diff --git a/journal/Readme.md b/journal/Readme.md index a0349e26d1017f459fe8d254cf75ae2574b3ebf2..8749f9e5ed4aa03ed2256bbe4f80a37bb191bceb 100644 --- a/journal/Readme.md +++ b/journal/Readme.md @@ -27,6 +27,10 @@ Je sens que si on ne maitrise pas déjà les outils ça va être **très** compl Bon allez, un dernier tour de tests et on remballe. _**Tant pis**_ +<<<<<<< HEAD +======= + +>>>>>>> ba4ea19d979d665f06f8e31e40e57c0e74f5f857 ## 8 février 2021: Une lumière au bout du tunnel Après des **HEURES** passées sur internet et des _**dizaines**_ de tentatives, je crois que je touche au but. diff --git a/module3/exo1/analyse-syndrome-grippal.ipynb b/module3/exo1/analyse-syndrome-grippal.ipynb index 59d72b5b58a3ae26346460dd39e62a39c55243d7..aedbf6efe963fb87c1f1644888fe648aaa7fab9b 100644 --- a/module3/exo1/analyse-syndrome-grippal.ipynb +++ b/module3/exo1/analyse-syndrome-grippal.ipynb @@ -9,7 +9,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "metadata": {}, "outputs": [], "source": [ @@ -28,13 +28,11 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": true - }, + "execution_count": 4, + "metadata": {}, "outputs": [], "source": [ - "data_url = \"http://www.sentiweb.fr/datasets/incidence-PAY-3.csv\"" + "data_url = \"https://www.sentiweb.fr/datasets/incidence-PAY-3.csv\"" ] }, { @@ -61,9 +59,976 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_name
020210632381618867.028765.03629.043.0FRFrance
120210532249118436.026546.03428.040.0FRFrance
220210432580421491.030117.03932.046.0FRFrance
320210332181017894.025726.03327.039.0FRFrance
420210231732013906.020734.02621.031.0FRFrance
520210132179917778.025820.03327.039.0FRFrance
620205332122016498.025942.03225.039.0FRFrance
720205231642812285.020571.02519.031.0FRFrance
820205132161917370.025868.03327.039.0FRFrance
920205031684513220.020470.02620.032.0FRFrance
102020493129399923.015955.02015.025.0FRFrance
1120204831380410641.016967.02116.026.0FRFrance
1220204731908515285.022885.02923.035.0FRFrance
1320204632480120503.029099.03831.045.0FRFrance
1420204534251636857.048175.06556.074.0FRFrance
1520204434456738521.050613.06859.077.0FRFrance
1620204334373737523.049951.06657.075.0FRFrance
1720204233514529812.040478.05345.061.0FRFrance
1820204132787723206.032548.04235.049.0FRFrance
1920204032044316381.024505.03125.037.0FRFrance
2020203931981015900.023720.03024.036.0FRFrance
2120203832556221142.029982.03932.046.0FRFrance
2220203731848514649.022321.02822.034.0FRFrance
232020363103907646.013134.01612.020.0FRFrance
24202035399186842.012994.01510.020.0FRFrance
25202034360843090.09078.094.014.0FRFrance
26202033361063411.08801.095.013.0FRFrance
27202032359183330.08506.095.013.0FRFrance
28202031343512269.06433.074.010.0FRFrance
29202030381795442.010916.0128.016.0FRFrance
.................................
