0877 3 233 17.9 16.2 19.4
0.08873 21 5.64 0 0.439 5.963 45.7 6.8147 4 243 16.8 13.45 19.7
0.04337 21 5.64 0 0.439 6.115 63 6.8147 4 243 16.8 9.43 20.5
0.0536 21 5.64 0 0.439 6.511 21.1 6.8147 4 243 16.8 5.28 25
0.04981 21 5.64 0 0.439 5.998 21.4 6.8147 4 243 16.8 8.43 23.4
0.0136 75 4 0 0.41 5.888 47.6 7.3197 3 469 21.1 14.8 18.9
0.01311 90 1.22 0 0.403 7.249 21.9 8.6966 5 226 17.9 4.81 35.4
0.02055 85 0.74 0 0.41 6.383 35.7 9.1876 2 313 17.3 5.77 24.7
0.01432 100 1.32 0 0.411 6.816 40.5 8.3248 5 256 15.1 3.95 31.6
0.15445 25 5.13 0 0.453 6.145 29.2 7.8148 8 284 19.7 6.86 23.3
0.10328 25 5.13 0 0.453 5.927 47.2 6.932 8 284 19.7 9.22 19.6
0.14932 25 5.13 0 0.453 5.741 66.2 7.2254 8 284 19.7 13.15 18.7
0.17171 25 5.13 0 0.453 5.966 93.4 6.8185 8 284 19.7 14.44 16
0.11027 25 5.13 0 0.453 6.456 67.8 7.2255 8 284 19.7 6.73 22.2
0.1265 25 5.13 0 0.453 6.762 43.4 7.9809 8 284 19.7 9.5 25
0.01951 17.5 1.38 0 0.4161 7.104 59.5 9.2229 3 216 18.6 8.05 33
0.03584 80 3.37 0 0.398 6.29 17.8 6.6115 4 337 16.1 4.67 23.5
0.04379 80 3.37 0 0.398 5.787 31.1 6.6115 4 337 16.1 10.24 19.4
0.05789 12.5 6.07 0 0.409 5.878 21.4 6.498 4 345 18.9 8.1 22
0.13554 12.5 6.07 0 0.409 5.594 36.8 6.498 4 345 18.9 13.09 17.4
0.12816 12.5 6.07 0 0.409 5.885 33 6.498 4 345 18.9 8.79 20.9
0.08826 0 10.81 0 0.413 6.417 6.6 5.2873 4 305 19.2 6.72 24.2
0.15876 0 10.81 0 0.413 5.961 17.5 5.2873 4 305 19.2 9.88 21.7
0.09164 0 10.81 0 0.413 6.065 7.8 5.2873 4 305 19.2 5.52 22.8
0.19539 0 10.81 0 0.413 6.245 6.2 5.2873 4 305 19.2 7.54 23.4
0.07896 0 12.83 0 0.437 6.273 6 4.2515 5 398 18.7 6.78 24.1
0.09512 0 12.83 0 0.437 6.286 45 4.5026 5 398 18.7 8.94 21.4
0.10153 0 12.83 0 0.437 6.279 74.5 4.0522 5 398 18.7 11.97 20
0.08707 0 12.83 0 0.437 6.14 45.8 4.0905 5 398 18.7 10.27 20.8
0.05646 0 12.83 0 0.437 6.232 53.7 5.0141 5 398 18.7 12.34 21.2
0.08387 0 12.83 0 0.437 5.874 36.6 4.5026 5 398 18.7 9.1 20.3
0.04113 25 4.86 0 0.426 6.727 33.5 5.4007 4 281 19 5.29 28
0.04462 25 4.86 0 0.426 6.619 70.4 5.4007 4 281 19 7.22 23.9
0.03659 25 4.86 0 0.426 6.302 32.2 5.4007 4 281 19 6.72 24.8
0.03551 25 4.86 0 0.426 6.167 46.7 5.4007 4 281 19 7.51 22.9
0.05059 0 4.49 0 0.449 6.389 48 4.7794 3 247 18.5 9.62 23.9
0.05735 0 4.49 0 0.449 6.63 56.1 4.4377 3 247 18.5 6.53 26.6
0.05188 0 4.49 0 0.449 6.015 45.1 4.4272 3 247 18.5 12.86 22.5
0.07151 0 4.49 0 0.449 6.121 56.8 3.7476 3 247 18.5 8.44 22.2
0.0566 0 3.41 0 0.489 7.007 86.3 3.4217 2 270 17.8 5.5 23.6
0.05302 0 3.41 0 0.489 7.079 63.1 3.4145 2 270 17.8 5.7 28.7
0.04684 0 3.41 0 0.489 6.417 66.1 3.0923 2 270 17.8 8.81 22.6
0.03932 0 3.41 0 0.489 6.405 73.9 3.0921 2 270 17.8 8.2 22
0.04203 28 15.04 0 0.464 6.442 53.6 3.6659 4 270 18.2 8.16 22.9
0.02875 28 15.04 0 0.464 6.211 28.9 3.6659 4 270 18.2 6.21 25
0.04294 28 15.04 0 0.464 6.249 77.3 3.615 4 270 18.2 10.59 20.6
0.12204 0 2.89 0 0.445 6.625 57.8 3.4952 2 276 18 6.65 28.4
0.11504 0 2.89 0 0.445 6.163 69.6 3.4952 2 276 18 11.34 21.4
0.12083 0 2.89 0 0.445 8.069 76 3.4952 2 276 18 4.21 38.7
0.08187 0 2.89 0 0.445 7.82 36.9 3.4952 2 276 18 3.57 43.8
0.0686 0 2.89 0 0.445 7.416 62.5 3.4952 2 276 18 6.19 33.2
0.14866 0 8.56 0 0.52 6.727 79.9 2.7778 5 384 20.9 9.42 27.5
0.11432 0 8.56 0 0.52 6.781 71.3 2.8561 5 384 20.9 7.67 26.5
0.22876 0 8.56 0 0.52 6.405 85.4 2.7147 5 384 20.9 10.63 18.6
0.21161 0 8.56 0 0.52 6.137 87.4 2.7147 5 384 20.9 13.44 19.3
0.1396 0 8.56 0 0.52 6.167 90 2.421 5 384 20.9 12.33 20.1
0.13262 0 8.56 0 0.52 5.851 96.7 2.1069 5 384 20.9 16.47 19.5
0.1712 0 8.56 0 0.52 5.836 91.9 2.211 5 384 20.9 18.66 19.5
0.13117 0 8.56 0 0.52 6.127 85.2 2.1224 5 384 20.9 14.09 20.4
0.12802 0 8.56 0 0.52 6.474 97.1 2.4329 5 384 20.9 12.27 19.8
0.26363 0 8.56 0 0.52 6.229 91.2 2.5451 5 384 20.9 15.55 19.4
0.10793 0 8.56 0 0.52 6.195 54.4 2.7778 5 384 20.9 13 21.7
0.10084 0 10.01 0 0.547 6.715 81.6 2.6775 6 432 17.8 10.16 22.8
0.12329 0 10.01 0 0.547 5.913 92.9 2.3534 6 432 17.8 16.21 18.8
0.22212 0 10.01 0 0.547 6.092 95.4 2.548 6 432 17.8 17.09 18.7
0.14231 0 10.01 0 0.547 6.254 84.2 2.2565 6 432 17.8 10.45 18.5
0.17134 0 10.01 0 0.547 5.928 88.2 2.4631 6 432 17.8 15.76 18.3
0.13158 0 10.01 0 0.547 6.176 72.5 2.7301 6 432 17.8 12.04 21.2
0.15098 0 10.01 0 0.547 6.021 82.6 2.7474 6 432 17.8 10.3 19.2
0.13058 0 10.01 0 0.547 5.872 73.1 2.4775 6 432 17.8 15.37 20.4
0.14476 0 10.01 0 0.547 5.731 65.2 2.7592 6 432 17.8 13.61 19.3
0.06899 0 25.65 0 0.581 5.87 69.7 2.2577 2 188 19.1 14.37 22
0.07165 0 25.65 0 0.581 6.004 84.1 2.1974 2 188 19.1 14.27 20.3
0.09299 0 25.65 0 0.581 5.961 92.9 2.0869 2 188 19.1 17.93 20.5
0.15038 0 25.65 0 0.581 5.856 97 1.9444 2 188 19.1 25.41 17.3
0.09849 0 25.65 0 0.581 5.879 95.8 2.0063 2 188 19.1 17.58 18.8
0.16902 0 25.65 0 0.581 5.986 88.4 1.9929 2 188 19.1 14.81 21.4
0.38735 0 25.65 0 0.581 5.613 95.6 1.7572 2 188 19.1 27.26 15.7
0.25915 0 21.89 0 0.624 5.693 96 1.7883 4 437 21.2 17.19 16.2
0.32543 0 21.89 0 0.624 6.431 98.8 1.8125 4 437 21.2 15.39 18
0.88125 0 21.89 0 0.624 5.637 94.7 1.9799 4 437 21.2 18.34 14.3
0.34006 0 21.89 0 0.624 6.458 98.9 2.1185 4 437 21.2 12.6 19.2
1.19294 0 21.89 0 0.624 6.326 97.7 2.271 4 437 21.2 12.26 19.6
0.59005 0 21.89 0 0.624 6.372 97.9 2.3274 4 437 21.2 11.12 23
0.32982 0 21.89 0 0.624 5.822 95.4 2.4699 4 437 21.2 15.03 18.4
0.97617 0 21.89 0 0.624 5.757 98.4 2.346 4 437 21.2 17.31 15.6
0.55778 0 21.89 0 0.624 6.335 98.2 2.1107 4 437 21.2 16.96 18.1
0.32264 0 21.89 0 0.624 5.942 93.5 1.9669 4 437 21.2 16.9 17.4
0.35233 0 21.89 0 0.624 6.454 98.4 1.8498 4 437 21.2 14.59 17.1
0.2498 0 21.89 0 0.624 5.857 98.2 1.6686 4 437 21.2 21.32 13.3
0.54452 0 21.89 0 0.624 6.151 97.9 1.6687 4 437 21.2 18.46 17.8
0.2909 0 21.89 0 0.624 6.174 93.6 1.6119 4 437 21.2 24.16 14
1.62864 0 21.89 0 0.624 5.019 100 1.4394 4 437 21.2 34.41 14.4
3.32105 0 19.58 1 0.871 5.403 100 1.3216 5 403 14.7 26.82 13.4
4.0974 0 19.58 0 0.871 5.468 100 1.4118 5 403 14.7 26.42 15.6
2.77974 0 19.58 0 0.871 4.903 97.8 1.3459 5 403 14.7 29.29 11.8
2.37934 0 19.58 0 0.871 6.13 100 1.4191 5 403 14.7 27.8 13.8
2.15505 0 19.58 0 0.871 5.628 100 1.5166 5 403 14.7 16.65 15.6
2.36862 0 19.58 0 0.871 4.926 95.7 1.4608 5 403 14.7 29.53 14.6
2.33099 0 19.58 0 0.871 5.186 93.8 1.5296 5 403 14.7 28.32 17.8
2.73397 0 19.58 0 0.871 5.597 94.9 1.5257 5 403 14.7 21.45 15.4
1.6566 0 19.58 0 0.871 6.122 97.3 1.618 5 403 14.7 14.1 21.5
1.49632 0 19.58 0 0.871 5.404 100 1.5916 5 403 14.7 13.28 19.6
1.12658 0 19.58 1 0.871 5.012 88 1.6102 5 403 14.7 12.12 15.3
2.14918 0 19.58 0 0.871 5.709 98.5 1.6232 5 403 14.7 15.79 19.4
1.41385 0 19.58 1 0.871 6.129 96 1.7494 5 403 14.7 15.12 17
3.53501 0 19.58 1 0.871 6.152 82.6 1.7455 5 403 14.7 15.02 15.6
2.44668 0 19.58 0 0.871 5.272 94 1.7364 5 403 14.7 16.14 13.1
1.22358 0 19.58 0 0.605 6.943 97.4 1.8773 5 403 14.7 4.59 41.3
1.34284 0 19.58 0 0.605 6.066 100 1.7573 5 403 14.7 6.43 24.3
1.42502 0 19.58 0 0.871 6.51 100 1.7659 5 403 14.7 7.39 23.3
1.27346 0 19.58 1 0.605 6.25 92.6 1.7984 5 403 14.7 5.5 27
1.46336 0 19.58 0 0.605 7.489 90.8 1.9709 5 403 14.7 1.73 50
1.83377 0 19.58 1 0.605 7.802 98.2 2.0407 5 403 14.7 1.92 50
1.51902 0 19.58 1 0.605 8.375 93.9 2.162 5 403 14.7 3.32 50
2.24236 0 19.58 0 0.605 5.854 91.8 2.422 5 403 14.7 11.64 22.7
2.924 0 19.58 0 0.605 6.101 93 2.2834 5 403 14.7 9.81 25
2.01019 0 19.58 0 0.605 7.929 96.2 2.0459 5 403 14.7 3.7 50
1.80028 0 19.58 0 0.605 5.877 79.2 2.4259 5 403 14.7 12.14 23.8
2.3004 0 19.58 0 0.605 6.319 96.1 2.1 5 403 14.7 11.1 23.8
2.44953 0 19.58 0 0.605 6.402 95.2 2.2625 5 403 14.7 11.32 22.3
1.20742 0 19.58 0 0.605 5.875 94.6 2.4259 5 403 14.7 14.43 17.4
2.3139 0 19.58 0 0.605 5.88 97.3 2.3887 5 403 14.7 12.03 19.1
0.13914 0 4.05 0 0.51 5.572 88.5 2.5961 5 296 16.6 14.69 23.1
0.09178 0 4.05 0 0.51 6.416 84.1 2.6463 5 296 16.6 9.04 23.6
0.08447 0 4.05 0 0.51 5.859 68.7 2.7019 5 296 16.6 9.64 22.6
0.06664 0 4.05 0 0.51 6.546 33.1 3.1323 5 296 16.6 5.33 29.4
0.07022 0 4.05 0 0.51 6.02 47.2 3.5549 5 296 16.6 10.11 23.2
0.05425 0 4.05 0 0.51 6.315 73.4 3.3175 5 296 16.6 6.29 24.6
0.06642 0 4.05 0 0.51 6.86 74.4 2.9153 5 296 16.6 6.92 29.9
0.0578 0 2.46 0 0.488 6.98 58.4 2.829 3 193 17.8 5.04 37.2
0.06588 0 2.46 0 0.488 7.765 83.3 2.741 3 193 17.8 7.56 39.8
0.06888 0 2.46 0 0.488 6.144 62.2 2.5979 3 193 17.8 9.45 36.2
0.09103 0 2.46 0 0.488 7.155 92.2 2.7006 3 193 17.8 4.82 37.9
0.10008 0 2.46 0 0.488 6.563 95.6 2.847 3 193 17.8 5.68 32.5
0.08308 0 2.46 0 0.488 5.604 89.8 2.9879 3 193 17.8 13.98 26.4
0.06047 0 2.46 0 0.488 6.153 68.8 3.2797 3 193 17.8 13.15 29.6
0.05602 0 2.46 0 0.488 7.831 53.6 3.1992 3 193 17.8 4.45 50
0.07875 45 3.44 0 0.437 6.782 41.1 3.7886 5 398 15.2 6.68 32
0.12579 45 3.44 0 0.437 6.556 29.1 4.5667 5 398 15.2 4.56 29.8
0.0837 45 3.44 0 0.437 7.185 38.9 4.5667 5 398 15.2 5.39 34.9
0.09068 45 3.44 0 0.437 6.951 21.5 6.4798 5 398 15.2 5.1 37
0.06911 45 3.44 0 0.437 6.739 30.8 6.4798 5 398 15.2 4.69 30.5
0.08664 45 3.44 0 0.437 7.178 26.3 6.4798 5 398 15.2 2.87 36.4
0.02187 60 2.93 0 0.401 6.8 9.9 6.2196 1 265 15.6 5.03 31.1
0.01439 60 2.93 0 0.401 6.604 18.8 6.2196 1 265 15.6 4.38 29.1
0.01381 80 0.46 0 0.422 7.875 32 5.6484 4 255 14.4 2.97 50
0.04011 80 1.52 0 0.404 7.287 34.1 7.309 2 329 12.6 4.08 33.3
0.04666 80 1.52 0 0.404 7.107 36.6 7.309 2 329 12.6 8.61 30.3
0.03768 80 1.52 0 0.404 7.274 38.3 7.309 2 329 12.6 6.62 34.6
0.0315 95 1.47 0 0.403 6.975 15.3 7.6534 3 402 17 4.56 34.9
0.01778 95 1.47 0 0.403 7.135 13.9 7.6534 3 402 17 4.45 32.9
0.03445 82.5 2.03 0 0.415 6.162 38.4 6.27 2 348 14.7 7.43 24.1
0.02177 82.5 2.03 0 0.415 7.61 15.7 6.27 2 348 14.7 3.11 42.3
0.0351 95 2.68 0 0.4161 7.853 33.2 5.118 4 224 14.7 3.81 48.5
0.02009 95 2.68 0 0.4161 8.034 31.9 5.118 4 224 14.7 2.88 50
0.13642 0 10.59 0 0.489 5.891 22.3 3.9454 4 277 18.6 10.87 22.6
0.22969 0 10.59 0 0.489 6.326 52.5 4.3549 4 277 18.6 10.97 24.4
0.25199 0 10.59 0 0.489 5.783 72.7 4.3549 4 277 18.6 18.06 22.5
0.13587 0 10.59 1 0.489 6.064 59.1 4.2392 4 277 18.6 14.66 24.4
0.43571 0 10.59 1 0.489 5.344 100 3.875 4 277 18.6 23.09 20
0.17446 0 10.59 1 0.489 5.96 92.1 3.8771 4 277 18.6 17.27 21.7
0.37578 0 10.59 1 0.489 5.404 88.6 3.665 4 277 18.6 23.98 19.3
0.21719 0 10.59 1 0.489 5.807 53.8 3.6526 4 277 18.6 16.03 22.4
0.14052 0 10.59 0 0.489 6.375 32.3 3.9454 4 277 18.6 9.38 28.1
0.28955 0 10.59 0 0.489 5.412 9.8 3.5875 4 277 18.6 29.55 23.7
0.19802 0 10.59 0 0.489 6.182 42.4 3.9454 4 277 18.6 9.47 25
0.0456 0 13.89 1 0.55 5.888 56 3.1121 5 276 16.4 13.51 23.3
0.07013 0 13.89 0 0.55 6.642 85.1 3.4211 5 276 16.4 9.69 28.7
0.11069 0 13.89 1 0.55 5.951 93.8 2.8893 5 276 16.4 17.92 21.5
0.11425 0 13.89 1 0.55 6.373 92.4 3.3633 5 276 16.4 10.5 23
0.35809 0 6.2 1 0.507 6.951 88.5 2.8617 8 307 17.4 9.71 26.7
0.40771 0 6.2 1 0.507 6.164 91.3 3.048 8 307 17.4 21.46 21.7
0.62356 0 6.2 1 0.507 6.879 77.7 3.2721 8 307 17.4 9.93 27.5
0.6147 0 6.2 0 0.507 6.618 80.8 3.2721 8 307 17.4 7.6 30.1
0.31533 0 6.2 0 0.504 8.266 78.3 2.8944 8 307 17.4 4.14 44.8
0.52693 0 6.2 0 0.504 8.725 83 2.8944 8 307 17.4 4.63 50
0.38214 0 6.2 0 0.504 8.04 86.5 3.2157 8 307 17.4 3.13 37.6
0.41238 0 6.2 0 0.504 7.163 79.9 3.2157 8 307 17.4 6.36 31.6
0.29819 0 6.2 0 0.504 7.686 17 3.3751 8 307 17.4 3.92 46.7
0.44178 0 6.2 0 0.504 6.552 21.4 3.3751 8 307 17.4 3.76 31.5
0.537 0 6.2 0 0.504 5.981 68.1 3.6715 8 307 17.4 11.65 24.3
0.46296 0 6.2 0 0.504 7.412 76.9 3.6715 8 307 17.4 5.25 31.7
0.57529 0 6.2 0 0.507 8.337 73.3 3.8384 8 307 17.4 2.47 41.7
0.33147 0 6.2 0 0.507 8.247 70.4 3.6519 8 307 17.4 3.95 48.3
0.44791 0 6.2 1 0.507 6.726 66.5 3.6519 8 307 17.4 8.05 29
0.33045 0 6.2 0 0.507 6.086 61.5 3.6519 8 307 17.4 10.88 24
0.52058 0 6.2 1 0.507 6.631 76.5 4.148 8 307 17.4 9.54 25.1
0.51183 0 6.2 0 0.507 7.358 71.6 4.148 8 307 17.4 4.73 31.5
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0.09252 30 4.93 0 0.428 6.606 42.2 6.1899 6 300 16.6 7.37 23.3
0.11329 30 4.93 0 0.428 6.897 54.3 6.3361 6 300 16.6 11.38 22
0.10612 30 4.93 0 0.428 6.095 65.1 6.3361 6 300 16.6 12.4 20.1
0.1029 30 4.93 0 0.428 6.358 52.9 7.0355 6 300 16.6 11.22 22.2
0.12757 30 4.93 0 0.428 6.393 7.8 7.0355 6 300 16.6 5.19 23.7
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0.19133 22 5.86 0 0.431 5.605 70.2 7.9549 7 330 19.1 18.46 18.5
0.33983 22 5.86 0 0.431 6.108 34.9 8.0555 7 330 19.1 9.16 24.3
0.19657 22 5.86 0 0.431 6.226 79.2 8.0555 7 330 19.1 10.15 20.5
0.16439 22 5.86 0 0.431 6.433 49.1 7.8265 7 330 19.1 9.52 24.5
0.19073 22 5.86 0 0.431 6.718 17.5 7.8265 7 330 19.1 6.56 26.2
0.1403 22 5.86 0 0.431 6.487 13 7.3967 7 330 19.1 5.9 24.4
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0.08221 22 5.86 0 0.431 6.957 6.8 8.9067 7 330 19.1 3.53 29.6
