diff --git a/module3/exo1/influenza-like-illness-analysis.ipynb b/module3/exo1/influenza-like-illness-analysis.ipynb index 152f4644a6d49c50a858ce496adc85d65c230756..d45f16ad9fcd60457f7eaaf5657f00177fdd3523 100644 --- a/module3/exo1/influenza-like-illness-analysis.ipynb +++ b/module3/exo1/influenza-like-illness-analysis.ipynb @@ -9,10 +9,8 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": true - }, + "execution_count": 1, + "metadata": {}, "outputs": [], "source": [ "%matplotlib inline\n", @@ -30,10 +28,8 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": true - }, + "execution_count": 2, + "metadata": {}, "outputs": [], "source": [ "data_url = \"http://www.sentiweb.fr/datasets/incidence-PAY-3.csv\"" @@ -63,9 +59,976 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
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weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_name
020230937172962525.080933.010894.0122.0FRFrance
120230837709068677.085503.0116103.0129.0FRFrance
220230738985180397.099305.0135121.0149.0FRFrance
320230639736887636.0107100.0146131.0161.0FRFrance
420230539546986268.0104670.0144130.0158.0FRFrance
520230437490166916.082886.0113101.0125.0FRFrance
620230336957061893.077247.010593.0117.0FRFrance
720230237826070090.086430.0118106.0130.0FRFrance
82023013121773111024.0132522.0183167.0199.0FRFrance
92022523155383142015.0168751.0234214.0254.0FRFrance
102022513248311232120.0264502.0374350.0398.0FRFrance
112022503234279219533.0249025.0353331.0375.0FRFrance
122022493163421151727.0175115.0246228.0264.0FRFrance
132022483121884111932.0131836.0184169.0199.0FRFrance
1420224739644787259.0105635.0145131.0159.0FRFrance
1520224636773560075.075395.010290.0114.0FRFrance
1620224534530638909.051703.06858.078.0FRFrance
1720224433471328880.040546.05243.061.0FRFrance
1820224334476936884.052654.06856.080.0FRFrance
1920224234746240773.054151.07262.082.0FRFrance
2020224134858342388.054778.07364.082.0FRFrance
2120224034192736115.047739.06354.072.0FRFrance
2220223933990234168.045636.06051.069.0FRFrance
2320223832878123733.033829.04335.051.0FRFrance
2420223732139517076.025714.03225.039.0FRFrance
2520223631412010487.017753.02116.026.0FRFrance
26202235392836485.012081.01410.018.0FRFrance
27202234374984731.010265.0117.015.0FRFrance
28202233375864442.010730.0116.016.0FRFrance
292022323122227749.016695.01811.025.0FRFrance
.................................
197119852132609619621.032571.04735.059.0FRFrance
197219852032789620885.034907.05138.064.0FRFrance
197319851934315432821.053487.07859.097.0FRFrance
197419851834055529935.051175.07455.093.0FRFrance
197519851733405324366.043740.06244.080.0FRFrance
197619851635036236451.064273.09166.0116.0FRFrance
197719851536388145538.082224.011683.0149.0FRFrance
19781985143134545114400.0154690.0244207.0281.0FRFrance
19791985133197206176080.0218332.0357319.0395.0FRFrance
19801985123245240223304.0267176.0445405.0485.0FRFrance
19811985113276205252399.0300011.0501458.0544.0FRFrance
19821985103353231326279.0380183.0640591.0689.0FRFrance
19831985093369895341109.0398681.0670618.0722.0FRFrance
19841985083389886359529.0420243.0707652.0762.0FRFrance
19851985073471852432599.0511105.0855784.0926.0FRFrance
19861985063565825518011.0613639.01026939.01113.0FRFrance
19871985053637302592795.0681809.011551074.01236.0FRFrance
19881985043424937390794.0459080.0770708.0832.0FRFrance
19891985033213901174689.0253113.0388317.0459.0FRFrance
199019850239758680949.0114223.0177147.0207.0FRFrance