186419852132609619621.032571.04735.059.0FRFrance
186519852032789620885.034907.05138.064.0FRFrance
186619851934315432821.053487.07859.097.0FRFrance
186719851834055529935.051175.07455.093.0FRFrance
186819851733405324366.043740.06244.080.0FRFrance
186919851635036236451.064273.09166.0116.0FRFrance
187019851536388145538.082224.011683.0149.0FRFrance
18711985143134545114400.0154690.0244207.0281.0FRFrance
18721985133197206176080.0218332.0357319.0395.0FRFrance
18731985123245240223304.0267176.0445405.0485.0FRFrance
18741985113276205252399.0300011.0501458.0544.0FRFrance
18751985103353231326279.0380183.0640591.0689.0FRFrance
18761985093369895341109.0398681.0670618.0722.0FRFrance
18771985083389886359529.0420243.0707652.0762.0FRFrance
18781985073471852432599.0511105.0855784.0926.0FRFrance
18791985063565825518011.0613639.01026939.01113.0FRFrance
18801985053637302592795.0681809.011551074.01236.0FRFrance
18811985043424937390794.0459080.0770708.0832.0FRFrance
18821985033213901174689.0253113.0388317.0459.0FRFrance
188319850239758680949.0114223.0177147.0207.0FRFrance
188419850138548965918.0105060.0155120.0190.0FRFrance
188519845238483060602.0109058.0154110.0198.0FRFrance
1886198451310172680242.0123210.0185146.0224.0FRFrance
18871984503123680101401.0145959.0225184.0266.0FRFrance
1888198449310107381684.0120462.0184149.0219.0FRFrance
188919844837862060634.096606.0143110.0176.0FRFrance
189019844737202954274.089784.013199.0163.0FRFrance
189119844638733067686.0106974.0159123.0195.0FRFrance
18921984453135223101414.0169032.0246184.0308.0FRFrance
189319844436842220056.0116788.012537.0213.0FRFrance
\n", + "

1894 rows × 10 columns

\n", + "
" + ], + "text/plain": [ + " week indicator inc inc_low inc_up inc100 inc100_low \\\n", + "0 202106 3 23816 18867.0 28765.0 36 29.0 \n", + "1 202105 3 22491 18436.0 26546.0 34 28.0 \n", + "2 202104 3 25804 21491.0 30117.0 39 32.0 \n", + "3 202103 3 21810 17894.0 25726.0 33 27.0 \n", + "4 202102 3 17320 13906.0 20734.0 26 21.0 \n", + "5 202101 3 21799 17778.0 25820.0 33 27.0 \n", + "6 202053 3 21220 16498.0 25942.0 32 25.0 \n", + "7 202052 3 16428 12285.0 20571.0 25 19.0 \n", + "8 202051 3 21619 17370.0 25868.0 33 27.0 \n", + "9 202050 3 16845 13220.0 20470.0 26 20.0 \n", + "10 202049 3 12939 9923.0 15955.0 20 15.0 \n", + "11 202048 3 13804 10641.0 16967.0 21 16.0 \n", + "12 202047 3 19085 15285.0 22885.0 29 23.0 \n", + "13 202046 3 24801 20503.0 29099.0 38 31.0 \n", + "14 202045 3 42516 36857.0 48175.0 65 56.0 \n", + "15 202044 3 44567 38521.0 50613.0 68 59.0 \n", + "16 202043 3 43737 37523.0 49951.0 66 57.0 \n", + "17 202042 3 35145 29812.0 40478.0 53 45.0 \n", + "18 202041 3 27877 23206.0 32548.0 42 35.0 \n", + "19 202040 3 20443 16381.0 24505.0 31 25.0 \n", + "20 202039 3 19810 15900.0 23720.0 30 24.0 \n", + "21 202038 3 25562 21142.0 29982.0 39 32.0 \n", + "22 202037 3 18485 14649.0 22321.0 28 22.0 \n", + "23 202036 3 10390 7646.0 13134.0 16 12.0 \n", + "24 202035 3 9918 6842.0 12994.0 15 10.0 \n", + "25 202034 3 6084 3090.0 9078.0 9 4.0 \n", + "26 202033 3 6106 3411.0 8801.0 9 5.0 \n", + "27 202032 3 5918 3330.0 8506.0 9 5.0 \n", + "28 202031 3 4351 2269.0 6433.0 7 4.0 \n", + "29 202030 3 8179 5442.0 10916.0 12 8.0 \n", + "... ... ... ... ... ... ... ... \n", + "1864 198521 3 26096 19621.0 32571.0 47 35.0 \n", + "1865 198520 3 27896 20885.0 34907.0 51 38.0 \n", + "1866 198519 3 43154 32821.0 53487.0 78 59.0 \n", + "1867 198518 3 40555 29935.0 51175.0 74 55.0 \n", + "1868 198517 3 34053 24366.0 43740.0 62 44.0 \n", + "1869 198516 3 50362 36451.0 64273.0 91 66.0 \n", + "1870 198515 3 63881 45538.0 82224.0 116 83.0 \n", + "1871 198514 3 134545 114400.0 154690.0 244 207.0 \n", + "1872 198513 3 197206 176080.0 218332.0 357 319.0 \n", + "1873 