0.36894 22 5.86 0 0.431 8.259 8.4 8.9067 7 330 19.1 3.54 42.8
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0.03548 80 3.64 0 0.392 5.876 19.1 9.2203 1 315 16.4 9.25 20.9
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0.65665 20 3.97 0 0.647 6.842 100 2.0107 5 264 13 6.9 30.1
0.54011 20 3.97 0 0.647 7.203 81.8 2.1121 5 264 13 9.59 33.8
0.53412 20 3.97 0 0.647 7.52 89.4 2.1398 5 264 13 7.26 43.1
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0.82526 20 3.97 0 0.647 7.327 94.5 2.0788 5 264 13 11.25 31
0.55007 20 3.97 0 0.647 7.206 91.6 1.9301 5 264 13 8.1 36.5
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0.5405 20 3.97 0 0.575 7.47 52.6 2.872 5 264 13 3.16 43.5
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0.29916 20 6.96 0 0.464 5.856 42.1 4.429 3 223 18.6 13 21.1
0.16211 20 6.96 0 0.464 6.24 16.3 4.429 3 223 18.6 6.59 25.2
0.1146 20 6.96 0 0.464 6.538 58.7 3.9175 3 223 18.6 7.73 24.4
0.22188 20 6.96 1 0.464 7.691 51.8 4.3665 3 223 18.6 6.58 35.2
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0.09604 40 6.41 0 0.447 6.854 42.8 4.2673 4 254 17.6 2.98 32
0.10469 40 6.41 1 0.447 7.267 49 4.7872 4 254 17.6 6.05 33.2
0.06127 40 6.41 1 0.447 6.826 27.6 4.8628 4 254 17.6 4.16 33.1
0.07978 40 6.41 0 0.447 6.482 32.1 4.1403 4 254 17.6 7.19 29.1
0.21038 20 3.33 0 0.4429 6.812 32.2 4.1007 5 216 14.9 4.85 35.1
0.03578 20 3.33 0 0.4429 7.82 64.5 4.6947 5 216 14.9 3.76 45.4
0.03705 20 3.33 0 0.4429 6.968 37.2 5.2447 5 216 14.9 4.59 35.4
0.06129 20 3.33 1 0.4429 7.645 49.7 5.2119 5 216 14.9 3.01 46
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0.00906 90 2.97 0 0.4 7.088 20.8 7.3073 1 285 15.3 7.85 32.2
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0.01965 80 1.76 0 0.385 6.23 31.5 9.0892 1 241 18.2 12.93 20.1
0.03871 52.5 5.32 0 0.405 6.209 31.3 7.3172 6 293 16.6 7.14 23.2
0.0459 52.5 5.32 0 0.405 6.315 45.6 7.3172 6 293 16.6 7.6 22.3
0.04297 52.5 5.32 0 0.405 6.565 22.9 7.3172 6 293 16.6 9.51 24.8
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0.07886 80 4.95 0 0.411 7.148 27.7 5.1167 4 245 19.2 3.56 37.3
0.03615 80 4.95 0 0.411 6.63 23.4 5.1167 4 245 19.2 4.7 27.9
0.08265 0 13.92 0 0.437 6.127 18.4 5.5027 4 289 16 8.58 23.9
0.08199 0 13.92 0 0.437 6.009 42.3 5.5027 4 289 16 10.4 21.7
0.12932 0 13.92 0 0.437 6.678 31.1 5.9604 4 289 16 6.27 28.6
0.05372 0 13.92 0 0.437 6.549 51 5.9604 4 289 16 7.39 27.1
0.14103 0 13.92 0 0.437 5.79 58 6.32 4 289 16 15.84 20.3
0.06466 70 2.24 0 0.4 6.345 20.1 7.8278 5 358 14.8 4.97 22.5
0.05561 70 2.24 0 0.4 7.041 10 7.8278 5 358 14.8 4.74 29
0.04417 70 2.24 0 0.4 6.871 47.4 7.8278 5 358 14.8 6.07 24.8
0.03537 34 6.09 0 0.433 6.59 40.4 5.4917 7 329 16.1 9.5 22
0.09266 34 6.09 0 0.433 6.495 18.4 5.4917 7 329 16.1 8.67 26.4
0.1 34 6.09 0 0.433 6.982 17.7 5.4917 7 329 16.1 4.86 33.1
0.05515 33 2.18 0 0.472 7.236 41.1 4.022 7 222 18.4 6.93 36.1
0.05479 33 2.18 0 0.472 6.616 58.1 3.37 7 222 18.4 8.93 28.4
0.07503 33 2.18 0 0.472 7.42 71.9 3.0992 7 222 18.4 6.47 33.4
0.04932 33 2.18 0 0.472 6.849 70.3 3.1827 7 222 18.4 7.53 28.2
0.49298 0 9.9 0 0.544 6.635 82.5 3.3175 4 304 18.4 4.54 22.8
0.3494 0 9.9 0 0.544 5.972 76.7 3.1025 4 304 18.4 9.97 20.3
2.63548 0 9.9 0 0.544 4.973 37.8 2.5194 4 304 18.4 12.64 16.1
0.79041 0 9.9 0 0.544 6.122 52.8 2.6403 4 304 18.4 5.98 22.1
0.26169 0 9.9 0 0.544 6.023 90.4 2.834 4 304 18.4 11.72 19.4
0.26938 0 9.9 0 0.544 6.266 82.8 3.2628 4 304 18.4 7.9 21.6
0.3692 0 9.9 0 0.544 6.567 87.3 3.6023 4 304 18.4 9.28 23.8
0.25356 0 9.9 0 0.544 5.705 77.7 3.945 4 304 18.4 11.5 16.2
0.31827 0 9.9 0 0.544 5.914 83.2 3.9986 4 304 18.4 18.33 17.8
0.24522 0 9.9 0 0.544 5.782 71.7 4.0317 4 304 18.4 15.94 19.8
0.40202 0 9.9 0 0.544 6.382 67.2 3.5325 4 304 18.4 10.36 23.1
0.47547 0 9.9 0 0.544 6.113 58.8 4.0019 4 304 18.4 12.73 21
0.1676 0 7.38 0 0.493 6.426 52.3 4.5404 5 287 19.6 7.2 23.8
0.18159 0 7.38 0 0.493 6.376 54.3 4.5404 5 287 19.6 6.87 23.1
0.35114 0 7.38 0 0.493 6.041 49.9 4.7211 5 287 19.6 7.7 20.4
0.28392 0 7.38 0 0.493 5.708 74.3 4.7211 5 287 19.6 11.74 18.5
0.34109 0 7.38 0 0.493 6.415 40.1 4.7211 5 287 19.6 6.12 25
0.19186 0 7.38 0 0.493 6.431 14.7 5.4159 5 287 19.6 5.08 24.6
0.30347 0 7.38 0 0.493 6.312 28.9 5.4159 5 287 19.6 6.15 23
0.24103 0 7.38 0 0.493 6.083 43.7 5.4159 5 287 19.6 12.79 22.2
0.06617 0 3.24 0 0.46 5.868 25.8 5.2146 4 430 16.9 9.97 19.3
0.06724 0 3.24 0 0.46 6.333 17.2 5.2146 4 430 16.9 7.34 22.6
0.04544 0 3.24 0 0.46 6.144 32.2 5.8736 4 430 16.9 9.09 19.8
0.05023 35 6.06 0 0.4379 5.706 28.4 6.6407 1 304 16.9 12.43 17.1
0.03466 35 6.06 0 0.4379 6.031 23.3 6.6407 1 304 16.9 7.83 19.4
0.05083 0 5.19 0 0.515 6.316 38.1 6.4584 5 224 20.2 5.68 22.2
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0.03961 0 5.19 0 0.515 6.037 34.5 5.9853 5 224 20.2 8.01 21.1
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0.03041 0 5.19 0 0.515 5.895 59.6 5.615 5 224 20.2 10.56 18.5
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0.06151 0 5.19 0 0.515 5.968 58.5 4.8122 5 224 20.2 9.29 18.7
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0.0795 60 1.69 0 0.411 6.579 35.9 10.7103 4 411 18.3 5.49 24.1
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0.10659 80 1.91 0 0.413 5.936 19.5 10.5857 4 334 22 5.57 20.6
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15.288 0 18.1 0 0.671 6.649 93.3 1.3449 24 666 20.2 23.24 13.9
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14.3337 0 18.1 0 0.7 4.88 100 1.5895 24 666 20.2 30.62 10.2
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11.5779 0 18.1 0 0.7 5.036 97 1.77 24 666 20.2 25.68 9.7
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38.3518 0 18.1 0 0.693 5.453 100 1.4896 24 666 20.2 30.59 5
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41.5292 0 18.1 0 0.693 5.531 85.4 1.6074 24 666 20.2 27.38 8.5
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14.0507 0 18.1 0 0.597 6.657 100 1.5275 24 666 20.2 21.22 17.2
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28.6558 0 18.1 0 0.597 5.155 100 1.5894 24 666 20.2 20.08 16.3
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73.5341 0 18.1 0 0.679 5.957 100 1.8026 24 666 20.2 20.62 8.8
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37.6619 0 18.1 0 0.679 6.202 78.7 1.8629 24 666 20.2 14.52 10.9
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4.03841 0 18.1 0 0.532 6.229 90.7 3.0993 24 666 20.2 12.87 19.6
3.56868 0 18.1 0 0.58 6.437 75 2.8965 24 666 20.2 14.36 23.2
4.64689 0 18.1 0 0.614 6.98 67.6 2.5329 24 666 20.2 11.66 29.8
8.05579 0 18.1 0 0.584 5.427 95.4 2.4298 24 666 20.2 18.14 13.8
6.39312 0 18.1 0 0.584 6.162 97.4 2.206 24 666 20.2 24.1 13.3
4.87141 0 18.1 0 0.614 6.484 93.6 2.3053 24 666 20.2 18.68 16.7
15.0234 0 18.1 0 0.614 5.304 97.3 2.1007 24 666 20.2 24.91 12
10.233 0 18.1 0 0.614 6.185 96.7 2.1705 24 666 20.2 18.03 14.6
14.3337 0 18.1 0 0.614 6.229 88 1.9512 24 666 20.2 13.11 21.4
5.82401 0 18.1 0 0.532 6.242 64.7 3.4242 24 666 20.2 10.74 23
5.70818 0 18.1 0 0.532 6.75 74.9 3.3317 24 666 20.2 7.74 23.7
5.73116 0 18.1 0 0.532 7.061 77 3.4106 24 666 20.2 7.01 25
2.81838 0 18.1 0 0.532 5.762 40.3 4.0983 24 666 20.2 10.42 21.8
2.37857 0 18.1 0 0.583 5.871 41.9 3.724 24 666 20.2 13.34 20.6
3.67367 0 18.1 0 0.583 6.312 51.9 3.9917 24 666 20.2 10.58 21.2
5.69175 0 18.1 0 0.583 6.114 79.8 3.5459 24 666 20.2 14.98 19.1
4.83567 0 18.1 0 0.583 5.905 53.2 3.1523 24 666 20.2 11.45 20.6
0.15086 0 27.74 0 0.609 5.454 92.7 1.8209 4 711 20.1 18.06 15.2
0.18337 0 27.74 0 0.609 5.414 98.3 1.7554 4 711 20.1 23.97 7
0.20746 0 27.74 0 0.609 5.093 98 1.8226 4 711 20.1 29.68 8.1
0.10574 0 27.74 0 0.609 5.983 98.8 1.8681 4 711 20.1 18.07 13.6
0.11132 0 27.74 0 0.609 5.983 83.5 2.1099 4 711 20.1 13.35 20.1
0.17331 0 9.69 0 0.585 5.707 54 2.3817 6 391 19.2 12.01 21.8
0.27957 0 9.69 0 0.585 5.926 42.6 2.3817 6 391 19.2 13.59 24.5
0.17899 0 9.69 0 0.585 5.67 28.8 2.7986 6 391 19.2 17.6 23.1
0.2896 0 9.69 0 0.585 5.39 72.9 2.7986 6 391 19.2 21.14 19.7
0.26838 0 9.69 0 0.585 5.794 70.6 2.8927 6 391 19.2 14.1 18.3
0.23912 0 9.69 0 0.585 6.019 65.3 2.4091 6 391 19.2 12.92 21.2
0.17783 0 9.69 0 0.585 5.569 73.5 2.3999 6 391 19.2 15.1 17.5
0.22438 0 9.69 0 0.585 6.027 79.7 2.4982 6 391 19.2 14.33 16.8
0.06263 0 11.93 0 0.573 6.593 69.1 2.4786 1 273 21 9.67 22.4
0.04527 0 11.93 0 0.573 6.12 76.7 2.2875 1 273 21 9.08 20.6
0.06076 0 11.93 0 0.573 6.976 91 2.1675 1 273 21 5.64 23.9
0.10959 0 11.93 0 0.573 6.794 89.3 2.3889 1 273 21 6.48 22
0.04741 0 11.93 0 0.573 6.03 80.8 2.505 1 273 21 7.88 11.9

Exercise for Pandas Groupby-Pivot-Graphs-Charts.ipynb

{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Exercise for Python Charts and Graphs\n", "The zip file associated with this exercise includes a notebook and 3 csv files for data\n", "Note: the Pandas group by content is optional" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "%matplotlib inline\n", "import numpy as np\n", "import pandas as pd\n", "import matplotlib.pyplot as plt\n", "import seaborn as sns" ] }, { "cell_type": "code", "execution_count": 97, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "'module://ipykernel.pylab.backend_inline'" ] }, "execution_count": 97, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Example to check the backend layer of matplotlib\n", "import matplotlib as mpl\n", "mpl.get_backend()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Exercise for Python Charts and Graphs (Required)" ] }, { "cell_type": "code", "execution_count": 51, "metadata": {}, "outputs": [ { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th>Month</th>\n", " <th>Apple</th>\n", " <th>Banana</th>\n", " <th>Pear</th>\n", " <th>Cherry</th>\n", " <th>Watermelon</th>\n", " <th>Kiwi</th>\n", " <th>Peach</th>\n", " <th>Total Profit</th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>0</th>\n", " <td>1</td>\n", " <td>2500</td>\n", " <td>1500</td>\n", " <td>5200</td>\n", " <td>9200</td>\n", " <td>1200</td>\n", " <td>1490</td>\n", " <td>21100</td>\n", " <td>42190</td>\n", " </tr>\n", " <tr>\n", " <th>1</th>\n", " <td>2</td>\n", " <td>2630</td>\n", " <td>1200</td>\n", " <td>5100</td>\n", " <td>6100</td>\n", " <td>2100</td>\n", " <td>1845</td>\n", " <td>18330</td>\n", " <td>37305</td>\n", " </tr>\n", " <tr>\n", " <th>2</th>\n", " <td>3</td>\n", " <td>2140</td>\n", " <td>1340</td>\n", " <td>4550</td>\n", " <td>9550</td>\n", " <td>3550</td>\n", " <td>1135</td>\n", " <td>22470</td>\n", " <td>44735</td>\n", " </tr>\n", " <tr>\n", " <th>3</th>\n", " <td>4</td>\n", " <td>3400</td>\n", " <td>1130</td>\n", " <td>5870</td>\n", " <td>8870</td>\n", " <td>1870</td>\n", " <td>2007</td>\n", " <td>22270</td>\n", " <td>45417</td>\n", " </tr>\n", " <tr>\n", " <th>4</th>\n", " <td>5</td>\n", " <td>3600</td>\n", " <td>1740</td>\n", " <td>4560</td>\n", " <td>7760</td>\n", " <td>1560</td>\n", " <td>1876</td>\n", " <td>20960</td>\n", " <td>42056</td>\n", " </tr>\n", " <tr>\n", " <th>5</th>\n", " <td>6</td>\n", " <td>2760</td>\n", " <td>1555</td>\n", " <td>4890</td>\n", " <td>7490</td>\n", " <td>1890</td>\n", " <td>1540</td>\n", " <td>20140</td>\n", " <td>40265</td>\n", " </tr>\n", " <tr>\n", " <th>6</th>\n", " <td>7</td>\n", " <td>2980</td>\n", " <td>1120</td>\n", " <td>4780</td>\n", " <td>8980</td>\n", " <td>1780</td>\n", " <td>1120</td>\n", " <td>29550</td>\n", " <td>50310</td>\n", " </tr>\n", " <tr>\n", " <th>7</th>\n", " <td>8</td>\n", " <td>3700</td>\n", " <td>1400</td>\n", " <td>5860</td>\n", " <td>9960</td>\n", " <td>2860</td>\n", " <td>2001</td>\n", " <td>36140</td>\n", " <td>61921</td>\n", " </tr>\n", " <tr>\n", " <th>8</th>\n", " <td>9</td>\n", " <td>3540</td>\n", " <td>1780</td>\n", " <td>6100</td>\n", " <td>8100</td>\n", " <td>2100</td>\n", " <td>1658</td>\n", " <td>23400</td>\n", " <td>46678</td>\n", " </tr>\n", " <tr>\n", " <th>9</th>\n", " <td>10</td>\n", " <td>1990</td>\n", " <td>1890</td>\n", " <td>8300</td>\n", " <td>10300</td>\n", " <td>2300</td>\n", " <td>1900</td>\n", " <td>26670</td>\n", " <td>53350</td>\n", " </tr>\n", " <tr>\n", " <th>10</th>\n", " <td>11</td>\n", " <td>2340</td>\n", " <td>2100</td>\n", " <td>7300</td>\n", " <td>13300</td>\n", " <td>2400</td>\n", " <td>1756</td>\n", " <td>41280</td>\n", " <td>70476</td>\n", " </tr>\n", " <tr>\n", " <th>11</th>\n", " <td>12</td>\n", " <td>2900</td>\n", " <td>1760</td>\n", " <td>7400</td>\n", " <td>14400</td>\n", " <td>1800</td>\n", " <td>1977</td>\n", " <td>30020</td>\n", " <td>60257</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "</div>" ], "text/plain": [ " Month Apple Banana Pear Cherry Watermelon Kiwi