198512 3 245240 223304.0 267176.0 445 405.0 \n", + "1874 198511 3 276205 252399.0 300011.0 501 458.0 \n", + "1875 198510 3 353231 326279.0 380183.0 640 591.0 \n", + "1876 198509 3 369895 341109.0 398681.0 670 618.0 \n", + "1877 198508 3 389886 359529.0 420243.0 707 652.0 \n", + "1878 198507 3 471852 432599.0 511105.0 855 784.0 \n", + "1879 198506 3 565825 518011.0 613639.0 1026 939.0 \n", + "1880 198505 3 637302 592795.0 681809.0 1155 1074.0 \n", + "1881 198504 3 424937 390794.0 459080.0 770 708.0 \n", + "1882 198503 3 213901 174689.0 253113.0 388 317.0 \n", + "1883 198502 3 97586 80949.0 114223.0 177 147.0 \n", + "1884 198501 3 85489 65918.0 105060.0 155 120.0 \n", + "1885 198452 3 84830 60602.0 109058.0 154 110.0 \n", + "1886 198451 3 101726 80242.0 123210.0 185 146.0 \n", + "1887 198450 3 123680 101401.0 145959.0 225 184.0 \n", + "1888 198449 3 101073 81684.0 120462.0 184 149.0 \n", + "1889 198448 3 78620 60634.0 96606.0 143 110.0 \n", + "1890 198447 3 72029 54274.0 89784.0 131 99.0 \n", + "1891 198446 3 87330 67686.0 106974.0 159 123.0 \n", + "1892 198445 3 135223 101414.0 169032.0 246 184.0 \n", + "1893 198444 3 68422 20056.0 116788.0 125 37.0 \n", + "\n", + " inc100_up geo_insee geo_name \n", + "0 43.0 FR France \n", + "1 40.0 FR France \n", + "2 46.0 FR France \n", + "3 39.0 FR France \n", + "4 31.0 FR France \n", + "5 39.0 FR France \n", + "6 39.0 FR France \n", + "7 31.0 FR France \n", + "8 39.0 FR France \n", + "9 32.0 FR France \n", + "10 25.0 FR France \n", + "11 26.0 FR France \n", + "12 35.0 FR France \n", + "13 45.0 FR France \n", + "14 74.0 FR France \n", + "15 77.0 FR France \n", + "16 75.0 FR France \n", + "17 61.0 FR France \n", + "18 49.0 FR France \n", + "19 37.0 FR France \n", + "20 36.0 FR France \n", + "21 46.0 FR France \n", + "22 34.0 FR France \n", + "23 20.0 FR France \n", + "24 20.0 FR France \n", + "25 14.0 FR France \n", + "26 13.0 FR France \n", + "27 13.0 FR France \n", + "28 10.0 FR France \n", + "29 16.0 FR France \n", + "... ... ... ... \n", + "1864 59.0 FR France \n", + "1865 64.0 FR France \n", + "1866 97.0 FR France \n", + "1867 93.0 FR France \n", + "1868 80.0 FR France \n", + "1869 116.0 FR France \n", + "1870 149.0 FR France \n", + "1871 281.0 FR France \n", + "1872 395.0 FR France \n", + "1873 485.0 FR France \n", + "1874 544.0 FR France \n", + "1875 689.0 FR France \n", + "1876 722.0 FR France \n", + "1877 762.0 FR France \n", + "1878 926.0 FR France \n", + "1879 1113.0 FR France \n", + "1880 1236.0 FR France \n", + "1881 832.0 FR France \n", + "1882 459.0 FR France \n", + "1883 207.0 FR France \n", + "1884 190.0 FR France \n", + "1885 198.0 FR France \n", + "1886 224.0 FR France \n", + "1887 266.0 FR France \n", + "1888 219.0 FR France \n", + "1889 176.0 FR France \n", + "1890 163.0 FR France \n", + "1891 195.0 FR France \n", + "1892 308.0 FR France \n", + "1893 213.0 FR France \n", + "\n", + "[1894 rows x 10 columns]" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "raw_data = pd.read_csv(data_url, skiprows=1)\n", "raw_data" @@ -78,9 +1043,73 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_name
165719891930NaNNaN0NaNNaNFRFrance
\n", + "
" + ], + "text/plain": [ + " week indicator inc inc_low inc_up inc100 inc100_low inc100_up \\\n", + "1657 198919 3 0 NaN NaN 0 NaN NaN \n", + "\n", + " geo_insee geo_name \n", + "1657 FR France " + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "raw_data[raw_data.isnull().any(axis=1)]" ] @@ -94,9 +1123,976 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 7, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_name
020210632381618867.028765.03629.043.0FRFrance
120210532249118436.026546.03428.040.0FRFrance
220210432580421491.030117.03932.046.0FRFrance
320210332181017894.025726.03327.039.0FRFrance
420210231732013906.020734.02621.031.0FRFrance
520210132179917778.025820.03327.039.0FRFrance
620205332122016498.025942.03225.039.0FRFrance
720205231642812285.020571.02519.031.0FRFrance
820205132161917370.025868.03327.039.0FRFrance
920205031684513220.020470.02620.032.0FRFrance
102020493129399923.015955.02015.025.0FRFrance
1120204831380410641.016967.02116.026.0FRFrance
1220204731908515285.022885.02923.035.0FRFrance
1320204632480120503.029099.03831.045.0FRFrance
1420204534251636857.048175.06556.074.0FRFrance
1520204434456738521.050613.06859.077.0FRFrance
1620204334373737523.049951.06657.075.0FRFrance
1720204233514529812.040478.05345.061.0FRFrance
1820204132787723206.032548.04235.049.0FRFrance
1920204032044316381.024505.03125.037.0FRFrance
2020203931981015900.023720.03024.036.0FRFrance
2120203832556221142.029982.03932.046.0FRFrance
2220203731848514649.022321.02822.034.0FRFrance
232020363103907646.013134.01612.020.0FRFrance
24202035399186842.012994.01510.020.0FRFrance
25202034360843090.09078.094.014.0FRFrance
26202033361063411.08801.095.013.0FRFrance
27202032359183330.08506.095.013.0FRFrance
28202031343512269.06433.074.010.0FRFrance
29202030381795442.010916.0128.016.0FRFrance
.................................
186419852132609619621.032571.04735.059.0FRFrance
186519852032789620885.034907.05138.064.0FRFrance
186619851934315432821.053487.07859.097.0FRFrance
186719851834055529935.051175.07455.093.0FRFrance
186819851733405324366.043740.06244.080.0FRFrance
186919851635036236451.064273.09166.0116.0FRFrance
187019851536388145538.082224.011683.0149.0FRFrance
18711985143134545114400.0154690.0244207.0281.0FRFrance
18721985133197206176080.0218332.0357319.0395.0FRFrance
18731985123245240223304.0267176.0445405.0485.0FRFrance
18741985113276205252399.0300011.0501458.0544.0FRFrance
18751985103353231326279.0380183.0640591.0689.0FRFrance
18761985093369895341109.0398681.0670618.0722.0FRFrance
18771985083389886359529.0420243.0707652.0762.0FRFrance
18781985073471852432599.0511105.0855784.0926.0FRFrance
18791985063565825518011.0613639.01026939.01113.0FRFrance
18801985053637302592795.0681809.011551074.01236.0FRFrance
18811985043424937390794.0459080.0770708.0832.0FRFrance
18821985033213901174689.0253113.0388317.0459.0FRFrance
188319850239758680949.0114223.0177147.0207.0FRFrance
188419850138548965918.0105060.0155120.0190.0FRFrance
188519845238483060602.0109058.0154110.0198.0FRFrance
1886198451310172680242.0123210.0185146.0224.0FRFrance
18871984503123680101401.0145959.0225184.0266.0FRFrance
1888198449310107381684.0120462.0184149.0219.0FRFrance
188919844837862060634.096606.0143110.0176.0FRFrance
189019844737202954274.089784.013199.0163.0FRFrance
189119844638733067686.0106974.0159123.0195.0FRFrance
18921984453135223101414.0169032.0246184.0308.0FRFrance
189319844436842220056.0116788.012537.0213.0FRFrance
\n", + "

1893 rows × 10 columns

\n", + "
" + ], + "text/plain": [ + " week indicator inc inc_low inc_up inc100 inc100_low \\\n", + "0 202106 3 23816 18867.0 28765.0 36 29.0 \n", + "1 202105 3 22491 18436.0 26546.0 34 28.0 \n", + "2 202104 3 25804 21491.0 30117.0 39 32.0 \n", + "3 202103 3 21810 17894.0 25726.0 33 27.0 \n", + "4 202102 3 17320 13906.0 20734.0 26 21.0 \n", + "5 202101 3 21799 17778.0 25820.0 33 27.0 \n", + "6 202053 3 21220 16498.0 25942.0 32 25.0 \n", + "7 202052 3 16428 12285.0 20571.0 25 19.0 \n", + "8 202051 3 21619 17370.0 25868.0 33 27.0 \n", + "9 202050 3 16845 13220.0 20470.0 26 20.0 \n", + "10 202049 3 12939 9923.0 15955.0 20 15.0 \n", + "11 202048 3 13804 10641.0 16967.0 21 16.0 \n", + "12 202047 3 19085 15285.0 22885.0 29 23.0 \n", + "13 202046 3 24801 20503.0 29099.0 38 31.0 \n", + "14 202045 3 42516 36857.0 