Peach Total Profit\n", "0 1 2500 1500 5200 9200 1200 1490 21100 42190\n", "1 2 2630 1200 5100 6100 2100 1845 18330 37305\n", "2 3 2140 1340 4550 9550 3550 1135 22470 44735\n", "3 4 3400 1130 5870 8870 1870 2007 22270 45417\n", "4 5 3600 1740 4560 7760 1560 1876 20960 42056\n", "5 6 2760 1555 4890 7490 1890 1540 20140 40265\n", "6 7 2980 1120 4780 8980 1780 1120 29550 50310\n", "7 8 3700 1400 5860 9960 2860 2001 36140 61921\n", "8 9 3540 1780 6100 8100 2100 1658 23400 46678\n", "9 10 1990 1890 8300 10300 2300 1900 26670 53350\n", "10 11 2340 2100 7300 13300 2400 1756 41280 70476\n", "11 12 2900 1760 7400 14400 1800 1977 30020 60257" ] }, "execution_count": 51, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Load FruitSales.csv data into fruit_sales_df. Display the data\n", "\n" ] }, { "cell_type": "code", "execution_count": 52, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 432x288 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# Plot a line chart of monthly total profit\n", "# Add a meaningful chart title, xlabel and ylabel\n", "\n" ] }, { "cell_type": "code", "execution_count": 64, "metadata": {}, "outputs": [ { "data": { "image/png": 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ZpH3b1GnDzzf9zNkNziZEgvf7viURY4zxk+ylTgozKis35zY615fh+EXwpjdjjCnlSppEsm0/uJ0fNv/gi5B8zq5EjDHGD7Ye2MrafWuJKhdFl+guxW5n9d7VtH+3PTUq1GDzPZuL3C3mb3YlYowxfpB9FXJB0wsIDw0vdjuta7Wmde3W7D6ym/HLx/soOt+xJGKMMX4wa+MsIO9VewtLRBjV1TNS68VfXiQjK6PEsfmSJRFjjPGDcf3H8cVVX3Bpi0tL3NYVra4gpnoMmw9s5tM/P/VBdL5jScQYY/ygSmQVBp42kDqV6pS4reMfoXv8kxHd5NckIiJVRWSqiKwTkbUi0kVEHheRHSKy3Hld6FX/QRGJE5G/RKSPV3lfpyxOREZ5lTcRkd9EZIOITBGRCH+ejzHGuOXGNjdSr3I9Vu1dxbcbvnU7nBz+vhJ5DZipqi2BtsBap/xVVW3nvL4DEJFWwDVAa6AvMEZEQkUkFHgL6Ae0Aq516gK84LTVHEgCbvXz+RhjTIEumHgBN3xxA3uO7PFZm+XCyjH87OEMaDmAhlUa+qzdkvJbEhGRKKAb8AGAqqap6oF8dukPTFbVVFXdDMQBHZ1XnKpuUtU0YDLQXzwPKe4JTHX2nwAM8M/ZGGNM4ew8vJO5m+cybd00qkZW9Wnb93S6h2lXT6NNnTY+bbck/Hkl0hRIAMaJyB8iMlZEKjrb7haRlSLyPxGp5pTVB7yXq4x3yvIqrwEcUNWM48pPICJDRGSpiCxNSEjwyckZY0xuZsV5RmX1bNKTcmHlfNq257tzcPFnEgkD2gNvq+qZwFFgFPA20AxoB+wCspeozO23o8UoP7FQ9T1VjVXV2Fq1ahXpJIwxpihmbnRmqZdwaG9+ft76M70n9WbZrmV+O0Zh+TOJxAPxqvqb83kq0F5V96hqpqpmAe/j6a7Krt/Aa/9oYGc+5fuAqiISdly5Mca4IiMrgzkb5wDQr3k/vx3nq3VfMWfTHJ5f8LzfjlFYfksiqrob2C4iLZyi84E1IlLXq9pAYLXzfjpwjYiUE5EmQHNgMbAEaO6MxIrAc/N9unrGuM0DrnD2Hwx85a/zMcaYgizesZikY0k0r96cptWa+u0493W5j/CQcKaumcr6/ev9dpzC8PforGHARyKyEk/31bPAiyKyyinrAdwLoKp/Ap8Ca4CZwF3OFUsGcDcwC8/ork+dugAjgftEJA7PPZIP/Hw+xhiTJ18tuFiQ+lH1Gdx2cFA8QleCadJKIMTGxurSpUvdDsMYUwb9ufdPpq2bxvlNzqdLg+IvulgYG/ZvoOVbLQmVUDbds4noqGi/Ho/c70PbjHVjjPGV1rVb80i3R/yeQACa12jOFa2uID0rnVd+de8RupZEjDGmlHrwnAcB+HDVh6RmpLoSgz1PxBhjfOC5+c8BcFO7m6hbuW4BtX2j3SntGNd/HBc1v8jnc1IKy+6JGGNMCWVpFqe8fAoJyQmsuXMNp9U6ze2Q/MHuiRhjjD8s27WMhOQEGlZpSMuaLV2JIT0znbUJawuu6GPWnWWMMSWUPbS3X0w/V5Ym2X5wO+eOO5f0rHQ2/XtTQLu27ErEGGNKKFDzQ/ISHRVNlcgq7Dy8k4krJgb02JZEjDGmBJJSklgYv5CwkDB6NunpSgz/eITury+SmZUZsGNbEjHGmBL4ftP3ZGkWXRt0JapclGtxXNn6SppWa0pcYhxT10wteAcfsSRijDElUK9yPa45/Rquan2Vq3GEhYTlPEL3uQXPBewRujbE1xhjyojUjFSavNaEXUd28e1133Jh8wsL3qnwbIivMcaUZeXCynFfl/toWq1pwO6L2JWIMabQNiVtYsaGGdx51p1B+ZS9QJu9cTYp6Sn0bNKTyuUqux0O4LkaCQ0JJSzE5zM47ErEGFM8q/asYtKKSXQe25m7Z9zN0p32RQzg+QXPM2DKAGbEzXA7lBzlwsr5I4HkyZKIMaZAryx8hUFfDiIhOQGAaeumuRyR+w6nHmbBtgWESAi9mvZyO5wT7Dmyh1Hfj2LF7hV+PY4lEWNMvvYl72Py6skIwnsXvwfAF2u/cDkq9/2w+QfSs9LpHN2ZauWruR3OCV745QVe+OUFnlvwnF+PY0nEGJOvcX+MIzUzlb4xfbn5zJupXr46f+3/y5V1moJJziz1Zu7MUi/IvZ3vJTwknM/WfEZcYpzfjmNJxBiTp8ysTN5e+jYAd511F2EhYVxy6iXAyd2lparM3OjuUicFaVClATe2uZEszfLrI3QtiRhj8jRr4yw2H9hMk6pNcv5YDmw5EDi5k8hf+/9iy4Et1KxQkw71OrgdTp5GdB2BIExYMYEdh3b45RiWRIwxeXpryVsA3BF7B6EhoQD0btabmhVqEh0VTVpmmpvhuWZf8j7a1GlDn2Z9CJHg/TPaomYLLm91OWmZaYxeONovx/DrPBERqQqMBU4HFLgF+AuYAjQGtgBXqWqSeAadvwZcCCQDN6nqMqedwcAjTrNPq+oEp7wDMB4oD3wH3KMFnJDNEzGm8N77/T3eX/Y+M66fQc0KNXPK0zPTCQ8NdzGy4FAafg/Ldi2jw3sdqBRRiV3376JSRKXiNpXrPBF/J5EJwHxVHSsiEUAF4CEgUVWfF5FRQDVVHSkiFwLD8CSRTsBrqtpJRKoDS4FYPInod6CDk3gWA/cAi/AkkddVNd8B25ZEjDEnmxcWvMCFzS/kjDpnlKSZwE42FJEooBvwAYCqpqnqAaA/MMGpNgEY4LzvD0xUj0VAVRGpC/QB5qhqoqomAXOAvs62KFVd6Fx9TPRqyxjjZ2mZacyKm0VSSpLboQTUlgNb2Ji40e0wimTkOSNLmkDy5M/OvKZAAjBORP4QkbEiUhGoo6q7AJyftZ369YHtXvvHO2X5lcfnUn4CERkiIktFZGlCQkLJz8yYMu6zPz9j+OzhbE7anGedq6deTd+P+vLlui8DGJn7Xl34KjFvxPDSLy+5HUpQ8GcSCQPaA2+r6pnAUWBUPvVzu1TSYpSfWKj6nqrGqmpsrVq18o/aGMNLv77EywtfZt6WeXnW6dOsD3DyjdLKXuLk7AZnuxxJcPBnEokH4lX1N+fzVDxJZY/TFYXzc69X/QZe+0cDOwsoj86l3BhTAkt2LGHJziVUi6zGNadfk2e9/i36IwizN87mSNqRAEbono2JG9mQuIGqkVXpFN3J7XCCgt+SiKruBraLSAun6HxgDTAdGOyUDQa+ct5PBwaJR2fgoNPdNQvoLSLVRKQa0BuY5Ww7LCKdnZFdg7zaMsYU05ilYwC45cxbqBBeIc96dSvXpUuDLqRmpubM3i7rZm2cBUCvpr0CushhMPP3AOdhwEcishJoBzwLPA/0EpENQC/nM3hGV20C4oD3gTsBVDUReApY4ryedMoAhuIZQhwHbASCZylNY0qh/cn7mbx6MgBDY4cWWD974uHJspZWdldWsM5Sd4NfU6mqLsczNPd45+dSV4G78mjnf8D/cilfimcOijHGB8YtH8exjGP0jelLs+rNCqw/sOVAhs8ZzrcbviUtM42I0IgAROmO1IxUftj8A/D3/SBjM9aNMY4szfrHOlmF0ax6M86ofQa1K9Zmy4EtfozOfWv3rUVVaVOnDfWjch0IelKyJxsaYwDPooKL4hfxyepPeLXPqznLnBQkMSWRapHVToonHR7LOEb8oXhiqse4HYobijdjXUQ6O5P/8i0rLSyJGGNMsRR7xvqYXMreKlksxphgkqVZJW5j+8HtxB+KL7hiKZSSnnLSLjZZkDyTiIh0FJF7gFoi8m+v1yNAcK84ZowpkofmPkTvSb2L/ez00QtH0/C/DXl14as+jiw4fLTqI2q8WINn5z/rdihBJ78rkYpATTwjuGp5vdKAK/0fmjEmEI5lHGPssrHM2TSHzKzMYrXRqb5n4t0X676gLN5nnRk3kyNpR6hevrrboQSdPIf4quo8YJ6IjFPVTQGMyRgTQFNWT2F/yn461O1Ax/odi9VGlwZdqFOxDlsObGHFnhW0O6Wdj6N0T3pmOnM2zQFsaG9u8uvOesV5+4qIfHH8K0DxGWP8LPvBU3eedWexR1iFSAj9W/QHYNrasrWW1qL4RRxKPUSLGi1oUq2J2+EEnfy6syY7P9/EcyP9+JcxppQr7DpZhTHwtLL52NzsJV36xfRzOZLglN+M9WfwrFN1vqo+FKB4jDEBVNh1sgqjZ5OeRJWLYtXeVcQlxpWZuRS21En+8rsSiRaRrsBAETlDRNp4vwIVoDHGP45lHMt5FsgdsXeUuL2I0AguPvViIkIjWL57eYnbCwZ7juzhj91/EBkWSbdG3dwOJyjlOdlQRK4GbgM6A8f/i1BVLZW/UZtsaMzf9iXvY+6muVx9+tU+aS/+UDxR5aKIKhflk/bcpqqs37+eNQlrcrrrTmLFnrH+hKo+5peQXGBJxBhjiiXXJFLgKr6q+piIXIjneekAP6rqyfHwAGPKqN1HdlOjfA3CQ/0zbzgjK4OEownUrVzXL+2b4FHgsici8jQwAs+zPjYBI5wyY0wpddv022j8WmN+2faLz9uev3U+dV6uw01f3eTztgNpyY4ltH+3Pa8tes3tUIJaYZ4ncilwpqpmAojI/4BlwCP+DMwY4x+bkzbz3YbvCA8N59Qap/q8/dNqncaBYwf4YfMPHDh2gKqRVX1+jED4bsN3/LH7D7pEd3E7lKBW2OeJeN8lq+yPQIwxgfHO0ndQlKtbX02tirV83n7NCjXp1qgbGVkZfLv+W5+3HygzN3p67W1ob/4Kk0ReBJaJyFgR+QBYCrzg37CMMf5wLOMYH/zxAeCZoe4vl7W8DCi9Ew/3J+9n8Y7FhIeE06NJD7fDCWr5JhHxrIEwFzgHzzPQvwO6qepHAYjNGONjn/75KftT9tO+bvucRRP9YUDLAYBnol5KeorfjuMvczbNIUuzOLfRuVSKqOR2OEEt3yTiPPf8G1XdoapfqOrnqrqjsI2LyBYRWSUiy0VkqVP2uIjscMqWOyO/sus/KCJxIvKXiPTxKu/rlMWJyCiv8iYi8puIbBCRKSJSdh/wbIwP5KyTFVv8dbIKo0GVBsTWiyU5PZnZG2f77Tj+YkudFF5hurMWi0j7Ehyjh6q2U9VYr7JXnbJ2qvodgIi0Aq4BWgN9gTEiEioioXjW6uoHtAKudeqCp1vtVVVtDiQBt5YgTmPKtP3J+3MeZXvtGdf6/XgDW3om5/245Ue/H8uXsjQrJ4nY/ZCCFWZ01jnAEBGJA47imXCiqlqSxJKb/sBkVU0FNjvHy16XOi57OXoRmQz0F5G1QE/gOqfOBOBx4G0fx2VMmVCjQg3+uvsv4hLjSrxOVmHc3O5m+sX0K3XLwmdpFmMuGsOCbQtoXau12+EEvcIkkQElaF+B2SKiwLuq+p5TfreIDMJzk/5+VU0C6gPez22Pd8oAth9X3gmoARxQ1Yxc6v+DiAwBhgA0bNiwBKdjTOkWIiF+Gdabm7qV65bKyYZhIWFcdtplXHbaZW6HUirk9zyRciJyNzAM6A5sUdWN2a9Ctt/VuWLpB9wlIt3wXCk0A9oBu4Ds55bk1kGrxSg/sVD1PVWNVdXYWrV8P6TRmGD3y7ZfXH3+eXJ6smvHNv6V3z2R8Xi6sjbguRp5uaiNq+pO5+deYBrQUVX3qGqmqmYB7/N3l1U80MBr92hgZz7l+4CqIhJ2XLkxxkuWZjHoy0E0/m9jFu9YHNBj70vex9kfnE3LN1uSpVkBPXZxHDx2kBun3ciU1VPcDqXUyC+JnK6q16jqW8BlwHlFaVhEKopI5ez3eJ5NslpEvK9vBwKrnffTgWucK6AmQHNgMbAEaO6MxIrAc/N9ujNybB5whbP/YOCrosRozMlgVtwsNiVtIjoqmg51OwT02DXK1yD+UDzbD21nyY4lAT12cczdPJcPV36YM4rNFCy/JJKe/UZV0/Opl5c6wAIRWYEnGXzrLNz4ojPsdyXQA7jXOcafwKfAGmAmcJdzxZIB3A3MAtYCnzp1AUYC9zk34WsAHxQjTmPKtOwHT90RewehIaEBPbaI5MwZKQ0TD2dssAdQFVV+zxPJBA5mf8Sz3Mkh/h6dVT0gEfqYLQVvTiabkzbT7PVmhN/UiZMAACAASURBVIeGE39vvF+WOSnIvM3z6DmxJ6fWOJV1d63z6/yUklBVGv63IfGH4vl9yO+0r+vrAailXpGXgreJe8aUcu/+/i6KclXrq1xJIADnNjqXGuVrsH7/etbuW0urWq0K3skFaxLWEH8onjoV65S6YcluyrM7y+lKyvMVyCCNMUV3LOMYY5eNBeCus+5yLY6wkDAubXEpAF+s/cK1OAqSPcGwT0wfQqSwa9Ma+00ZU0YlpSRxXuPz6Fi/o1/XySqM7NnrX6//2tU48jMjzrkf0szuhxRFYSYbGmNKobqV6/L5VZ+Tnpnu+n2IXs16MWngJC5qfpGrceSnV9NepGSk0LtZb7dDKVUKfMZ6WWM31o0xplhy/SaS34z1JBFJzOWVJCKJ/ovTGFNSby1+i1lxs4Jygl+wfXHdcmCL2yGUavndE6kJ1MrllV1ujAlCiSmJPDDnAfp+1JdNSZvcDieHqnL3d3dTf3R9Eo4muB0OAHM3zSXm9Rgem/eY26GUWoUenQVUwTOBMPtljAlC4/4Yx7GMY/Ru1puY6jFuh5NDRIhLjGPXkV1BcYM94WgCN067kUzNtNFYJVDgb05ELhKR9XjWsPrN+fmDvwMzxhRdlmbx9lLP0xDcHNabl+xRWm7PXldVbv7qZnYd2cW5Dc/l4W4PuxpPaVaY9PsM0BX4S1UbAH2AH/0ZlDGmeGZvnM3GpI00rNIwKEdC9W/ZH0GYvXE2h1MPuxbHm4vf5NsN31I1siofXvYhYSE2ULW4CpNEMlQ1AQgREVHVOYCtB2BMEBqzxFknq0Pg18kqjFMqncLZDc4mLTMtZ15GoK3YvYIH5jwAwNhLxtKwij1jqCQKk0QOOqvwLgAmisgrQPAN+TDmJLflwBa+Wf8NEaER3Nb+NrfDyZPbXVr3zLyHtMw0/tXhX1ze6nJXYihLCpNEBgDHgP/g6cbaAVzsx5iMMcVQOaIyj3d/nGEdh7m2TlZhDDzNk0S+Xf8tqRmpAT/+5CsmMzR2KKP7jA74scuiAicbisizqvpQQWWlhU02NMZ9oxeO5pyG5xBbL9ZGRpUeRZts6CW3hWSC746dMabUuK/LfXSs3zFgCWTbwW088/MzZGRlBOR4J5M8hySIyL+AO4BTRWSZ16bKgH2VNyaIXDP1GtrXbc+dZ91JpYhKbocTVDKyMrj+i+tZsG0BKRkpPN3zabdDKlPy+xrwKXAl8J3zM/vVVVWvDUBsxphCWLZrGVP+nMJzC54rVV1DH678kO7ju7Ng2wK/Hufpn59mwbYF1Ktcj/90/o9fj3Uyym/GepKqxqnqlUB5oJfzCt47dsachN5a7Hke+M3tbqZCeAWXoym8FbtX8NPWn/h8zed+O8b8rfN56uenEIQPB35IzQo1/Xask1VhZqzfheeqpKHz+lRE7vR3YMaYgiWlJPHx6o8BGBo71OVoiiZ7lNa0ddP8sihjUkoS139xPVmaxahzRtGjSQ+fH8MU7sb6v4COqvqQMyKrE557JcYYl41b/vc6Wc1rNHc7nCLpHN2ZUyqdwtaDW1m+e7lP21ZVbv/6drYf2k6n+p14ovsTPm3f/K0wSUSAdK/P6eQx1OuEHUW2iMgqEVkuIkudsuoiMkdENjg/qznlIiKvi0iciKwUkfZe7Qx26m8QkcFe5R2c9uOcfd198o4xAeS9TtadsaWvcyBEQhjQYgDg+4mHyenJHDh2gMoRlfn48o8JDw33afvmb/k9TyR75NYkYJGIPCIijwC/AhOKcIweqtpOVWOdz6OAuaraHJjrfAboBzR3XkOAt504qgOP4bkC6gg8lp14nDpDvPaz51qak8bMuJnEJcbRqEojLj61dM7/ze7S8vWz1ytGVGT2jbNZeOtCmlZr6tO2zT/lt+rYYqC9qr4oIvOAc/FcgdyhqktKcMz+QHfn/QQ8s+BHOuUT1dM5ukhEqopIXafuHFVNBBCROUBfEfkRiFLVhU75RDyz691ZkMeYAOsb05dpV08jS7OCcp2swujeuDtVylXhz4Q/2bB/Q4m75NIy0wiVUEJDQgmREFrXbu2jSE1e8ksiOV1DTtIoTuJQYLaIKPCuqr4H1FHVXU67u0SktlO3PrDda994pyy/8vhcyk88EZEheK5YaNjQFlszZUOIhDCg5QC3wyiRiNAIHjvvMapGVqVOpZI/puj+WfezOmE1kwZOIjoq2gcRmoLkl0Rqich9eW1U1cIsPNNVVXc6iWKOiKzLp25u9zO0GOUnFnqS13vgWfYk/5CNCW6qyq4ju6hXuZ7bofjEvV3u9Uk7X//1NW8ueZPwkHD2HNljSSRA8ruxHgpUwjNDPbdXgVR1p/NzLzANzz2NPU43Fc7PvU71eKCB1+7RwM4CyqNzKTemTPtp6080+m8j7p91v9uhBI0dh3Zw81c3A/Dc+c/RoV4HlyM6eeR3JbJLVZ8sbsPO8vEhqnrYed8beBKYDgwGnnd+fuXsMh24W0Qm47mJftDp7poFPOt1M7038KCqJorIYRHpjOeJi4OAN4obrzGlxTPzPWtAVYms4nYoPvPHrj8Yu2wsXRt25bozrivSvplZmdw47Ub2p+ynd7PePruyMYVTqHsixVQHmOaMug0DPlbVmSKyBM+ExVuBbXiWUgHP8ioXAnFAMnAzgJMsnuLvezJPZt9kB4YC4/HMqJ+B3VQ3Zdxv8b/x/abvqRxRmWEdh7kdjs+s2LOCMUvHsCFxQ5GTyIu/vMi8LfOoXbE2EwZMKFVLv5QF+SWR80vSsKpuAtrmUr4/t7adUVm5PhRaVf8H/C+X8qXA6SWJ05jS5Jn5zwCe56dXK1+tgNqlxyWnXkKohDJvyzySUpIKfW4r96zk/+b9HwATBkzglEqn+DNMk4v81s5KzGubMSbwVu5Zydfrv6Z8WPky12VTo0INzmt8HhlZGXyz/ptC79e6Vmse7/44w88eTt8YmybmBrvuM6aUeHb+swDc3v52alesXUDt0qc4j80NDQnlkW6P8GKvF/0VlimAJRFjSoHMrEwUpVxoOYZ3He52OH6RPedlZtxMktOT8607K24Wuw7vCkRYpgCWRIwpBUJDQplyxRS23butzM5/iI6KpmP9jqRkpDArblae9dbvX8/ln15Om3fasOPQjgBGaHKT3411Y0yQKYvdWN6GtB/COQ3OoWXNlrluT8tM49rPr+Vo+lEuaXFJmZlwWZpZEjEmyL21+C1a1mxJzyY9KesLVd/a/tZ8tz809yGW7VpG46qNeeeid8r876M0sCRiTBDbdXgX98++n9TMVDYM20BM9Ri3Q3LNrLhZvLLwFUIllE8u/6RMTbYszSyJGBPERi8cTWpmKpeddtlJk0D2J+9nyp9TUFXu6uiZOrbnyB4GfTkIgCd7PEnn6M5uhmi82I11Y4LU/uT9OQ+deuich1yOJnC2HNjCXd/dxTPznyFLswCYu3ku+5L30b1xd0Z2HelyhMabXYkYE6Re++01jqYfpW9M35NqQcH2ddvTsEpDth3cxuIdi+kc3ZnrzriO6KhomlVrVmqfnVJW2ZWIMUHoUOoh3ljsWU/0kXMfcTmawBKRvx+bu/bviYfdGnWjflSujwwyLrIkYkwQenvJ2xw4doDzGp1H14Zd3Q4n4LIfm/viry8ye+Nsl6Mx+bHuLGOC0G3tb+No+lF6NO7hdiiuOKfhOTnvb/nqFrb+Z6t1YwUpuxIxJgjVqFCDJ3s8SY8mJ2cSCQsJ4/nzn6d59ebMvnG2JZAgJp4V2E8esbGxunTpUrfDMCZX6ZnpKEpEaITboRhzvFxndtqViDFBZPzy8cS8HsOnf37qdijGFIolEWOCREZWBs//8jzbD23PmR9hTLCzJGJMkJi8ejKbkjbRvHpzrmx1ZcE7GBMELIkYEwSyNIvnFjwHwKhzRtmNZFNq+D2JiEioiPwhIt84n8eLyGYRWe682jnlIiKvi0iciKwUkfZebQwWkQ3Oa7BXeQcRWeXs87rYkp5B5+Cxg6Skp+R8nrRiEt3Hd2fYd8M4eOygi5EFly/XfcmahDU0rNKQG9rc4HY4xhRaIOaJ3AOsBaK8yoar6tTj6vUDmjuvTsDbQCcRqQ48BsQCCvwuItNVNcmpMwRYBHwH9AVm+PFcTC4yszJZtmsZcYlxbEjcQFxiXM4rITmBqVdO5fJWlwOw9+heftr6Ez9t/Ymv13/NhAETOK/xeS6fgbtUlad/fhqAEWePsJFZplTxaxIRkWjgIuAZ4L4CqvcHJqpnzPEiEakqInWB7sAcVU102pwD9BWRH4EoVV3olE8EBmBJxOdUlf0p+9mw/+8EERoSyqPnPQp4bgh3/qBzrjeDI8MiSUxJzPl8eavLiakew9Pzn2bpzqX0mNCDB85+gKd6PEW5sHIBO6dgsvvIbg6nHaZOxTrccuYtbodjTJH4+0rkv8AIoPJx5c+IyKPAXGCUqqYC9YHtXnXinbL8yuNzKTfFoKrsObqHShGVqBRRCYBxf4zjrSVvEZcYx8HUf3Y91a1UNyeJlAsrR59mfagQXoGY6jHEVI+hefXmxFSPoW7luoTI372mjas2pnHVxlzY/EKe/vlpnpn/DC/9+hIz42by5TVf0rRa08CddJCoW7kua+9aS1xiHOXDy7sdjjFF4rckIiIXA3tV9XcR6e616UFgNxABvAeMBJ4k94ksWozy3GIZgqfbi4YNGxbyDE4e/130Xx6d9yiH0w4z5YopXNX6KsCzCODvu34HIKpc1D+SQ0z1GFQ158ly313/XZGOGR4azhM9nqBf837cOO1GDqUeokb5Gr49sVIkLCQsz0fCGhPM/Hkl0hW4VEQuBCKBKBH5UFWz7xqmisg44AHnczzQwGv/aGCnU979uPIfnfLoXOqfQFXfw5OwiI2NPbmm6Bfgt/jfuH/2/WRpFtUiq3Ek7UjOtstbXU7H+h2JqR5DzQo1/fIo0s7RnVn+r+VsPbg150l1Kekp7D26l0ZVG/n8eMHmnaXv0L9Ff+pWrut2KMYUi99GZ6nqg6oaraqNgWuAH1T1Buc+B85IqgHAameX6cAgZ5RWZ+Cgqu4CZgG9RaSaiFQDegOznG2HRaSz09Yg4Ct/nU9ZlJqRyi3TbyFLsxh+9nASRyb+o08+OiqaLg26UKtiLb8+y7piREVa1WqV8/nBuQ9yxttnMH75eMrysjyLdyxm6LdDaftOW1IzUt0Ox