48175.0 65 56.0 \n", + "15 202044 3 44567 38521.0 50613.0 68 59.0 \n", + "16 202043 3 43737 37523.0 49951.0 66 57.0 \n", + "17 202042 3 35145 29812.0 40478.0 53 45.0 \n", + "18 202041 3 27877 23206.0 32548.0 42 35.0 \n", + "19 202040 3 20443 16381.0 24505.0 31 25.0 \n", + "20 202039 3 19810 15900.0 23720.0 30 24.0 \n", + "21 202038 3 25562 21142.0 29982.0 39 32.0 \n", + "22 202037 3 18485 14649.0 22321.0 28 22.0 \n", + "23 202036 3 10390 7646.0 13134.0 16 12.0 \n", + "24 202035 3 9918 6842.0 12994.0 15 10.0 \n", + "25 202034 3 6084 3090.0 9078.0 9 4.0 \n", + "26 202033 3 6106 3411.0 8801.0 9 5.0 \n", + "27 202032 3 5918 3330.0 8506.0 9 5.0 \n", + "28 202031 3 4351 2269.0 6433.0 7 4.0 \n", + "29 202030 3 8179 5442.0 10916.0 12 8.0 \n", + "... ... ... ... ... ... ... ... \n", + "1864 198521 3 26096 19621.0 32571.0 47 35.0 \n", + "1865 198520 3 27896 20885.0 34907.0 51 38.0 \n", + "1866 198519 3 43154 32821.0 53487.0 78 59.0 \n", + "1867 198518 3 40555 29935.0 51175.0 74 55.0 \n", + "1868 198517 3 34053 24366.0 43740.0 62 44.0 \n", + "1869 198516 3 50362 36451.0 64273.0 91 66.0 \n", + "1870 198515 3 63881 45538.0 82224.0 116 83.0 \n", + "1871 198514 3 134545 114400.0 154690.0 244 207.0 \n", + "1872 198513 3 197206 176080.0 218332.0 357 319.0 \n", + "1873 198512 3 245240 223304.0 267176.0 445 405.0 \n", + "1874 198511 3 276205 252399.0 300011.0 501 458.0 \n", + "1875 198510 3 353231 326279.0 380183.0 640 591.0 \n", + "1876 198509 3 369895 341109.0 398681.0 670 618.0 \n", + "1877 198508 3 389886 359529.0 420243.0 707 652.0 \n", + "1878 198507 3 471852 432599.0 511105.0 855 784.0 \n", + "1879 198506 3 565825 518011.0 613639.0 1026 939.0 \n", + "1880 198505 3 637302 592795.0 681809.0 1155 1074.0 \n", + "1881 198504 3 424937 390794.0 459080.0 770 708.0 \n", + "1882 198503 3 213901 174689.0 253113.0 388 317.0 \n", + "1883 198502 3 97586 80949.0 114223.0 177 147.0 \n", + "1884 198501 3 85489 65918.0 105060.0 155 120.0 \n", + "1885 198452 3 84830 60602.0 109058.0 154 110.0 \n", + "1886 198451 3 101726 80242.0 123210.0 185 146.0 \n", + "1887 198450 3 123680 101401.0 145959.0 225 184.0 \n", + "1888 198449 3 101073 81684.0 120462.0 184 149.0 \n", + "1889 198448 3 78620 60634.0 96606.0 143 110.0 \n", + "1890 198447 3 72029 54274.0 89784.0 131 99.0 \n", + "1891 198446 3 87330 67686.0 106974.0 159 123.0 \n", + "1892 198445 3 135223 101414.0 169032.0 246 184.0 \n", + "1893 198444 3 68422 20056.0 116788.0 125 37.0 \n", + "\n", + " inc100_up geo_insee geo_name \n", + "0 43.0 FR France \n", + "1 40.0 FR France \n", + "2 46.0 FR France \n", + "3 39.0 FR France \n", + "4 31.0 FR France \n", + "5 39.0 FR France \n", + "6 39.0 FR France \n", + "7 31.0 FR France \n", + "8 39.0 FR France \n", + "9 32.0 FR France \n", + "10 25.0 FR France \n", + "11 26.0 FR France \n", + "12 35.0 FR France \n", + "13 45.0 FR France \n", + "14 74.0 FR France \n", + "15 77.0 FR France \n", + "16 75.0 FR France \n", + "17 61.0 FR France \n", + "18 49.0 FR France \n", + "19 37.0 FR France \n", + "20 36.0 FR France \n", + "21 46.0 FR France \n", + "22 34.0 FR France \n", + "23 20.0 FR France \n", + "24 20.0 FR France \n", + "25 14.0 FR France \n", + "26 13.0 FR France \n", + "27 13.0 FR France \n", + "28 10.0 FR France \n", + "29 16.0 FR France \n", + "... ... ... ... \n", + "1864 59.0 FR France \n", + "1865 64.0 FR France \n", + "1866 97.0 FR France \n", + "1867 93.0 FR France \n", + "1868 80.0 FR France \n", + "1869 116.0 FR France \n", + "1870 149.0 FR France \n", + "1871 281.0 FR France \n", + "1872 395.0 FR France \n", + "1873 485.0 FR France \n", + "1874 544.0 FR France \n", + "1875 689.0 FR France \n", + "1876 722.0 FR France \n", + "1877 762.0 FR France \n", + "1878 926.0 FR France \n", + "1879 1113.0 FR France \n", + "1880 1236.0 FR France \n", + "1881 832.0 FR France \n", + "1882 459.0 FR France \n", + "1883 207.0 FR France \n", + "1884 190.0 FR France \n", + "1885 198.0 FR France \n", + "1886 224.0 FR France \n", + "1887 266.0 FR France \n", + "1888 219.0 FR France \n", + "1889 176.0 FR France \n", + "1890 163.0 FR France \n", + "1891 195.0 FR France \n", + "1892 308.0 FR France \n", + "1893 213.0 FR France \n", + "\n", + "[1893 rows x 10 columns]" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "data = raw_data.dropna().copy()\n", "data" @@ -122,7 +2118,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 8, "metadata": {}, "outputs": [], "source": [ @@ -152,10 +2148,8 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": true - }, + "execution_count": 9, + "metadata": {}, "outputs": [], "source": [ "sorted_data = data.set_index('period').sort_index()" @@ -179,9 +2173,17 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 10, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "1989-05-01/1989-05-07 1989-05-15/1989-05-21\n" + ] + } + ], "source": [ "periods = sorted_data.index\n", "for p1, p2 in zip(periods[:-1], periods[1:]):\n", @@ -199,9 +2201,32 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 11, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": "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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], "source": [ "sorted_data['inc'].plot()" ] @@ -215,9 +2240,32 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 12, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": "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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], "source": [ "sorted_data['inc'][-200:].plot()" ] @@ -252,10 +2300,8 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": true - }, + "execution_count": 13, + "metadata": {}, "outputs": [], "source": [ "first_august_week = [pd.Period(pd.Timestamp(y, 8, 1), 'W')\n", @@ -274,7 +2320,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 14, "metadata": {}, "outputs": [], "source": [ @@ -298,9 +2344,32 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 15, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": "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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], "source": [ "yearly_incidence.plot(style='*')" ] @@ -314,9 +2383,55 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 16, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "2014 1600941\n", + "1991 1659249\n", + "1995 1840410\n", + "2020 2042389\n", + "2012 2175217\n", + "2003 2234584\n", + "2019 2254386\n", + "2006 2307352\n", + "2017 2321583\n", + "2001 2529279\n", + "1992 2574578\n", + "1993 2703886\n", + "2018 2705325\n", + "1988 2765617\n", + "2007 2780164\n", + "1987 2855570\n", + "2016 2856393\n", + "2011 2857040\n", + "2008 2973918\n", + "1998 3034904\n", + "2002 3125418\n", + "2009 3444020\n", + "1994 3514763\n", + "1996 3539413\n", + "2004 3567744\n", + "1997 3620066\n", + "2015 3654892\n", + "2000 3826372\n", + "2005 3835025\n", + "1999 3908112\n", + "2010 4111392\n", + "2013 4182691\n", + "1986 5115251\n", + "1990 5235827\n", + "1989 5466192\n", + "dtype: int64" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "yearly_incidence.sort_values()" ] @@ -331,9 +2446,32 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 17, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": "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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], "source": [ "yearly_incidence.hist(xrot=20)" ] @@ -364,7 +2502,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.1" + "version": "3.6.4" } }, "nbformat": 4,