5hicWOeyEcisgpYBdQEnnbKvwM2AXHA+8CdAM4N9aeAJc7ryeyb7MBQYKyzz0bspnqRPDv/WdYkrKF59eY80f0Jt8MBPCO94g/FczjtMDd/dTOXf3o5CUcT3A7LL56Z/wwAt5x5y0k7qMCUfrYA40lq1Z5VtH+vPRlZGfx00090a9TN7ZByqCoTV0xk2IxhOaOWPrj0Ay469SK3Q/OZVXtW0eadNkSGRbLlni3UqVTH7ZCMKYgtwGj+1rhqY+7ocAd3n3V3UCUQ8DzZbnC7wawcupJzG57LnqN7uPiTi7njmztIz0x3OzyfeHbBswAMaT/EEogp1eyhVCepyuUq88aFbwT1PYfGVRszb/A8Ri8czSPzHmFf8j7CQkr/P9n1+9czZfUUwkPCGd51uNvhGFMipf//SFMkOw7toGpkVSpGVATw6w1zXwgNCWV41+H0ielDvcr1cuLddXgXNSvUJDw03OUIi+75Bc+jKIPbDiY6KrrgHYwJYpZETiJZmsW1n1/L9kPb+fLqL2l7Slu3Qyq0NnXa5LxPy0zjoo8vIjQklEkDJ5W6+RW3t7+dhOQERp4z0u1QjCkxuydyEnl36bvM3zaf5PTkUv0NeNvBbSSmJLJ051LOfPdM3lz8ZlB3yx2vS4MufH3t18RUj3E7FGNKzJLISWLbwW2M+H4EAG9d+BY1KpTe2eEx1WNYOXQlg9sO5ljGMYbNGEbfj/qy49AOt0PLlz1oypRFlkROAqrKHd/cwZG0I1x22mVc0eoKt0MqsahyUYwfMJ6pV06lRvkazN44mzPePoOpa45fHDp4jPp+FBd+dCGr964uuLIxpYQlkZPAhys/ZEbcDKpGVuXNfm+6HY5PXd7qclYNXUW/mH4kHUsK2omJ+5P3M2bJGGbEzbDZ6aZMsRvrZdzBYwf5z6z/APBqn1fL5BpNdSvX5dvrvuXr9V9zyamX5JTvPbqX2hVruxjZ317/7XWOph+lb0xfOtTr4HY4xviMXYkUQWm6eZutSmQVxl4ylkFtBzG47eCCdyilRIRLW1yaMwR4Y+JGYl6P4b5Z93Es45irsR1KPcTri18H4OFzH3Y1FmN8zZJIIe0+spvOH3Tm1+2/uh1KkQ08bSATBkwI+jkhvvTL9l9ITk/m1UWv0uG9Dny57kvSMtNciWXMkjEcOHaAbo26cU7Dc1yJwRh/sSRSSK8teo3FOxbT98O+LIpf5HY4BUpKSWL57uVuh+GaQW0HsfDWhZxa41TWJKxh4JSB1B9dn3/P+HdAfy/J6cmMXjgasKsQUzZZEimkp3o+xdWtr+Zw2mH6fNiHxTsWux1Svu6ffT+x78Xyvz/+53Yorjmr/ln88a8/eKnXS7Su1Zp9yft4Y/EbAf2dLN6xmEOphzir3ln0atorYMc1JlBsFd8iyMjK4LrPr+OzNZ9RpVwVvh/0PbH1Yn0cYcnN2TiH3h/2plxoOVbcsYIWNVu4HZLrVJVlu5YxccVEbmp3E2fWPROA8cvHM3n1ZAa3HcyAlgP88njaXYd3sS95H2fUOcPnbRsTQLn2h1sSKaL0zHSu/fxaPl/7OVUjqzJ30Fza123vwwhL5kjaEU4fczpbD27l2Z7P8uC5D7odUlDrOaEn87bMAzxzT65qdRWD2w2ma4OuJ9U9JGMKwZaC94Xw0HA+ufwTBrYcyIFjB/hqXXA9TPHhuQ+z9eBWzjzlTB44+4GCdzjJfXblZ7zZ703OqncWh1IPMfaPsZw77lxi3ohh4oqJxW43IyuDqWumkpGV4cNojQk+lkSKITw0nMlXTGbigIk83v1xt8PJ8cu2X3hj8RuESigfXPpBqVzhNtBqVKjBXR3vYvHti1lz5xpGdh1J/cr12ZS06R+TAhOOJnA49XCh252yegpXfnYll3xyScGVjSnFLIkUU0RoBDe2vTGny2P3kd2uLmehqtw3+z4UZWTXkTl9/qbwTqt1Gs9f8Dxb/7OV2TfM5qrWV+Vse/rnp6nzch1u+OIG5mycQ2ZWZp7tZGlWzkOnrmx1pd/jNsZNlkR8YM+RPXQf350eE3q4lkhEhKlXTmVo7FD+77z/cyWGsiI0JJRezXpRJbJKTtmOwztIyUjho1Uf0fvD3jT6byNGfT+KNQlrTtj/y3VfsiZhDQ2iGnBDmxsCGboxAWdJxAeqRFahabWm7EveR88JPflz75+uxNGgSgPGXDSGyLBIV45flk29aiob/72Rx897nKbVmrLj8A5e+OUFWo9pzbPzn82pp6o8M/8ZAEZ0HUFEaIRbIRsTEH5PIiISKiJ/iMg3zucmIvKbiGwQkSkiEuGUl3M+xznbG3u18aBT/peI9PEq7+uUxYnIKH+fS14iwyL54uov6NOsDwnJCfSc2DPXb6j+kJ6ZzqQVk2yZ8QBoWq0pj3V/jLhhccy/eT63nXkbUeWi6NmkZ06dUd+PYtmuZdSpWIdbz7zVxWiNCYxAXIncA6z1+vwC8KqqNgeSgOz/024FklQ1BnjVqYeItAKuAVoDfYExTmIKBd4C+gGtgGuduq6IDItk2tXT6NW0F3uP7qXnhJ6s27fO78d9+deXGfTlIG74wrpNAkVEOKfhObx/6fvsvn83nep3ytk2Z9McAO7vcr9f5pwYE2z8mkREJBq4CBjrfBagJ5D90IcJwADnfX/nM8728536/YHJqpqqqpuBOKCj84pT1U2qmgZMduq6pnx4eb665ivOb3I+e47uoceEHuw9utdvx1u3bx1P/PQEADe3u9lvxzF5Kx9ePmdwhapy/RnX80CXB7i7490uR2ZMYPh7Kfj/AiOAys7nGsABVc0ePB8P1Hfe1we2A6hqhogcdOrXB7wXq/LeZ/tx5Z3IhYgMAYYANGzYsASnU7Dy4eWZfu10Lv74YjrV70StCrX8cpwszeK26beRmpnKLe1uoVczW1LDbSLC/Wff73YYxgSU35KIiFwM7FXV30Wke3ZxLlW1gG15led2FZXr9HtVfQ94Dzwz1vMJ2ycqhFdg5g0zCQ8J99us5zFLxvDL9l84pdIpvNz7Zb8cwxhjCuLP7qyuwKUisgVPV1NPPFcmVUUkO3lFAzud9/FAAwBnexUg0bv8uH3yKg8KEaEROQlk5+Gd9JrUi42JG33S9pYDWxj1vWccwdsXvU218tV80q4xxhSV35KIqj6oqtGq2hjPjfEfVPV6YB6Q/ZDvwUD2uiHTnc84239Qz8Je04FrnNFbTYDmwGJgCdDcGe0V4Rxjur/OpyQenPsg32/6nh4TerA5aXOJ23tt0WscTT/KVa2vYkDLAQXvYIwxfuLG43FHApNF5GngD+ADp/wDYJKIxOG5ArkGQFX/FJFPgTVABnCXqmYCiMjdwCwgFPifqrozQaMAb/Z7k7jEOH7d/is9JvTgx5t+pHHVxsVu76XeL9GoaiOuPf1a3wVpjDHFYKv4Bsih1EP0+bAPi+IX0bhqY34c/CONqjYKeBzGGFNMtoqvm6LKRTHz+pl0rN+RLQe20GNCD7Yf3F7wjg5V5aVfXmLn4aC57WOMMZZEAqlKZBVm3TCL2HqxbD6wmU///LTQ+05dM5UR34+g89jOrj0r3BhjjufGPZGTWtXIqsy+YTaTV0/mjtg7CrXP/uT93D3DM3ntwXMetPWYjDFBw5KIC6qVr8bQs4bmfN55eCeCULdy3Vzr3zvrXvYe3Uu3Rt34V+y/AhWmMcYUyLqzXLbj0A7OG38ePSb0YPeR3Sds/27Dd0xaOYnIsEjGXjKWELH/ZMaY4GF/kVxWLqwcFcIr8Nf+v+gxoQd7juzJ2XYo9RB3fOPp8nqy+5M0r9HcrTCNMSZXlkRcVrNCTb6/8XtOr3066/ato+fEnjmLNs7dNJcdh3cQWy+We7vc63KkxhhzIpsnEiT2Ht1Ljwk9WJOwhta1WjNv8DxqVazFkh1LqBBegda1W7sdojHm5GbzRIJZ7Yq1+WHQD5xW8zT+TPiT8yeez9G0o5xV/yxLIMaYoGVJJIjUqVSHHwb/QMuaLenfoj8Vwiu4HZIxxuTLhvgGmVMqncLi2xZTKaKS35aRN8YYX7EkEoQql6tccCVjjAkC1p1ljDGm2CyJGGOMKTZLIsYYY4rNkogxxphisyRijDGm2CyJGGOMKTZLIsYYY4rNkogxxphi81sSEZFIEVksIitE5E8RecIpHy8im0VkufNq55SLiLwuInEislJE2nu1NVhENjivwV7lHURklbPP62JTvI0xJqD8OWM9FeipqkdEJBxYICIznG3DVXXqcfX7Ac2dVyfgbaCTiFQHHgNiAQV+F5Hpqprk1BkCLAK+A/oCMzDGGBMQfrsSUY8jzsdw55XfuvP9gYnOfouAqiJSF+gDzFHVRCdxzAH6OtuiVHWhetaznwgM8Nf5GGOMOZFf184SkVDgdyAGeEtVfxORocAzIvIoMBcYpaqpQH1gu9fu8U5ZfuXxuZTnFscQPFcsAEdE5K+SnluA1AT2uR2En9i5lV5l+fzs3PI2U1X7Hl/o1ySiqplAOxGpCkwTkdOBB4HdQATwHjASeJLcH3iixSjPLY73nGOVKiKyVFVj3Y7DH+zcSq+yfH52bkUXkNFZqnoA+BHoq6q7nC6rVGAc0NGpFg808NotGthZQHl0LuXGGGMCxJ+js2o5VyCISHngAmCdcy8DZyTVAGC1s8t0YJAzSqszcFBVdwGzgN4iUk1EqgG9gVnOtsMi0tlpaxDwlb/OxxhjzIn82Z1VF5jg3BcJAT5V1W9E5AcRqYWnO2o5cIdT/zvgQiAOSAZuBlDVRBF5Clji1HtSVROd90OB8UB5PKOyytrIrFLXBVcEdm6lV1k+Pzu3IhLPwCZjjDGm6GzGujHGmGKzJGKMMabYLIkEGRFpICLzRGSts1zMPW7H5GsiEioif4jIN27H4msiUlVEporIOue/YRe3Y/IVEbnX+Te5WkQ+EZFIt2MqCRH5n4jsFZHVXmXVRWSOs8TSHGcwT6mTx7m95Py7XCki07IHPpWUJZHgkwHcr6qnAZ2Bu0Sklcsx+do9wFq3g/CT1/BMymoJtKWMnKeI1Af+DcSq6ulAKHCNu1GV2Hg8SyV5GwXMVdXmOJOhAx2Uj4znxHObA5yuqm2A9Xjm7JWYJZEg48yjWea8P4znj1CuM/FLIxGJBi4Cxrodi6+JSBTQDfgAQFXTnDlSZUUYUF5EwoAKlPJ5War6M5B4XHF/YILzfgKldCml3M5NVWeraobzcRH/nGdXbJZEgpiINAbOBH5zNxKf+i8wAshyOxA/aAokAOOc7rqxIlLR7aB8QVV3AC8D24BdeOZxzXY3Kr+o48xBw/lZ2+V4/OUWfDQlwpJIkBKRSsDnwH9U9ZDb8fiCiFwM7FXV392OxU/CgPbA26p6JnCU0tsd8g/OvYH+QBOgHlBRRG5wNypTHCLyMJ5u84980Z4lkSDkLJ3/OfCRqn7hdjw+1BW4VES2AJOBniLyobsh+VQ8EK+q2VeOU/EklbLgAmCzqiaoajrwBXC2yzH5wx6vVTXqAntdjsennOcxXQxcrz6aJGhJJMg4S7h8AKxV1dFux+NLqvqgqkaramM8N2V/UNUy821WVXcD20WkhVN0PrDGxZB8aRvQWUQqOP9Gz6eMDBo4znQg+8F3gylDSymJSF88C95eqqrJvmrXkkjw6QrciOdbevbTHy90OyhTaMOAj0RkJdAOeNbleHzCubqaCiwDVuH521GqlwgRkU+AhUALEYkXkVuB54FeIrIB6OV8LnXymQr7AQAAAfRJREFUOLc3gcrAHOfvyjs+OZYte2KM+f/27lg1iiiKw/h3IE1AUEhhK9iISNDGJhZpgq+g+AYpxEYQm0QrwXdIkSCmDEK0ExEEsVGirVZJZVKJQgpzLO4NGZeskZtZVsP36+beuzOzxfLfmd05R2rllYgkqZkhIklqZohIkpoZIpKkZoaIJKmZISL1KCIyIlY62xMR8bW1YnGtCjzf2Z49idWP9f8yRKR+fQcuRcRk3Z4Dto6xvzPA/JGrpDExRKT+vaBUKga4CTzdn6j9KtZqT4e3ETFdxxdrD4hXEfElIm7XlzwCzteHwx7XsVOdniVP6hPk0lgYIlL/VoEbtWnTNL9XYX4AvK89He4Dy525C8B14CqwUGuo3QM+Z+blzLxb110B7gAXKZWDZ0b5ZqQ/MUSknmXmBnCOchXyfGD6GrBS170EpiLidJ1bz8zdzNymFP47O+QQ7zJzMzP3gA/1WNJYTIz7BKQT6hml/8YsMNUZP+zW037tod3O2E+Gfz7/dp00cl6JSKOxBDzMzI8D46+BW1D+aQVsH9Ev5hulaJ70T/IbjDQCmblJ6bc+aJHS+XAD+MFB2fFh+9mJiDcR8Ynyg/163+cqHYdVfCVJzbydJUlqZohIkpoZIpKkZoaIJKmZISJJamaISJKaGSKSpGa/AO/ez0x+PRf+AAAAAElFTkSuQmCC\n", "text/plain": [ "<Figure size 432x288 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# Take the chart created above, change the line to a green dashed line\n", "# Mark out the highest profit with a red circle and a text annotation of the \n", "# profit adjust arguments in ylim() and text() to get desired look as below \n", "\n", "# if you want to remove the top and right edge of the chart, uncomment\n", "# the following code.\n", "# ax = plt.gca()\n", "# ax.spines['top'].set_visible(False)\n", "# ax.spines['right'].set_visible(False)\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 54, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 432x288 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# Compare the profit change between apple and pear by two lines\n", "# Make the line of apple red and that of pear green\n", "# Display a legend for the two lines. Should be at the displayed location\n", "\n", "\n" ] }, { "cell_type": "code", "execution_count": 55, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 432x288 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# Create a scatter plot between peach and cherry. Set alpha=0.7\n", "\n" ] }, { "cell_type": "code", "execution_count": 56, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "<Figure size 432x288 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# Create a histogram of Total Profit using pyplot hist(). \n", "# Set the edge color to be white\n", "\n" ] }, { "cell_type": "code", "execution_count": 57, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 864x288 with 3 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# Create a grid of charts with 1 rows and 3 columns. Plot the profit\n", "# comparison of the following pairs in each chart: apple vs pear, \n", "# banana vs kiwi, cherry vs. peach. Add an overall title for the 3 subplots. \n", "# Adjust spaces between charts so the final look resemble the answer.\n", "# The two lines on the same chart must be different but could be different from mine.\n", "# If you want the colors to match my chart, look for color names on this webpage:\n", "# https://matplotlib.org/3.1.1/gallery/color/named_colors.html?highlight=color%20names\n", "\n", "\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# Get the mean profit of each fruit using the mean() method. Save it to\n", "# 'avg_profit'. Make sure to remove that of Total Profit\n" ] }, { "cell_type": "code", "execution_count": 74, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 432x288 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# Create a bar chart using plt.bar(). set 'avg_profit' as height. \n", "# You get the question correct if you get a chart like below\n", "# But you can get an extra point for getting the bar plot sorted\n", "# like the one after this cell. Anyway to get it sorted counts\n", "\n", "\n" ] }, { "cell_type": "code", "execution_count": 83, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 432x288 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "\n", "\n" ] }, { "cell_type": "code", "execution_count": 85, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "(506, 13)\n", "Index(['CRIM', 'ZN', 'INDUS', 'CHAS', 'NOX', 'RM', 'AGE', 'DIS', 'RAD', 'TAX',\n", " 'PTRATIO', 'LSTAT', 'MEDV'],\n", " dtype='object')\n" ] }, { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th>CRIM</th>\n", " <th>ZN</th>\n", " <th>INDUS</th>\n", " <th>CHAS</th>\n", " <th>NOX</th>\n", " <th>RM</th>\n", " <th>AGE</th>\n", " <th>DIS</th>\n", " <th>RAD</th>\n", " <th>TAX</th>\n", " <th>PTRATIO</th>\n", " <th>LSTAT</th>\n", " <th>MEDV</th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>0</th>\n", " <td>0.00632</td>\n", " <td>18.0</td>\n", " <td>2.31</td>\n", " <td>0</td>\n", " <td>0.538</td>\n", " <td>6.575</td>\n", " <td>65.2</td>\n", " <td>4.0900</td>\n", " <td>1</td>\n", " <td>296</td>\n", " <td>15.3</td>\n", " <td>4.98</td>\n", " <td>24.0</td>\n", " </tr>\n", " <tr>\n", " <th>1</th>\n", " <td>0.02731</td>\n", " <td>0.0</td>\n", " <td>7.07</td>\n", " <td>0</td>\n", " <td>0.469</td>\n", " <td>6.421</td>\n", " <td>78.9</td>\n", " <td>4.9671</td>\n", " <td>2</td>\n", " <td>242</td>\n", " <td>17.8</td>\n", " <td>9.14</td>\n", " <td>21.6</td>\n", " </tr>\n", " <tr>\n", " <th>2</th>\n", " <td>0.02729</td>\n", " <td>0.0</td>\n", " <td>7.07</td>\n", " <td>0</td>\n", " <td>0.469</td>\n", " <td>7.185</td>\n", " <td>61.1</td>\n", " <td>4.9671</td>\n", " <td>2</td>\n", " <td>242</td>\n", " <td>17.8</td>\n", " <td>4.03</td>\n", " <td>34.7</td>\n", " </tr>\n", " <tr>\n", " <th>3</th>\n", " <td>0.03237</td>\n", " <td>0.0</td>\n", " <td>2.18</td>\n", " <td>0</td>\n", " <td>0.458</td>\n", " <td>6.998</td>\n", " <td>45.8</td>\n", " <td>6.0622</td>\n", " <td>3</td>\n", " <td>222</td>\n", " <td>18.7</td>\n", " <td>2.94</td>\n", " <td>33.4</td>\n", " </tr>\n", " <tr>\n", " <th>4</th>\n", " <td>0.06905</td>\n", " <td>0.0</td>\n", " <td>2.18</td>\n", " <td>0</td>\n", " <td>0.458</td>\n", " <td>7.147</td>\n", " <td>54.2</td>\n", " <td>6.0622</td>\n", " <td>3</td>\n", " <td>222</td>\n", " <td>18.7</td>\n", " <td>5.33</td>\n", " <td>36.2</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "</div>" ], "text/plain": [ " CRIM ZN INDUS CHAS NOX RM AGE DIS RAD TAX PTRATIO \\\n", "0 0.00632 18.0 2.31 0 0.538 6.575 65.2 4.0900 1 296 15.3 \n", "1 0.02731 0.0 7.07 0 0.469 6.421 78.9 4.9671 2 242 17.8 \n", "2 0.02729 0.0 7.07 0 0.469 7.185 61.1 4.9671 2 242 17.8 \n", "3 0.03237 0.0 2.18 0 0.458 6.998 45.8 6.0622 3 222 18.7 \n", "4 0.06905 0.0 2.18 0 0.458 7.147 54.2 6.0622 3 222 18.7 \n", "\n", " LSTAT MEDV \n", "0 4.98 24.0 \n", "1 9.14 21.6 \n", "2 4.03 34.7 \n", "3 2.94 33.4 \n", "4 5.33 36.2 " ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Load the data in BostonHousing.csv into dataframe 'housing_df'\n", "# print out the shape, columns and top 5 rows of data\n", "\n" ] }, { "cell_type": "code", "execution_count": 76, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 432x288 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# Create a histgram of MEDV using plt.hist()\n", "# find a color picker online and set the color close to min use a color\n", "# picker like this one: https://www.rapidtables.com/web/color/RGB_Color.html\n", "# Give it a title, x and y axis labels\n" ] }, { "cell_type": "code", "execution_count": 77, "metadata": { "scrolled": true }, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "<Figure size 432x288 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# Create a boxplot of MEDV by CHAS using boxplot() of seaborn\n", "# Is housing more expensive by river charles or not?\n", "\n" ] }, { "cell_type": "code", "execution_count": 91, "metadata": { "scrolled": true }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 432x288 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# Create a scatterplot of MEDV and RM using scatter() of pyplot. \n", "# Set alpha to be 0.5 and marker size to be 20\n", "\n" ] }, { "cell_type": "code", "execution_count": 89, "metadata": { "scrolled": true }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 432x288 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# Create a bar chart of RAD and color the bars with CHAS using \n", "# seaborn countplot()\n" ] }, { "cell_type": "code", "execution_count": 87, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 288x576 with 2 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# Create 2 top to bottom charts that displays the scatterplots of CRIM and MEDV \n", "# the one on the top should be houses with CHAS=0 and the one at the bottom CHAS=1\n", "# Add x and y axis labels and legend like the answer\n", "\n", "\n" ] }, { "cell_type": "code", "execution_count": 96, "metadata": { "scrolled": true }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 762.375x720 with 20 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# Create a chart scatterplot matrix using MEDV, RM, CRIM, LSTAT, use CHAS as the hue\n", "\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Exercise for Pandas Groupby and Pivot Table (Optional)" ] }, { "cell_type": "code", "execution_count": 96, "metadata": {}, "outputs": [ { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th>Gender</th>\n", " <th>ClassYear</th>\n", " <th>LarkOwl</th>\n", " <th>NumEarlyClass</th>\n", " <th>EarlyClass</th>\n", " <th>GPA</th>\n", " <th>ClassesMissed</th>\n", " <th>CognitionZscore</th>\n", " <th>PoorSleepQuality</th>\n", " <th>DepressionScore</th>\n", " <th>...</th>\n", " <th>AlcoholUse</th>\n", " <th>Drinks</th>\n", " <th>WeekdayBed</th>\n", " <th>WeekdayRise</th>\n", " <th>WeekdaySleep</th>\n", " <th>WeekendBed</th>\n", " <th>WeekendRise</th>\n", " <th>WeekendSleep</th>\n", " <th>AverageSleep</th>\n", " <th>AllNighter</th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>0</th>\n", " <td>0</td>\n", " <td>4</td>\n", " <td>Neither</td>\n", " <td>0</td>\n", " <td>0</td>\n", " <td>3.60</td>\n", " <td>0</td>\n", " <td>-0.26</td>\n", " <td>4</td>\n", " <td>4</td>\n", " <td>...</td>\n", " <td>Moderate</td>\n", " <td>10</td>\n", " <td>25.75</td>\n", " <td>8.70</td>\n", " <td>7.70</td>\n", " <td>25.75</td>\n", " <td>9.50</td>\n", " <td>5.88</td>\n", " <td>7.18</td>\n", " <td>0</td>\n", " </tr>\n", " <tr>\n", " <th>1</th>\n", " <td>0</td>\n", " <td>4</td>\n", " <td>Neither</td>\n", " <td>2</td>\n", " <td>1</td>\n", " <td>3.24</td>\n", " <td>0</td>\n", " <td>1.39</td>\n", " <td>6</td>\n", " <td>1</td>\n", " <td>...</td>\n", " <td>Moderate</td>\n", " <td>6</td>\n", " <td>25.70</td>\n", " <td>8.20</td>\n", " <td>6.80</td>\n", " <td>26.00</td>\n", " <td>10.00</td>\n", " <td>7.25</td>\n", " <td>6.93</td>\n", " <td>0</td>\n", " </tr>\n", " <tr>\n", " <th>2</th>\n", " <td>0</td>\n", " <td>4</td>\n", " <td>Owl</td>\n", " <td>0</td>\n", " <td>0</td>\n", " <td>2.97</td>\n", " <td>12</td>\n", " <td>0.38</td>\n", " <td>18</td>\n", " <td>18</td>\n", " <td>...</td>\n", " <td>Light</td>\n", " <td>3</td>\n", " <td>27.44</td>\n", " <td>6.55</td>\n", " <td>3.00</td>\n", " <td>28.00</td>\n", " <td>12.59</td>\n", " <td>10.09</td>\n", " <td>5.02</td>\n", " <td>0</td>\n", " </tr>\n", " <tr>\n", " <th>3</th>\n", " <td>0</td>\n", " <td>1</td>\n", " <td>Lark</td>\n", " <td>5</td>\n", " <td>1</td>\n", " <td>3.76</td>\n", " <td>0</td>\n", " <td>1.39</td>\n", " <td>9</td>\n", " <td>1</td>\n", " <td>...</td>\n", " <td>Light</td>\n", " <td>2</td>\n", " <td>23.50</td>\n", " <td>7.17</td>\n", " <td>6.77</td>\n", " <td>27.00</td>\n", " <td>8.00</td>\n", " <td>7.25</td>\n", " <td>6.90</td>\n", " <td>0</td>\n", " </tr>\n", " <tr>\n", " <th>4</th>\n", " <td>0</td>\n", " <td>4</td>\n", " <td>Owl</td>\n", " <td>0</td>\n", " <td>0</td>\n", " <td>3.20</td>\n", " <td>4</td>\n", " <td>1.22</td>\n", " <td>9</td>\n", " <td>7</td>\n", " <td>...</td>\n", " <td>Moderate</td>\n", " <td>4</td>\n", " <td>25.90</td>\n", " <td>8.67</td>\n", " <td>6.09</td>\n", " <td>23.75</td>\n", " <td>9.50</td>\n", " <td>7.00</td>\n", " <td>6.35</td>\n", " <td>0</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "<p>5 rows � 27 columns</p>\n", "</div>" ], "text/plain": [ " Gender ClassYear LarkOwl NumEarlyClass EarlyClass GPA ClassesMissed \\\n", "0 0 4 Neither 0 0 3.60 0 \n", "1 0 4 Neither 2 1 3.24 0 \n", "2 0 4 Owl 0 0 2.97 12 \n", "3 0 1 Lark 5 1 3.76 0 \n", "4 0 4 Owl 0 0 3.20 4 \n", "\n", " CognitionZscore PoorSleepQuality DepressionScore ... AlcoholUse \\\n", "0 -0.26 4 4 ... Moderate \n", "1 1.39 6 1 ... Moderate \n", "2 0.38 18 18 ... Light \n", "3 1.39 9 1 ... Light \n", "4 1.22 9 7 ... Moderate \n", "\n", " Drinks WeekdayBed WeekdayRise WeekdaySleep WeekendBed WeekendRise \\\n", "0 10 25.75 8.70 7.70 25.75 9.50 \n", "1 6 25.70 8.20 6.80 26.00 10.00 \n", "2 3 27.44 6.55 3.00 28.00 12.59 \n", "3 2 23.50 7.17 6.77 27.00 8.00 \n", "4 4 25.90 8.67 6.09 23.75 9.50 \n", "\n", " WeekendSleep AverageSleep AllNighter \n", "0 5.88 7.18 0 \n", "1 7.25 6.93 0 \n", "2 10.09 5.02 0 \n", "3 7.25 6.90 0 \n", "4 7.00 6.35 0 \n", "\n", "[5 rows x 27 columns]" ] }, "execution_count": 96, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# load data in sleepstudy.csv into sleep_df. Display the top 5 rows\n" ] }, { "cell_type": "code", "execution_count": 97, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(253, 27)" ] }, "execution_count": 97, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Get the shape of sleep_df\n" ] }, { "cell_type": "code", "execution_count": 98, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Index(['Gender', 'ClassYear', 'LarkOwl', 'NumEarlyClass', 'EarlyClass', 'GPA',\n", " 'ClassesMissed', 'CognitionZscore', 'PoorSleepQuality',\n", " 'DepressionScore', 'AnxietyScore', 'StressScore', 'DepressionStatus',\n", " 'AnxietyStatus', 'Stress', 'DASScore', 'Happiness', 'AlcoholUse',\n", " 'Drinks', 'WeekdayBed', 'WeekdayRise', 'WeekdaySleep', 'WeekendBed',\n", " 'WeekendRise', 'WeekendSleep', 'AverageSleep', 'AllNighter'],\n", " dtype='object')" ] }, "execution_count": 98, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Get the columns of sleep_df\n" ] }, { "cell_type": "code", "execution_count": 103, "metadata": {}, "outputs": [], "source": [ "# Group sleep_df by larkOwl in a larkOwl_group variable\n" ] }, { "cell_type": "code", "execution_count": 104, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "LarkOwl\n", "Lark 7.960000\n", "Neither 7.873252\n", "Owl 7.763265\n", "Name: WeekdaySleep, dtype: float64" ] }, "execution_count": 104, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# based on larkOwn_group, calculate the average WeekdaySleep\n" ] }, { "cell_type": "code", "execution_count": 106, "metadata": {}, "outputs": [ { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th>WeekdaySleep</th>\n", " <th>WeekendSleep</th>\n", " <th>GPA</th>\n", " </tr>\n", " <tr>\n", " <th>LarkOwl</th>\n", " <th></th>\n", " <th></th>\n", " <th></th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>Lark</th>\n", " <td>7.960000</td>\n", " <td>7.920976</td>\n", " <td>3.330976</td>\n", " </tr>\n", " <tr>\n", " <th>Neither</th>\n", " <td>7.873252</td>\n", " <td>8.235276</td>\n", " <td>3.236012</td>\n", " </tr>\n", " <tr>\n", " <th>Owl</th>\n", " <td>7.763265</td>\n", " <td>8.405102</td>\n", " <td>3.196735</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "</div>" ], "text/plain": [ " WeekdaySleep WeekendSleep GPA\n", "LarkOwl \n", "Lark 7.960000 7.920976 3.330976\n", "Neither 7.873252 8.235276 3.236012\n", "Owl 7.763265 8.405102 3.196735" ] }, "execution_count": 106, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Group sleep_df by larkOwl and calculate the average WeekdaySleep\n", "# WeekendSleep and GPA\n" ] }, { "cell_type": "code", "execution_count": 116, "metadata": {}, "outputs": [ { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead tr th {\n", " text-align: left;\n", " }\n", "\n", " .dataframe thead tr:last-of-type th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr>\n", " <th></th>\n", " <th colspan=\"2\" halign=\"left\">GPA</th>\n", " <th>AverageSleep</th>\n", " <th>CognitionZscore</th>\n", " <th>Happiness</th>\n", " </tr>\n", " <tr>\n", " <th></th>\n", " <th>mean</th>\n", " <th>std</th>\n", " <th>median</th>\n", " <th>mean</th>\n", " <th>mean</th>\n", " </tr>\n", " <tr>\n", " <th>AlcoholUse</th>\n", " <th></th>\n", " <th></th>\n", " <th></th>\n", " <th></th>\n", " <th></th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>Abstain</th>\n", " <td>3.321471</td>\n", " <td>0.479312</td>\n", " <td>7.845</td>\n", " <td>0.068824</td>\n", " <td>26.647059</td>\n", " </tr>\n", " <tr>\n", " <th>Heavy</th>\n", " <td>3.151250</td>\n", " <td>0.436759</td>\n", " <td>7.365</td>\n", " <td>-0.233750</td>\n", " <td>26.562500</td>\n", " </tr>\n", " <tr>\n", " <th>Light</th>\n", " <td>3.280482</td>\n", " <td>0.384926</td>\n", " <td>8.110</td>\n", " <td>0.130241</td>\n", " <td>25.927711</td>\n", " </tr>\n", " <tr>\n", " <th>Moderate</th>\n", " <td>3.208750</td>\n", " <td>0.388863</td>\n", " <td>8.035</td>\n", " <td>-0.078500</td>\n", " <td>26.025000</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "</div>" ], "text/plain": [ " GPA AverageSleep CognitionZscore Happiness\n", " mean std median mean mean\n", "AlcoholUse \n", "Abstain 3.321471 0.479312 7.845 0.068824 26.647059\n", "Heavy 3.151250 0.436759 7.365 -0.233750 26.562500\n", "Light 3.280482 0.384926 8.110 0.130241 25.927711\n", "Moderate 3.208750 0.388863 8.035 -0.078500 26.025000" ] }, "execution_count": 116, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Group sleep_df by AlcohollUse save to alcohol_group\n", "\n", "# use agg() function to get GPA avg, std, AverageSleep median, \n", "# avg CognitionZscore, and avg Happiness \n" ] }, { "cell_type": "code", "execution_count": 123, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "AlcoholUse\n", "Abstain 5.50\n", "Heavy 3.42\n", "Light 4.98\n", "Moderate 4.66\n", "dtype: float64" ] }, "execution_count": 123, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# use the apply() method to get the range of AverageSleep in each group\n", "# You can pass an anoynmous function to the apply() method\n" ] }, { "cell_type": "code", "execution_count": 109, "metadata": { "scrolled": true }, "outputs": [ { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead tr th {\n", " text-align: left;\n", " }\n", "\n", " .dataframe thead tr:last-of-type th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr>\n", " <th>LarkOwl</th>\n", " <th colspan=\"2\" halign=\"left\">Lark</th>\n", " <th colspan=\"2\" halign=\"left\">Neither</th>\n", " <th colspan=\"2\" halign=\"left\">Owl</th>\n", " <th>All</th>\n", " </tr>\n", " <tr>\n", " <th>Gender</th>\n", " <th>0</th>\n", " <th>1</th>\n", " <th>0</th>\n", " <th>1</th>\n", " <th>0</th>\n", " <th>1</th>\n", " <th></th>\n", " </tr>\n", " <tr>\n", " <th>ClassYear</th>\n", " <th></th>\n", " <th></th>\n", " <th></th>\n", " <th></th>\n", " <th></th>\n", " <th></th>\n", " <th></th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>1</th>\n", " <td>4.0</td>\n", " <td>2.0</td>\n", " <td>24.0</td>\n", " <td>9.0</td>\n", " <td>6.0</td>\n", " <td>2.0</td>\n", " <td>47</td>\n", " </tr>\n", " <tr>\n", " <th>2</th>\n", " <td>9.0</td>\n", " <td>9.0</td>\n", " <td>25.0</td>\n", " <td>29.0</td>\n", " <td>9.0</td>\n", " <td>14.0</td>\n", " <td>95</td>\n", " </tr>\n", " <tr>\n", " <th>3</th>\n", " <td>7.0</td>\n", " <td>2.0</td>\n", " <td>19.0</td>\n", " <td>16.0</td>\n", " <td>6.0</td>\n", " <td>4.0</td>\n", " <td>54</td>\n", " </tr>\n", " <tr>\n", " <th>4</th>\n", " <td>7.0</td>\n", " <td>1.0</td>\n", " <td>27.0</td>\n", " <td>14.0</td>\n", " <td>8.0</td>\n", " <td>NaN</td>\n", " <td>57</td>\n", " </tr>\n", " <tr>\n", " <th>All</th>\n", " <td>27.0</td>\n", " <td>14.0</td>\n", " <td>95.0</td>\n", " <td>68.0</td>\n", " <td>29.0</td>\n", " <td>20.0</td>\n", " <td>253</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "</div>" ], "text/plain": [ "LarkOwl Lark Neither Owl All\n", "Gender 0 1 0 1 0 1 \n", "ClassYear \n", "1 4.0 2.0 24.0 9.0 6.0 2.0 47\n", "2 9.0 9.0 25.0 29.0 9.0 14.0 95\n", "3 7.0 2.0 19.0 16.0 6.0 4.0 54\n", "4 7.0 1.0 27.0 14.0 8.0 NaN 57\n", "All 27.0 14.0 95.0 68.0 29.0 20.0 253" ] }, "execution_count": 109, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Get a pivot table of # of students by LarkOwl, ClassYear and Gender\n", "# Display the totals\n" ] }, { "cell_type": "code", "execution_count": 111, "metadata": {}, "outputs": [ { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th>GPA</th>\n", " </tr>\n", " <tr>\n", " <th>AlcoholUse</th>\n", " <th></th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>Abstain</th>\n", " <td>3.321471</td>\n", " </tr>\n", " <tr>\n", " <th>Heavy</th>\n", " <td>3.151250</td>\n", " </tr>\n", " <tr>\n", " <th>Light</th>\n", " <td>3.280482</td>\n", " </tr>\n", " <tr>\n", " <th>Moderate</th>\n", " <td>3.208750</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "</div>" ], "text/plain": [ " GPA\n", "AlcoholUse \n", "Abstain 3.321471\n", "Heavy 3.151250\n", "Light 3.280482\n", "Moderate 3.208750" ] }, "execution_count": 111, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Get a pivot table of avg GPA of students by AlcoholUse\n" ] }, { "cell_type": "code", "execution_count": 89, "metadata": {}, "outputs": [ { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th>AGE</th>\n", " <th>CRIM</th>\n", " <th>DIS</th>\n", " <th>INDUS</th>\n", " <th>LSTAT</th>\n", " <th>MEDV</th>\n", " <th>NOX</th>\n", " <th>PTRATIO</th>\n", " <th>RAD</th>\n", " <th>RM</th>\n", " <th>TAX</th>\n", " <th>ZN</th>\n", " </tr>\n", " <tr>\n", " <th>CHAS</th>\n", " <th></th>\n", " <th></th>\n", " <th></th>\n", " <th></th>\n", " <th></th>\n", " <th></th>\n", " <th></th>\n", " <th></th>\n", " <th></th>\n", " <th></th>\n", " <th></th>\n", " <th></th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>0</th>\n", " <td>67.911677</td>\n", " <td>3.744447</td>\n", " <td>3.851915</td>\n", " <td>11.019193</td>\n", " <td>12.757941</td>\n", " <td>22.093843</td>\n", " <td>0.551817</td>\n", " <td>18.527176</td>\n", " <td>9.566879</td>\n", " <td>6.267174</td>\n", " <td>409.870488</td>\n", " <td>11.634820</td>\n", " </tr>\n", " <tr>\n", " <th>1</th>\n", " <td>77.500000</td>\n", " <td>1.851670</td>\n", " <td>3.029709</td>\n", " <td>12.719143</td>\n", " <td>11.241714</td>\n", " <td>28.440000</td>\n", " <td>0.593426</td>\n", " <td>17.491429</td>\n", " <td>9.314286</td>\n", " <td>6.519600</td>\n", " <td>386.257143</td>\n", " <td>7.714286</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "</div>" ], "text/plain": [ " AGE CRIM DIS INDUS LSTAT MEDV \\\n", "CHAS \n", "0 67.911677 3.744447 3.851915 11.019193 12.757941 22.093843 \n", "1 77.500000 1.851670 3.029709 12.719143 11.241714 28.440000 \n", "\n", " NOX PTRATIO RAD RM TAX ZN \n", "CHAS \n", "0 0.551817 18.527176 9.566879 6.267174 409.870488 11.634820 \n", "1 0.593426 17.491429 9.314286 6.519600 386.257143 7.714286 " ] }, "execution_count": 89, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Get a pivot table with the average of all other columns by CHAS\n", "# Make two rows with CHAS=0 and CHAS=1\n" ] }, { "cell_type": "code", "execution_count": 91, "metadata": {}, "outputs": [ { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th>CHAS</th>\n", " <th>0</th>\n", " <th>1</th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>AGE</th>\n", " <td>67.911677</td>\n", " <td>77.500000</td>\n", " </tr>\n", " <tr>\n", " <th>CRIM</th>\n", " <td>3.744447</td>\n", " <td>1.851670</td>\n", " </tr>\n", " <tr>\n", " <th>DIS</th>\n", " <td>3.851915</td>\n", " <td>3.029709</td>\n", " </tr>\n", " <tr>\n", " <th>INDUS</th>\n", " <td>11.019193</td>\n", " <td>12.719143</td>\n", " </tr>\n", " <tr>\n", " <th>LSTAT</th>\n", " <td>12.757941</td>\n", " <td>11.241714</td>\n", " </tr>\n", " <tr>\n", " <th>MEDV</th>\n", " <td>22.093843</td>\n", " <td>28.440000</td>\n", " </tr>\n", " <tr>\n", " <th>NOX</th>\n", " <td>0.551817</td>\n", " <td>0.593426</td>\n", " </tr>\n", " <tr>\n", " <th>PTRATIO</th>\n", " <td>18.527176</td>\n", " <td>17.491429</td>\n", " </tr>\n", " <tr>\n", " <th>RAD</th>\n", " <td>9.566879</td>\n", " <td>9.314286</td>\n", " </tr>\n", " <tr>\n", " <th>RM</th>\n", " <td>6.267174</td>\n", " <td>6.519600</td>\n", " </tr>\n", " <tr>\n", " <th>TAX</th>\n", " <td>409.870488</td>\n", " <td>386.257143</td>\n", " </tr>\n", " <tr>\n", " <th>ZN</th>\n", " <td>11.634820</td>\n", " <td>7.714286</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "</div>" ], "text/plain": [ "CHAS 0 1\n", "AGE 67.911677 77.500000\n", "CRIM 3.744447 1.851670\n", "DIS 3.851915 3.029709\n", "INDUS 11.019193 12.719143\n", "LSTAT 12.757941 11.241714\n", "MEDV 22.093843 28.440000\n", "NOX 0.551817 0.593426\n", "PTRATIO 18.527176 17.491429\n", "RAD 9.566879 9.314286\n", "RM 6.267174 6.519600\n", "TAX 409.870488 386.257143\n", "ZN 11.634820 7.714286" ] }, "execution_count": 91, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Get a pivot table with the average of all other columns by CHAS\n", "# Make two columns with CHAS=0 and CHAS=1\n" ] }, { "cell_type": "code", "execution_count": 95, "metadata": {}, "outputs": [ { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead tr th {\n", " text-align: left;\n", " }\n", "\n", " .dataframe thead tr:last-of-type th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr>\n", " <th></th>\n", " <th colspan=\"2\" halign=\"left\">AGE</th>\n", " <th colspan=\"2\" halign=\"left\">CRIM</th>\n", " <th colspan=\"2\" halign=\"left\">MEDV</th>\n", " </tr>\n", " <tr>\n", " <th>CHAS</th>\n", " <th>0</th>\n", " <th>1</th>\n", " <th>0</th>\n", " <th>1</th>\n", " <th>0</th>\n", " <th>1</th>\n", " </tr>\n", " <tr>\n", " <th>RAD</th>\n", " <th></th>\n", " <th></th>\n", " <th></th>\n", " <th></th>\n", " <th></th>\n", " <th></th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>1</th>\n", " <td>46.089474</td>\n", " <td>24.800000</td>\n", " <td>0.037135</td>\n", " <td>0.015010</td>\n", " <td>23.015789</td>\n", " <td>50.000000</td>\n", " </tr>\n", " <tr>\n", " <th>2</th>\n", " <td>64.770833</td>\n", " <td>NaN</td>\n", " <td>0.083285</td>\n", " <td>NaN</td>\n", " <td>26.833333</td>\n", " <td>NaN</td>\n", " </tr>\n", " <tr>\n", " <th>3</th>\n", " <td>48.902778</td>\n", " <td>56.650000</td>\n", " <td>0.094087</td>\n", " <td>0.156265</td>\n", " <td>27.927778</td>\n", " <td>27.950000</td>\n", " </tr>\n", " <tr>\n", " <th>4</th>\n", " <td>60.681373</td>\n", " <td>62.887500</td>\n", " <td>0.409490</td>\n", " <td>0.195176</td>\n", " <td>21.040196</td>\n", " <td>25.812500</td>\n", " </tr>\n", " <tr>\n", " <th>5</th>\n", " <td>67.475962</td>\n", " <td>85.745455</td>\n", " <td>0.622514</td>\n", " <td>1.304961</td>\n", " <td>25.521154</td>\n", " <td>27.463636</td>\n", " </tr>\n", " <tr>\n", " <th>6</th>\n", " <td>60.142308</td>\n", " <td>NaN</td>\n", " <td>0.150054</td>\n", " <td>NaN</td>\n", " <td>20.976923</td>\n", " <td>NaN</td>\n", " </tr>\n", " <tr>\n", " <th>7</th>\n", " <td>40.141176</td>\n", " <td>NaN</td>\n", " <td>0.150399</td>\n", " <td>NaN</td>\n", " <td>27.105882</td>\n", " <td>NaN</td>\n", " </tr>\n", " <tr>\n", " <th>8</th>\n", " <td>63.994737</td>\n", " <td>80.100000</td>\n", " <td>0.345052</td>\n", " <td>0.471570</td>\n", " <td>31.505263</td>\n", " <td>26.000000</td>\n", " </tr>\n", " <tr>\n", " <th>24</th>\n", " <td>89.731452</td>\n", " <td>90.950000</td>\n", " <td>13.209833</td>\n", " <td>5.775886</td>\n", " <td>15.438710</td>\n", " <td>31.362500</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "</div>" ], "text/plain": [ " AGE CRIM MEDV \n", "CHAS 0 1 0 1 0 1\n", "RAD \n", "1 46.089474 24.800000 0.037135 0.015010 23.015789 50.000000\n", "2 64.770833 NaN 0.083285 NaN 26.833333 NaN\n", "3 48.902778 56.650000 0.094087 0.156265 27.927778 27.950000\n", "4 60.681373 62.887500 0.409490 0.195176 21.040196 25.812500\n", "5 67.475962 85.745455 0.622514 1.304961 25.521154 27.463636\n", "6 60.142308 NaN 0.150054 NaN 20.976923 NaN\n", "7 40.141176 NaN 0.150399 NaN 27.105882 NaN\n", "8 63.994737 80.100000 0.345052 0.471570 31.505263 26.000000\n", "24 89.731452 90.950000 13.209833 5.775886 15.438710 31.362500" ] }, "execution_count": 95, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Get a pivot table by CHAS and RAD with MEDV, AGE and CRIM as value\n" ] }, { "cell_type": "code", "execution_count": 112, "metadata": {}, "outputs": [ { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th>MEDV</th>\n", " </tr>\n", " <tr>\n", " <th>CRIM</th>\n", " <th></th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>(0.00532, 0.082]</th>\n", " <td>27.370079</td>\n", " </tr>\n", " <tr>\n", " <th>(0.082, 0.257]</th>\n", " <td>22.509524</td>\n", " </tr>\n", " <tr>\n", " <th>(0.257, 3.677]</th>\n", " <td>24.103968</td>\n", " </tr>\n", " <tr>\n", " <th>(3.677, 88.976]</th>\n", " <td>16.159843</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "</div>" ], "text/plain": [ " MEDV\n", "CRIM \n", "(0.00532, 0.082] 27.370079\n", "(0.082, 0.257] 22.509524\n", "(0.257, 3.677] 24.103968\n", "(3.677, 88.976] 16.159843" ] }, "execution_count": 112, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Cut crime rate into 4 quartiles. Save in crime_quartiles\n", "\n", "# Create a pivot table to compare the mean MDEV by the quartiles\n" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.6" } }, "nbformat": 4, "nbformat_minor": 4 }

FruitSales.csv

Month Apple Banana Pear Cherry Watermelon Kiwi Peach Total Profit
1 2500 1500 5200 9200 1200 1490 21100 42190
2 2630 1200 5100 6100 2100 1845 18330 37305
3 2140 1340 4550 9550 3550 1135 22470 44735
4 3400 1130 5870 8870 1870 2007 22270 45417
5 3600 1740 4560 7760 1560 1876 20960 42056
6 2760 1555 4890 7490 1890 1540 20140 40265
7 2980 1120 4780 8980 1780 1120 29550 50310
8 3700 1400 5860 9960 2860 2001 36140 61921
9 3540 1780 6100 8100 2100 1658 23400 46678
10 1990 1890 8300 10300 2300 1900 26670 53350
11 2340 2100 7300 13300 2400 1756 41280 70476
12 2900 1760 7400 14400 1800 1977 30020 60257

SleepStudy.csv

Gender ClassYear LarkOwl NumEarlyClass EarlyClass GPA ClassesMissed CognitionZscore PoorSleepQuality DepressionScore AnxietyScore StressScore DepressionStatus AnxietyStatus Stress DASScore Happiness AlcoholUse Drinks WeekdayBed WeekdayRise WeekdaySleep WeekendBed WeekendRise WeekendSleep AverageSleep AllNighter
0 4 Neither 0 0 3.6 0 -0.26 4 4 3 8 normal normal normal 15 28 Moderate 10 25.75 8.7 7.7 25.75 9.5 5.88 7.18 0
0 4 Neither 2 1 3.24 0 1.39 6 1 0 3 normal normal normal 4 25 Moderate 6 25.7 8.2 6.8 26 10 7.25 6.93 0
0 4 Owl 0 0 2.97 12 0.38 18 18 18 9 moderate severe normal 45 17 Light 3 27.44 6.55 3 28 12.59 10.09 5.02 0
0 1 Lark 5 1 3.76 0 1.39 9 1 4 6 normal normal normal 11 32 Light 2 23.5 7.17 6.77 27 8 7.25 6.9 0
0 4 Owl 0 0 3.2 4 1.22 9 7 25 14 normal severe normal 46 15 Moderate 4 25.9 8.67 6.09 23.75 9.5 7 6.35 0
1 4 Neither 0 0 3.5 0 -0.04 6 14 8 28 moderate moderate high 50 22 Abstain 0 23.8 8.95 9.05 26 10.75 9 9.04 0
1 2 Lark 2 1 3.35 2 0.41 2 1 0 1 normal normal normal 2 25 Moderate 6 25.35 8.48 7.73 25.63 10.13 7 7.52 1
0 2 Lark 0 0 3 0 -0.59 10 2 2 3 normal normal normal 7 29 Light 3 23.9 9.07 9.02 25.13 9.75 9 9.01 0
0 1 Neither 2 1 4 0 1.03 5 12 16 20 moderate severe high 48 29 Light 3 24.4 8.75 8.25 24 9 9.25 8.54 0
0 4 Neither 2 1 2.9 0 0.72 2 6 11 31 normal moderate high 48 30 Moderate 6 26.2 8 6.6 25.38 10.25 6.88 6.68 0
1 2 Neither 1 1 3.7 0 0.06 11 2 12 13 normal moderate normal 27 14 Moderate 10 25 8.53 8.23 25.25 10.75 7.75 8.09 0
1 2 Neither 0 0 3 0 -0.47 8 2 8 11 normal moderate normal 21 24 Moderate 10 25.3 9.8 8.4 26.5 10.75 8.5 8.43 0
0 1 Neither 4 1 3.3 0 -0.14 3 10 13 18 moderate moderate high 41 21 Moderate 4 25.92 7.97 6.34 26.29 11.25 8.25 6.89 0
1 3 Neither 2 1 3.3 6 0.04 7 3 3 2 normal normal normal 8 20 Light 5 25.6 8.73 7.03 27.25 11.5 8.5 7.45 0
0 3 Neither 5 1 3.5 1 -0.4 4 2 0 3 normal normal normal 5 28 Abstain 0 22.9 6.9 8.4 22.25 9.5 10.25 8.93 0
0 3 Lark 0 0 3.4 0 0.4 4 3 1 11 normal normal normal 15 23 Light 2 24 8.77 8.67 25.25 10.5 9.5 8.9 0
0 2 Neither 2 1 2.8 5 -0.8 8 16 7 21 moderate normal high 44 25 Moderate 4 22.9 6.85 8.25 23.75 9.09 8.59 8.34 0
1 2 Lark 5 1 3 0 -1.18 8 23 12 20 severe moderate high 55 24 Heavy 12 24 7.9 8.5 25.5 10.5 7.5 8.22 0
1 2 Neither 3 1 2.8 0 -0.4 3 1 4 1 normal normal normal 6 30 Moderate 10 25.77 9.52 8.55 25.25 11.25 8 8.39 1
1 3 Owl 3 1 2.8 20 -0.57 15 6 5 10 normal normal normal 21 19 Moderate 7 25.25 8.12 7.2 25.67 10.5 8 7.43 0
0 3 Neither 2 1 3.05 4 -0.11 15 4 10 20 normal moderate high 34 30 Light 1 24.5 7.8 7.4 25.5 8.75 7 7.29 0
0 3 Neither 0 0 3.3 1 -0.58 5 1 6 12 normal normal normal 19 34 Light 2 25 9.65 8.45 26 10.38 8.88 8.57 0
0 3 Neither 2 1 2.9 1 -0.05 4 1 1 10 normal normal normal 12 28 Moderate 7 24.63 9.04 9.74 25.75 10.5 8.5 9.39 0
0 1 Neither 0 0 3 5 -0.31 6 5 0 6 normal normal normal 11 27 Light 3 24.6 9.2 9.3 23.75 11.75 10.25 9.57 0
0 2 Neither 2 1 3.2 0 -0.33 3 8 2 8 normal normal normal 18 25 Abstain 0 24.6 8.25 7.65 25.5 10.38 8.88 8 0
1 2 Owl 0 0 3.07 20 -0.62 9 23 5 16 severe normal high 44 24 Abstain 0 24.7 11.02 10.32 27.5 12.25 8.75 9.87 0
1 2 Owl 4 1 3 10 0.16 5 14 13 14 moderate moderate normal 41 28 Moderate 8 24.4 7.95 8.45 24 11.75 9.5 8.75 0
0 4 Neither 2 1 2.9 0 -0.04 8 18 12 26 moderate moderate high 56 17 Moderate 5 24.4 8.6 8.4 25.5 11 9 8.57 0
0 4 Neither 2 1 3.4 3 0.78 9 4 5 9 normal normal normal 18 27 Light 3 23.9 7.8 8 25.25 10 7 7.71 0
0 4 Neither 2 1 3 2 -0.86 6 7 8 14 normal moderate normal 29 25 Moderate 5 25 8.6 8.1 25.5 8.5 5.75 7.43 0
0 2 Neither 2 1 3.75 0 1.37 12 15 15 23 moderate severe high 53 25 Moderate 8 24.05 8.35 8.55 25.38 9.75 7.75 8.32 0
0 1 Neither 3 1 4 0 0.01 5 8 3 10 normal normal normal 21 15 Light 1 22.9 8.3 9.4 27.25 11.5 8.25 9.07 0
0 4 Neither 3 1 2.8 0 -1.27 3 4 1 2 normal normal normal 7 18 Light 6 23.8 8.1 8.4 25.25 10.75 9.25 8.64 0
1 2 Neither 0 0 2.35 6 -0.29 6 4 16 7 normal severe normal 27 21 Moderate 12 25 10.18 9.18 26.5 11.25 8.75 9.06 0
0 2 Neither 3 1 3.04 0 0.2 7 11 13 17 moderate moderate high 41 23 Abstain 0 26.63 8.63 7.05 25.88 11.13 7.38 7.14 0
1 4 Neither 0 0 2.75 0 0.26 11 4 7 5 normal normal normal 16 27 Abstain 0 23.8 7.55 7.75 25 8.88 7.88 7.79 0
0 1 Neither 5 1 3.5 1 0.06 6 2 1 4 normal normal normal 7 27 Light 3 25.8 7.75 6.45 25.5 10.88 8.13 6.93 0
0 1 Neither 3 1 3.2 0 0.62 2 6 4 2 normal normal normal 12 25 Light 1 24.6 8.67 8.17 26.5 11.5 8.75 8.33 0
0 1 Lark 3 1 3.25 5 -0.28 4 4 8 14 normal moderate normal 26 30 Moderate 4 22.83 9.38 10.48 26.25 9.75 7.67 9.68 0
0 4 Neither 0 0 2.9 4 0.05 12 10 12 18 moderate moderate high 40 25 Moderate 4 25.17 8.92 8 25.13 11.25 9.5 8.43 0
0 4 Neither 0 0 3.84 1 -0.05 3 0 1 3 normal normal normal 4 30 Moderate 4 23.9 8.05 7.95 25.5 8.5 7.5 7.82 0
0 4 Neither 0 0 3.5 0 -0.6 5 0 2 13 normal normal normal 15 28 Moderate 3 24.4 8.4 8.6 25 8.75 6.25 7.93 0
1 2 Neither 2 1 2.8 1 0.34 6 0 0 0 normal normal normal 0 26 Light 2 25.4 9.37 7.57 27 11 9 7.98 0
1 1 Neither 2 1 3.25 2 -0.48 7 7 6 7 normal normal normal 20 31 Light 3 23.3 8.4 8.8 25.5 10 9.25 8.93 0
0 1 Neither 2 1 2.9 0 0.07 8 5 6 11 normal normal normal 22 24 Light 5 24.9 9.15 8.25 26.5 11.3 9 8.46 0
1 3 Owl 0 0 3.5 2 0.47 6 9 5 19 normal normal high 33 24 Moderate 9 24.95 8.86 7.97 27 11.63 9.13 8.3 0
0 4 Neither 2 1 3.1 6 -0.32 5 4 9 18 normal moderate high 31 26 Light 3 23.65 8.4 8.95 25.5 9.75 7.75 8.61 0
0 3 Neither 2 1 3.2 1 -0.24 6 2 1 9 normal normal normal 12 28 Light 6 26.6 8 5.9 26 10 6.75 6.14 0
1 1 Owl 1 1 3.4 2 0.04 8 2 2 3 normal normal normal 7 30 Moderate 5 26.8 8.8 6.2 28.5 10.75 5.75 6.07 1
1 2 Neither 2 1 2.5 0 -0.13 4 5 4 11 normal normal normal 20 27 Light 5 25.57 6.67 5.63 23.79 9.42 8.29 6.39 0
1 3 Neither 2 1 3.25 0 -0.39 3 1 1 6 normal normal normal 8 31 Moderate 9 24.12 8.2 7.87 24.96 10 9.59 8.36 0
0 3 Neither 2 1 3 0 1.41 9 21 22 26 severe severe high 69 25 Light 3 25 8.55 7.55 26 10 8 7.68 0
0 2 Neither 3 1 3.2 3 0.59 7 5 6 4 normal normal normal 15 30 Light 2 25.2 9.05 8.23 24.29 9.63 8.38 8.27 0
0 4 Neither 2 1 3.25 4 -1.16 9 7 10 12 normal moderate normal 29 21 Moderate 7 23.2 8.4 8.9 25.25 10 9.5 9.07 0
0 3 Neither 2 1 2 1 -0.75 6 1 2 1 normal normal normal 4 23 Moderate 5 25.3 7.55 6.85 26 7.88 4.38 6.14 0
1 1 Neither 1 1 3.4 1 1.37 10 4 8 8 normal moderate normal 20 28 Abstain 0 27 8.23 4.79 26.5 10.25 8.25 5.78 1
0 2 Owl 0 0 3.4 2 0.53 11 25 10 24 severe moderate high 59 16 Moderate 5 25.2 10.37 9.97 27.25 11.5 6.25 8.9 1
0 2 Neither 5 1 3.3 2 -0.75 5 4 14 27 normal moderate high 45 29 Heavy 5 24.5 7.97 7.12 26.38 8.38 6.88 7.05 0
0 2 Neither 3 1 3.25 0 1.77 4 1 2 2 normal normal normal 5 29 Light 5 25.3 9.2 8.6 24.5 9.75 7.5 8.29 0
1 2 Neither 1 1 2.5 3 0.29 5 2 3 5 normal normal normal 10 21 Moderate 10 26.13 9.38 6 27 10.5 7 6.29 1
0 2 Neither 5 1 3.2 2 0.03 5 0 1 5 normal normal normal 6 31 Light 6 24.4 7.75 7.95 25 10.5 8 7.96 0
0 4 Lark 2 1 3.25 1 1.89 4 0 0 0 normal normal normal 0 30 Light 5 23 6.72 8.22 24.5 9.75 8 8.16 0
0 1 Neither 4 1 3.32 5 0.19 9 4 4 8 normal normal normal 16 25 Moderate 9 24.55 8.28 7.73 29 11 6 7.24 1
1 4 Neither 2 1 3 2 -0.86 12 28 21 25 severe severe high 74 12 Moderate 5 26.45 9.03 6.63 26.25 10.75 8.38 7.13 1
0 3 Owl 3 1 3.67 14 -0.02 9 5 9 12 normal moderate normal 26 32 Abstain 0 25.6 8.17 5.87 28.25 9.25 6.75 6.12 0
0 4 Neither 3 1 3.1 10 -0.37 3 3 2 5 normal normal normal 10 31 Light 3 24.1 8.9 8.9 26 12.5 10.25 9.29 0
0 2 Owl 2 1 2 1 0.48 4 8 2 0 normal normal normal 10 22 Abstain 0 23.1 9.13 10.23 24.5 12 11 10.45 0
0 2 Neither 4 1 3.2 0 -0.48 4 1 2 4 normal normal normal 7 30 Moderate 6 24.33 7.75 7.52 25.75 11.13 9.13 7.98 0
0 2 Neither 2 1 3.4 0 0.36 3 4 6 13 normal normal normal 23 30 Moderate 7 24.2 9.2 8.6 26 11.5 10.5 9.14 0
0 2 Neither 2 1 3.11 4 0.07 8 0 0 6 normal normal normal 6 33 Light 2 23.8 8.53 8.33 25.5 10 9.5 8.66 0
0 2 Neither 0 0 3.4 1 -0.16 4 0 7 4 normal normal normal 11 33 Abstain 0 24.45 8.2 7.65 24.5 8.59 8.34 7.85 0
0 3 Neither 0 0 2.4 4 -0.07 4 2 6 4 normal normal normal 12 25 Light 5 25.75 10.02 8.77 25.5 10.38 7.63 8.44 0
0 1 Owl 5 1 4 0 -0.51 8 4 10 14 normal moderate normal 28 20 Moderate 5 24.4 8.17 7.17 26.5 10.75 9.75 7.9 0
1 2 Lark 3 1 3.35 2 -1.62 8 15 10 31 moderate moderate high 56 12 Moderate 10 23 7.29 8.29 25.13 8.25 7.13 7.96 1
0 4 Neither 2 1 3.3 1 1.22 6 4 4 13 normal normal normal 21 30 Light 4 24.2 8.52 8.62 25 10.75 9 8.73 0
0 3 Owl 2 1 3.3 2 1 10 11 3 17 moderate normal high 31 24 Light 1 24.4 7.5 7.1 23.5 10.5 11 8.21 0
1 4 Neither 0 0 3.6 1 -0.03 6 10 11 18 moderate moderate high 39 29 Light 2 24.3 7.8 7.7 23.5 9 9 8.07 0
0 2 Neither 3 1 3.25 0 -0.04 4 4 1 4 normal normal normal 9 24 Light 5 23.7 7.83 8.23 23.75 8.25 8.25 8.24 0
0 2 Owl 2 1 3.6 3 0.52 5 2 3 6 normal normal normal 11 30 Moderate 4 25.6 8.43 7.33 26.5 12 8.25 7.59 0
0 4 Owl 0 0 3.3 2 -0.6 4 11 1 2 moderate normal normal 14 25 Moderate 8 24.1 9.41 9.41 24.5 8.5 7.75 8.94 0
0 2 Neither 3 1 3.3 0 0.7 7 6 6 17 normal normal high 29 19 Light 2 24.65 8.8 8.75 26.25 10.25 6.5 8.11 0
1 4 Neither 2 1 3 3 -0.8 8 3 0 6 normal normal normal 9 28 Moderate 7 24.15 7.97 8.22 25.75 11 8.25 8.23 0
0 2 Owl 5 1 2.84 0 0.49 3 2 13 21 normal moderate high 36 29 Light 2 24.25 7.54 7.79 24.25 11.5 10 8.42 0
1 2 Neither 2 1 2.75 2 -0.22 2 0 0 1 normal normal normal 1 33 Light 3 25 9.8 8.5 26 11.67 10.42 9.05 0
0 2 Owl 2 1 3.12 15 -1.45 11 8 20 13 normal severe normal 41 30 Abstain 0 27.67 10.52 3.63 27.5 12.25 8.25 4.95 1
1 2 Neither 4 1 3.6 0 -0.01 5 0 0 2 normal normal normal 2 27 Abstain 0 25.5 7.25 5.25 26 8.63 7.88 6 0
0 4 Neither 0 0 3.75 0 -1.21 7 12 12 23 moderate moderate high 47 20 Light 4 22.87 8.19 9.11 23.63 8.5 9.38 9.19 0
0 3 Lark 5 1 3.7 0 0.15 7 2 4 4 normal normal normal 10 31 Light 2 24.4 7.3 6.8 25.25 9.25 8.25 7.21 0
0 4 Lark 3 1 2.4 0 0.03 3 4 5 12 normal normal normal 21 19 Abstain 0 21.8 6.38 8.63 21.5 7.25 9.25 8.8 0
0 4 Neither 2 1 3.6 0 0.3 8 3 17 26 normal severe high 46 30 Moderate 3 25 7.6 5.95 25.63 9 9 6.82 0
1 2 Lark 3 1 3 1 -1.52 3 0 1 2 normal normal normal 3 28 Moderate 4 24.1 9.2 9.2 24.75 11.75 10.75 9.64 0
0 1 Neither 4 1 3.95 3 -0.01 11 12 10 18 moderate moderate high 40 18 Heavy 7 25.2 8.2 7.7 25.5 9.5 6.25 7.29 0
0 1 Neither 2 1 3.43 0 -0.05 4 1 1 2 normal normal normal 4 28 Abstain 0 24.05 8.6 8.65 24.25 8.38 7.88 8.43 0
1 3 Neither 0 0 2.81 2 -0.33 5 0 7 11 normal normal normal 18 27 Moderate 6 25.2 8.85 8.25 25.5 11 8 8.18 0
1 2 Neither 2 1 3 1 0.2 4 0 0 0 normal normal normal 0 34 Heavy 13 25.1 8.1 7 27 10 7 7 0
1 2 Lark 2 1 3.52 1 0.36 3 1 2 5 normal normal normal 8 28 Moderate 10 23.9 8.2 8.6 25.75 12.5 10 9 0
1 4 Neither 2 1 3.2 7 0.11 4 2 1 4 normal normal normal 7 30 Moderate 7 25.3 8.82 7.32 27.5 12.25 9.25 7.87 0
1 4 Neither 2 1 3.67 1 0.09 2 5 1 2 normal normal normal 8 13 Moderate 5 24.4 8.05 7.85 26 9 6.5 7.46 0
1 2 Owl 0 0 3.6 6 0.34 5 0 2 6 normal normal normal 8 29 Moderate 10 25.1 9.8 9.3 25.25 10.5 7.75 8.86 0
0 4 Lark 0 0 3.62 4 0.76 6 3 7 25 normal normal high 35 33 Moderate 3 25.27 7.17 7.3 23 11 8.5 7.64 1
0 3 Lark 2 1 3.6 0 0.11 5 0 0 0 normal normal normal 0 31 Light 5 24.2 8.05 7.45 25 9.75 9.75 8.11 0
0 1 Neither 5 1 3.9 0 0.11 6 4 7 14 normal normal normal 25 25 Light 3 26.1 8 6 25.5 9.5 7.75 6.5 1
0 3 Owl 2 1 3.5 1 -0.37 4 14 4 7 moderate normal normal 25 28 Abstain 1 25.4 8.07 6.67 26 8.13 6.13 6.51 0
0 1 Neither 4 1 3.7 0 -0.43 6 9 13 25 normal moderate high 47 17 Light 5 25.05 8.37 8.22 24.5 9.63 6.88 7.83 0
1 2 Neither 5 1 3.2 2 -1.02 7 21 12 20 severe moderate high 53 16 Light 9 25.3 8.45 6.7 26.13 10.96 9.96 7.63 1
0 1 Owl 5 1 3.2 0 0.21 3 6 9 5 normal moderate normal 20 28 Moderate 9 24.25 8.08 8.63 24.75 10.88 8.13 8.49 0
0 3 Owl 2 1 3 1 0.52 6 0 0 3 normal normal normal 3 28 Moderate 3 24 9.3 9.85 24.88 12.5 10.25 9.96 0
0 3 Neither 2 1 3.3 7 -0.31 14 19 15 37 moderate severe high 71 20 Moderate 3 22.83 8.45 9.13 23 10.5 11.5 9.8 0
0 3 Neither 2 1 3.8 1 0.24 5 2 4 19 normal normal high 25 31 Moderate 5 24.75 8.2 7.25 26.13 11.25 9.63 7.93 0
0 1 Neither 3 1 3.5 0 1.14 8 1 4 7 normal normal normal 12 29 Moderate 4 24.6 7.57 7.17 25.75 9 6.75 7.05 0
0 4 Lark 2 1 3.93 0 -0.72 4 0 9 13 normal moderate normal 22 29 Light 1 23.55 6.8 7.05 24 8.5 9 7.61 0
1 2 Lark 3 1 3.78 0 0.25 2 0 3 2 normal normal normal 5 26 Abstain 0 23.83 7.46 7.78 23.63 8 8 7.84 0
1 1 Neither 2 1 3.83 0 0.95 3 0 0 1 normal normal normal 1 33 Abstain 0 25.2 9.7 9.2 25.75 10.34 6.84 8.52 0
1 3 Neither 2 1 3.3 0 0.02 1 0 0 0 normal normal normal 0 28 Moderate 7 25.17 8.73 8.22 24.5 10.75 9.5 8.59 0
0 4 Neither 2 1 3.1 3 -0.82 5 1 3 6 normal normal normal 10 29 Moderate 6 26.4 7.6 5.7 26.75 12 8 6.36 0
0 4 Owl 0 0 3.35 0 -0.04 5 4 0 4 normal normal normal 8 27 Moderate 8 24.7 9.05 8.95 25.25 10.25 7.5 8.54 0
0 2 Owl 2 1 3.5 1 0.79 8 1 0 1 normal normal normal 2 33 Moderate 12 25.65 8.71 8.16 25.88 9.46 4.84 7.21 0
1 1 Lark 3 1 3.75 2 0.91 9 35 0 14 severe normal normal 49 5 Light 2 25.2 8.1 7.3 26 11.5 8.5 7.64 0
1 2 Neither 3 1 3.68 0 0.56 5 2 3 1 normal normal normal 6 28 Light 1 25.8 8.27 6.57 26.25 10.75 8.25 7.05 0
1 2 Neither 5 1 3.3 7 -0.76 6 14 3 10 moderate normal normal 27 16 Moderate 5 24.8 7.5 7.5 25.5 12.75 9.25 8 0
1 2 Neither 3 1 2.66 2 0.58 5 1 1 0 normal normal normal 2 28 Moderate 9 25.85 8.8 6.95 26.25 10.25 8 7.25 0
1 3 Neither 3 1 3.36 0 0.56 4 2 4 7 normal normal normal 13 32 Moderate 6 22.6 7.55 9.05 23.25 9.25 9.75 9.25 0
0 1 Lark 5 1 3.2 2 1.13 9 11 13 7 moderate moderate normal 31 13 Abstain 0 24.3 6.9 7.2 24.5 11 9 7.71 0
0 2 Neither 0 0 3 5 1.03 4 3 6 10 normal normal normal 19 29 Moderate 7 25.25 9.48 8.48 25.38 9.5 7.5 8.2 0
0 3 Neither 5 1 3.7 1 0.98 10 1 3 4 normal normal normal 8 29 Abstain 0 23.75 7.08 7.43 24.5 8.75 8 7.6 0
1 2 Owl 3 1 2.3 4 -1.23 8 2 3 2 normal normal normal 7 31 Light 12 26.3 8.07 6.57 26.25 13.75 9.5 7.4 0
1 2 Neither 3 1 3 4 -1.62 3 5 4 8 normal normal normal 17 30 Abstain 0 24.75 8.05 8.6 23.42 8.5 5.84 7.81 1
1 1 Neither 4 1 4 0 0.92 4 1 3 2 normal normal normal 6 32 Moderate 6 23.8 8.45 8.8 24.13 10.54 10.04 9.15 0
0 2 Neither 5 1 3 7 -0.75 8 13 10 22 moderate moderate high 45 15 Moderate 5 24.6 8 8.2 24 12 10 8.71 0
1 2 Neither 5 1 3.5 2 0.26 5 5 12 22 normal moderate high 39 28 Abstain 0 26.5 7.7 4.3 26 11.5 10 5.93 1
1 3 Neither 1 1 2.9 0 -0.4 6 1 2 3 normal normal normal 6 29 Moderate 8 25.1 8.25 7.15 26.5 11 8.5 7.54 0
1 4 Lark 0 0 3 1 -0.89 6 7 10 23 normal moderate high 40 25 Light 8 24.9 8.92 8.02 27.25 10.25 7 7.73 0
1 3 Neither 0 0 3.5 1 -0.99 8 3 1 6 normal normal normal 10 30 Moderate 7 26.5 9.64 7.64 26.25 11.25 7.75 7.67 0
1 2 Neither 0 0 3.4 0 -1.06 9 10 3 8 moderate normal normal 21 25 Light 4 25.9 8.65 7.05 25.5 9.75 7.5 7.18 0
1 3 Neither 0 0 3.9 4 0.52 6 4 2 7 normal normal normal 13 24 Heavy 12 25.6 9.85 8.85 25 10.75 8.25 8.68 0
0 2 Neither 0 0 3.72 1 1.45 4 4 1 8 normal normal normal 13 29 Light 3 25.34 8.16 8.03 27 10.25 7.5 7.88 0
0 3 Lark 2 1 3.5 0 1 2 0 6 13 normal normal normal 19 29 Moderate 6 24.63 7 6 27 8.5 6 6 1
0 2 Lark 3 1 3.6 1 1.19 4 20 9 25 moderate moderate high 54 28 Light 2 23.3 6.65 7.65 24 7.5 6.75 7.39 0
0 4 Neither 0 0 3.6 2 1.48 6 1 1 0 normal normal normal 2 30 Moderate 7 25.77 9.78 8.32 26.25 9.75 6.75 7.87 0
0 4 Neither 2 1 3.8 4 0.49 9 14 1 13 moderate normal normal 28 19 Light 4 25.7 8.75 4.45 26.5 11 9 5.75 0
0 2 Neither 2 1 3.44 0 -0.2 5 7 8 16 normal moderate high 31 27 Light 4 24.1 9.2 9.2 25 10.88 9.63 9.32 0
0 3 Lark 0 0 3.89 2 0.78 6 1 3 18 normal normal high 22 32 Moderate 6 25.45 7.44 6.49 24.63 9.38 7.5 6.78 0
0 1 Neither 0 0 3.5 2 -1.17 8 12 7 13 moderate normal normal 32 25 Light 4 26.6 9.1 7 26.25 8.5 5 6.43 0
0 3 Neither 0 0 3.61 2 0.58 13 24 21 37 severe severe high 82 11 Light 4 24.75 9.9 9.4 25.38 10 8 9 0
0 4 Lark 2 1 3.43 2 0.27 5 0 4 4 normal normal normal 8 31 Light 3 23.07 8.18 9.57 23.88 9.25 8.25 9.19 0
0 4 Lark 0 0 3.79 0 -0.42 3 3 2 9 normal normal normal 14 30 Light 1 25.46 8.78 7.83 25 10.42 8.42 7.99 0
0 4 Owl 0 0 3.4 6 -0.03 5 3 4 12 normal normal normal 19 21 Moderate 5 25.8 8.5 6.5 27.5 9 6 6.36 1
0 4 Owl 1 1 3.19 13 -0.47 8 2 8 11 normal moderate normal 21 30 Moderate 6 26 9.05 6.65 26.88 10.67 8.79 7.26 0
1 2 Owl 0 0 3.1 7 -1.17 5 3 2 1 normal normal normal 6 29 Moderate 9 26.13 9.37 7.28 27.5 11.76 8.14 7.53 0
0 3 Neither 2 1 3.52 1 0.44 4 9 4 8 normal normal normal 21 19 Moderate 8 23.9 7.6 7.7 25.75 9.25 7.5 7.64 0
0 3 Neither 0 0 3.2 0 0.59 2 0 0 1 normal normal normal 1 30 Light 3 24.67 8.92 8.95 24.5 11 8.75 8.89 0
0 1 Neither 3 1 3.25 3 -0.2 7 5 5 13 normal normal normal 23 21 Moderate 8 24.35 7.62 6.87 24.75 10 10.25 7.83 0
0 2 Neither 5 1 3 7 0.28 4 3 2 1 normal normal normal 6 23 Moderate 10 24.75 7.8 6.75 26 9.75 7.75 7.04 0
0 4 Neither 2 1 3.74 1 0.21 7 3 8 13 normal moderate normal 24 33 Light 3 24.1 7.8 7.4 25 9.75 9.5 8 0
0 4 Neither 0 0 3.3 0 0.13 5 0 1 7 normal normal normal 8 26 Moderate 6 24.7 9.1 9 24.5 10.25 8.25 8.79 0
0 3 Owl 2 1 3 1 0.26 4 1 0 3 normal normal normal 4 29 Moderate 5 24.8 8.73 8.03 25.25 10 8.5 8.17 0
0 3 Neither 2 1 2.8 1 -0.17 8 4 14 12 normal moderate normal 30 27 Moderate 6 24.1 9.25 9.05 26.5 8.25 6 8.18 0
0 1 Neither 0 0 4 0 0.09 6 10 8 24 moderate moderate high 42 19 Abstain 0 23 8.73 9.88 23.13 9.25 9.75 9.85 0
0 1 Neither 1 1 3.9 0 1.96 6 0 1 2 normal normal normal 3 29 Light 8 24.5 8.25 7.95 25 9.25 7.75 7.89 0
0 1 Owl 3 1 4 0 0.18 6 1 0 1 normal normal normal 2 28 Moderate 8 24.9 8.25 7.65 25.75 9.63 7.13 7.5 0
1 2 Neither 0 0 3.5 0 -0.22 3 18 13 36 moderate moderate high 67 29 Moderate 7 24.27 8.57 7.57 26.25 10.25 9.84 8.21 0
0 2 Lark 1 1 3.4 0 1.71 2 0 4 4 normal normal normal 8 31 Light 2 23.55 8.2 9.2 24 8.88 7.5 8.71 0
1 2 Owl 0 0 3.25 15 -0.82 7 8 6 5 normal normal normal 19 26 Moderate 7 25.1 10.2 8.9 28.25 12.75 9 8.93 1
1 2 Owl 0 0 2.5 0 -0.93 10 11 10 9 moderate moderate normal 30 29 Heavy 15 27.3 10.4 7.1 28.5 11 6.5 6.93 1
1 2 Owl 3 1 3.3 0 -1.15 11 3 2 5 normal normal normal 10 30 Abstain 0 25.4 9.1 7.3 26.5 10.5 9 7.79 0
0 4 Lark 4 1 3.5 0 0.19 1 0 1 1 normal normal normal 2 35 Light 2 24.4 8.2 7.7 25 10.25 9.5 8.21 0
0 2 Neither 0 0 2.5 0 0.75 6 13 1 14 moderate normal normal 28 26 Moderate 5 24.9 9.5 8.6 26.25 9.75 7.5 8.29 0
1 1 Owl 1 1 4 3 -0.12 11 5 1 3 normal normal normal 9 25 Moderate 9 26.9 9.6 6.7 25.5 10.29 8.79 7.3 1
1 3 Owl 0 0 2.4 4 -0.79 8 4 7 5 normal normal normal 16 31 Moderate 10 26.13 10.13 8.83 27.25 10.75 5.44 7.86 0
0 4 Neither 2 1 3.15 2 0.2 8 3 4 8 normal normal normal 15 30 Light 5 24.7 8.35 7.65 25.5 11 9.5 8.18 0
0 1 Neither 1 1 3.75 0 -0.83 4 2 3 18 normal normal high 23 31 Abstain 0 24.4 7.95 7.65 26.25 10.5 8 7.75 0
0 4 Neither 0 0 3 0 -0.04 6 2 0 4 normal normal normal 6 20 Light 10 24.5 8.1 8.25 25.88 9.25 7.25 7.96 1
0 1 Owl 0 0 3.75 0 0.68 6 15 0 13 moderate normal normal 28 27 Moderate 3 26 9.4 8 25.5 9.75 6.75 7.64 0
1 3 Neither 2 1 3.5 3 0.3 10 9 18 16 normal severe high 43 11 Heavy 8 26.1 8.27 6.72 26.63 10 6 6.51 0
0 2 Owl 0 0 3.3 2 -0.84 5 1 4 4 normal normal normal 9 24 Moderate 7 24.3 10.52 10.12 27.5 12.5 9.25 9.87 0
1 2 Neither 0 0 2.75 0 -0.54 7 3 5 2 normal normal normal 10 30 Moderate 13 26 9.6 7.8 27.5 12 8 7.86 0
1 2 Owl 0 0 2.5 1 -0.11 11 23 9 18 severe moderate high 50 12 Moderate 14 24.75 7.8 6.85 26.63 8.42 6.29 6.69 0
1 2 Neither 0 0 2.75 2 -1.04 4 4 6 8 normal normal normal 18 29 Moderate 10 24 10.97 10.97 25.5 11.25 9.75 10.62 0
0 2 Neither 0 0 2.8 0 -1.37 5 1 0 2 normal normal normal 3 31 Moderate 6 25.95 9.15 7.09 27.95 10.84 7.18 7.11 0
0 4 Neither 0 0 3.4 1 -0.78 9 4 14 18 normal moderate high 36 27 Light 3 24.7 8.7 8.05 24.13 8.25 8 8.04 0
1 1 Neither 2 1 3.8 1 0.8 6 0 0 0 normal normal normal 0 27 Moderate 10 24.5 9.05 8.05 24.25 9 10 8.61 0
1 1 Neither 1 1 3.6 1 0.45 6 0 6 15 normal normal high 21 22 Light 12 23.2 5.5 6.3 24 7.25 7.25 6.57 0
1 4 Neither 0 0 2.75 5 -0.81 6 2 1 3 normal normal normal 6 29 Light 10 24.5 8.9 8.5 25.25 9.75 8.25 8.43 0
1 4 Neither 0 0 3.1 3 0.85 7 1 2 2 normal normal normal 5 28 Moderate 8 24.3 9.05 8.75 25.5 10.25 8.75 8.75 0
0 4 Neither 2 1 2.5 3 -0.65 6 0 1 4 normal normal normal 5 28 Moderate 4 24.4 8.4 7.8 24.5 9.5 9.5 8.29 0
1 2 Neither 3 1 3.25 1 -1.13 5 0 3 8 normal normal normal 11 32 Moderate 8 25.5 8.8 7.45 26.13 9.5 7 7.32 0
0 1 Owl 0 0 3.5 4 1.12 3 2 3 8 normal normal normal 13 21 Moderate 10 25.75 9.88 7.93 25.75 11.13 9.88 8.49 0
0 3 Neither 2 1 2.77 2 0.83 5 4 8 14 normal moderate normal 26 27 Light 10 24.75 8.5 7.75 26.63 9.75 7.13 7.57 0
0 1 Neither 1 1 3.7 2 -0.46 7 5 10 8 normal moderate normal 23 27 Moderate 6 25.35 9.25 8.3 27 9.25 5.25 7.43 1
0 2 Lark 0 0 3.3 5 0.22 5 3 3 6 normal normal normal 12 31 Moderate 6 23.7 8.93 9.63 25 9 7 8.88 0
1 2 Owl 2 1 2.8 0 -0.01 10 8 10 7 normal moderate normal 25 22 Moderate 12 25.7 8.8 7.1 26.25 10.5 8.25 7.43 0
0 2 Lark 0 0 3.7 1 0.28 5 7 13 23 normal moderate high 43 29 Abstain 0 24.95 8.35 6.6 25 8.75 9.75 7.5 0
1 2 Lark 3 1 3.2 3 -0.73 12 13 1 14 moderate normal normal 28 27 Heavy 10 25.15 7.1 5.7 23.71 6.5 7.42 6.19 0
1 2 Lark 3 1 3.24 6 -0.29 5 4 11 16 normal moderate high 31 0 Moderate 12 26.8 8.45 5.95 25.5 8.25 6 5.96 1
1 3 Neither 0 0 2.75 5 -0.05 14 26 18 24 severe severe high 68 21 Light 3 25.8 8.23 6.43 26.5 12.75 10.25 7.52 0
0 4 Neither 0 0 3.4 1 0.39 6 0 1 2 normal normal normal 3 33 Moderate 6 26.7 11 8.5 26.5 10 7 8.07 0
0 3 Neither 2 1 3.3 0 1.06 4 6 2 8 normal normal normal 16 20 Abstain 0 23.65 7.82 7.97 24.75 8.25 8 7.98 0
1 3 Neither 0 0 2.8 2 -0.02 5 0 10 7 normal moderate normal 17 29 Moderate 10 24.3 9.58 8.98 25.5 9.13 8.38 8.81 0
0 2 Owl 2 1 3.32 0 -0.93 9 6 0 11 normal normal normal 17 28 Heavy 7 25 9.15 8.35 27 13.5 10 8.82 0
0 4 Owl 2 1 3.7 6 0.24 11 8 15 25 normal severe high 48 28 Moderate 9 25.2 9.57 7.57 26.25 13 12.75 9.05 0
1 4 Neither 0 0 3 6 0.03 4 6 2 4 normal normal normal 12 30 Moderate 10 24.87 9.05 7.98 27.5 9.75 6.75 7.63 1
1 2 Neither 0 0 3.2 0 0.3 3 0 0 1 normal normal normal 1 35 Abstain 0 25.85 10.1 7.95 27.5 13.5 10.75 8.75 0
1 3 Lark 0 0 2 2 -0.08 9 0 0 0 normal normal normal 0 22 Abstain 0 26.5 9.25 6.4 26 11 6.5 6.43 1
1 4 Neither 2 1 2.98 14 -0.33 6 4 2 6 normal normal normal 12 31 Moderate 10 24.9 8.5 7.8 26 10.75 8.25 7.93 0
0 4 Owl 1 1 3 3 0.63 4 1 2 0 normal normal normal 3 32 Heavy 7 25.5 10.95 9.45 26.5 12.5 10 9.61 0
1 4 Neither 2 1 2.5 1 0.76 5 15 2 5 moderate normal normal 22 29 Heavy 20 25.05 9.92 8.87 26.63 9.92 7.29 8.42 1
1 2 Neither 2 1 3.2 0 -0.83 5 1 0 0 normal normal normal 1 25 Moderate 9 25.13 8.42 7.73 25.63 9.25 6.5 7.38 0
0 2 Owl 2 1 3.6 1 0.79 8 7 7 11 normal normal normal 25 28 Abstain 0 25.13 8.8 7.67 28.5 14 9.5 8.19 0
0 2 Neither 5 1 3.2 1 -0.97 8 6 2 24 normal normal high 32 26 Moderate 7 24.1 7.78 7.72 24.15 9.79 9.54 8.24 0
0 3 Owl 2 1 3.56 4 -0.04 11 5 12 20 normal moderate high 37 22 Moderate 6 26.58 10.55 7.97 27 12.69 9.69 8.46 0
0 2 Neither 0 0 3 1 -0.52 9 1 5 2 normal normal normal 8 28 Abstain 0 24.2 8.97 9.17 24 9.25 8.25 8.9 0
0 4 Neither 3 1 3.1 0 0.27 5 3 2 5 normal normal normal 10 27 Light 7 24.2 8.1 8.1 24 8 7.5 7.93 0
1 3 Neither 2 1 3.3 1 -0.64 3 2 5 13 normal normal normal 20 27 Moderate 10 25.7 8.55 7.05 27 10.25 6.75 6.96 0
0 2 Lark 2 1 3.55 1 0.93 3 0 1 0 normal normal normal 1 23 Light 3 23.73 7.88 8.05 23.75 7.13 7.63 7.93 0
1 2 Lark 0 0 2.9 0 -0.18 8 1 0 1 normal normal normal 2 33 Light 10 24.25 9 8.9 25.75 9.25 7.13 8.39 0
0 1 Neither 2 1 4 1 -0.18 7 14 6 16 moderate normal high 36 24 Abstain 0 23.35 6.95 7.7 22.75 9.75 10.75 8.57 0
1 1 Neither 0 0 3.75 2 0.97 6 4 4 7 normal normal normal 15 25 Abstain 0 24.2 8.92 8.12 26.25 9.25 8.5 8.23 1
1 1 Lark 4 1 3.42 0 -0.51 8 16 1 4 moderate normal normal 21 26 Light 5 24.09 8.14 8.75 25.5 13.27 10.02 9.11 0
1 4 Neither 0 0 2.5 6 0.36 4 2 5 3 normal normal normal 10 30 Heavy 10 25.7 10.1 8.3 26.75 11.25 8.75 8.43 0
1 3 Lark 0 0 3 2 -0.71 9 9 3 5 normal normal normal 17 17 Moderate 20 26.15 9.5 7.35 27.25 11.75 8.5 7.68 0
1 2 Owl 2 1 3 2 0.7 7 6 1 2 normal normal normal 9 28 Moderate 15 25.25 9.3 8.3 25.63 10.75 8.5 8.36 0
1 3 Neither 2 1 3 2 -0.91 5 1 2 8 normal normal normal 11 31 Heavy 10 24.9 8.37 7.57 26.75 11.75 8.75 7.91 0
1 2 Neither 2 1 3.23 0 0.22 9 0 4 0 normal normal normal 4 30 Moderate 9 25.5 8.48 7.58 23.5 11 10 8.27 1
1 2 Owl 2 1 2.4 3 0.11 13 1 1 0 normal normal normal 2 24 Light 1 26.1 9.62 7.82 26.75 11.75 8.25 7.94 0
0 1 Neither 2 1 3.2 2 0.27 8 0 0 2 normal normal normal 2 22 Light 3 25.36 10.03 8.29 28.25 12.96 9.67 8.68 1
1 3 Owl 0 0 3 5 -0.49 7 1 3 1 normal normal normal 5 29 Heavy 15 29.1 12.02 7.02 30.25 15 8.5 7.44 1
1 4 Neither 2 1 3.35 2 -0.6 7 5 8 16 normal moderate high 29 24 Heavy 18 25.4 7.83 6.73 25.5 10.75 8.5 7.24 0
1 2 Owl 0 0 2.8 4 0.09 8 6 8 13 normal moderate normal 27 26 Moderate 10 25.9 10.2 8.2 26 10 8.25 8.21 1
0 3 Lark 0 0 3.25 1 -0.37 6 6 12 16 normal moderate high 34 29 Light 3 23.2 9.3 10.9 23.5 8 6.5 9.64 0
0 2 Lark 0 0 3.6 0 0.12 4 2 6 5 normal normal normal 13 18 Light 2 22.3 8.2 9.9 24.5 8 7.5 9.21 0
1 2 Neither 1 1 2.8 6 -0.14 2 7 4 11 normal normal normal 22 18 Light 24 24.4 7.2 7.4 26 10.5 7 7.29 0
0 2 Neither 3 1 3.5 0 -0.72 6 2 4 8 normal normal normal 14 30 Light 2 26.3 7.35 5.35 26 9.13 6.38 5.64 0
0 1 Neither 4 1 3.5 0 -0.54 3 2 4 5 normal normal normal 11 27 Moderate 3 25.15 8 7.2 25.88 10.13 7.38 7.25 1
0 2 Neither 0 0 3.4 0 -1.11 4 2 5 7 normal normal normal 14 25 Light 4 24.8 9.25 9.25 24.75 9.75 7 8.61 0
0 2 Lark 0 0 3.3 6 -0.09 15 3 26 16 normal severe high 45 18 Moderate 5 24.6 7.8 8.2 26.5 9 4 7 0
0 3 Neither 0 0 3.4 0 0.02 7 6 9 12 normal moderate normal 27 26 Heavy 10 24.8 7.8 7.6 26 9.5 6 7.14 0
1 1 Neither 3 1 2.8 1 -0.34 4 0 2 0 normal normal normal 2 32 Moderate 7 25.5 8.87 7.57 25 11.5 10 8.26 0
1 3 Neither 0 0 3.72 2 -0.01 3 0 4 9 normal normal normal 13 32 Light 3 24.9 8.47 7.77 25 10 8.5 7.98 0
1 1 Neither 2 1 3.4 0 0.39 10 3 1 8 normal normal normal 12 23 Moderate 8 23.7 7.65 8.15 22 5.25 6.75 7.75 0
0 2 Lark 2 1 3.3 3 -0.38 4 3 10 11 normal moderate normal 24 27 Moderate 6 24.15 8.58 8.43 25.5 9.34 7.84 8.26 0
1 2 Neither 0 0 2.7 0 -0.45 5 4 5 3 normal normal normal 12 25 Light 7 24.2 10.4 10.2 24 9.5 9.5 10 0
1 2 Owl 3 1 3.4 0 -0.14 4 0 1 3 normal normal normal 4 30 Abstain 0 24.9 9.2 8.7 24.88 10.75 8.88 8.75 0
1 2 Neither 0 0 3.15 2 -0.43 5 0 4 3 normal normal normal 7 30 Moderate 12 25.2 10.4 9.6 26.5 10.5 7 8.86 0
0 1 Neither 0 0 3.5 0 -1.05 10 7 10 10 normal moderate normal 27 30 Moderate 6 24.2 8.27 7.67 26.25 10.92 9.67 8.24 0
0 1 Lark 0 0 2.5 8 -1.13 10 5 15 4 normal severe normal 24 29 Moderate 5 25.7 8.2 6.6 23.5 6 6.25 6.5 1
0 1 Owl 2 1 3.25 0 -0.38 2 1 2 8 normal normal normal 11 34 Moderate 7 25.35 9.4 8.55 25.25 11 8.5 8.54 0
1 3 Neither 0 0 3.15 10 0.59 3 1 0 1 normal normal normal 2 30 Light 5 25.35 9.73 8.38 25.88 10.25 8.38 8.38 0
0 3 Lark 2 1 3.34 0 0.91 2 0 3 6 normal normal normal 9 30 Abstain 0 24 7.45 7.55 24 8 7.75 7.61 0
1 3 Neither 0 0 3.35 7 0.87 11 5 4 15 normal normal high 24 16 Light 3 26.75 9.42 6.77 24.5 10.5 9.5 7.55 1
0 1 Neither 2 1 3 1 -0.32 9 8 5 6 normal normal normal 19 20 Light 5 23.6 8.63 9.03 24.5 10 9.5 9.17 0
0 3 Neither 2 1 3.5 1 1.3 2 1 1 1 normal normal normal 3 35 Moderate 5 24.45 8.25 7.8 25 9.75 8.75 8.07 0
1 2 Neither 2 1 2.6 0 -0.29 5 1 1 3 normal normal normal 5 31 Moderate 7 24.38 9.2 8.97 26 9.88 7.5 8.55 0
1 2 Neither 5 1 2.5 3 -1 3 2 1 2 normal normal normal 5 32 Moderate 13 23.35 7.75 8.4 25 10.88 9.88 8.82 0