199119850138548965918.0105060.0155120.0190.0FRFrance
199219845238483060602.0109058.0154110.0198.0FRFrance
1993198451310172680242.0123210.0185146.0224.0FRFrance
19941984503123680101401.0145959.0225184.0266.0FRFrance
1995198449310107381684.0120462.0184149.0219.0FRFrance
199619844837862060634.096606.0143110.0176.0FRFrance
199719844737202954274.089784.013199.0163.0FRFrance
199819844638733067686.0106974.0159123.0195.0FRFrance
19991984453135223101414.0169032.0246184.0308.0FRFrance
200019844436842220056.0116788.012537.0213.0FRFrance
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2001 rows × 10 columns

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28880.0 40546.0 52 43.0 \n", + "18 202243 3 44769 36884.0 52654.0 68 56.0 \n", + "19 202242 3 47462 40773.0 54151.0 72 62.0 \n", + "20 202241 3 48583 42388.0 54778.0 73 64.0 \n", + "21 202240 3 41927 36115.0 47739.0 63 54.0 \n", + "22 202239 3 39902 34168.0 45636.0 60 51.0 \n", + "23 202238 3 28781 23733.0 33829.0 43 35.0 \n", + "24 202237 3 21395 17076.0 25714.0 32 25.0 \n", + "25 202236 3 14120 10487.0 17753.0 21 16.0 \n", + "26 202235 3 9283 6485.0 12081.0 14 10.0 \n", + "27 202234 3 7498 4731.0 10265.0 11 7.0 \n", + "28 202233 3 7586 4442.0 10730.0 11 6.0 \n", + "29 202232 3 12222 7749.0 16695.0 18 11.0 \n", + "... ... ... ... ... ... ... ... \n", + "1971 198521 3 26096 19621.0 32571.0 47 35.0 \n", + "1972 198520 3 27896 20885.0 34907.0 51 38.0 \n", + "1973 198519 3 43154 32821.0 53487.0 78 59.0 \n", + "1974 198518 3 40555 29935.0 51175.0 74 55.0 \n", + "1975 198517 3 34053 24366.0 43740.0 62 44.0 \n", + "1976 198516 3 50362 36451.0 64273.0 91 66.0 \n", + "1977 198515 3 63881 45538.0 82224.0 116 83.0 \n", + "1978 198514 3 134545 114400.0 154690.0 244 207.0 \n", + "1979 198513 3 197206 176080.0 218332.0 357 319.0 \n", + "1980 198512 3 245240 223304.0 267176.0 445 405.0 \n", + "1981 198511 3 276205 252399.0 300011.0 501 458.0 \n", + "1982 198510 3 353231 326279.0 380183.0 640 591.0 \n", + "1983 198509 3 369895 341109.0 398681.0 670 618.0 \n", + "1984 198508 3 389886 359529.0 420243.0 707 652.0 \n", + "1985 198507 3 471852 432599.0 511105.0 855 784.0 \n", + "1986 198506 3 565825 518011.0 613639.0 1026 939.0 \n", + "1987 198505 3 637302 592795.0 681809.0 1155 1074.0 \n", + "1988 198504 3 424937 390794.0 459080.0 770 708.0 \n", + "1989 198503 3 213901 174689.0 253113.0 388 317.0 \n", + "1990 198502 3 97586 80949.0 114223.0 177 147.0 \n", + "1991 198501 3 85489 65918.0 105060.0 155 120.0 \n", + "1992 198452 3 84830 60602.0 109058.0 154 110.0 \n", + "1993 198451 3 101726 80242.0 123210.0 185 146.0 \n", + "1994 198450 3 123680 101401.0 145959.0 225 184.0 \n", + "1995 198449 3 101073 81684.0 120462.0 184 149.0 \n", + "1996 198448 3 78620 60634.0 96606.0 143 110.0 \n", + "1997 198447 3 72029 54274.0 89784.0 131 99.0 \n", + "1998 198446 3 87330 67686.0 106974.0 159 123.0 \n", + "1999 198445 3 135223 101414.0 169032.0 246 184.0 \n", + "2000 198444 3 68422 20056.0 116788.0 125 37.0 \n", + "\n", + " inc100_up geo_insee geo_name \n", + "0 122.0 FR France \n", + "1 129.0 FR France \n", + "2 149.0 FR France \n", + "3 161.0 FR France \n", + "4 158.0 FR France \n", + "5 125.0 FR France \n", + "6 117.0 FR France \n", + "7 130.0 FR France \n", + "8 199.0 FR France \n", + "9 254.0 FR France \n", + "10 398.0 FR France \n", + "11 375.0 FR France \n", + "12 264.0 FR France \n", + "13 199.0 FR France \n", + "14 159.0 FR France \n", + "15 114.0 FR France \n", + "16 78.0 FR France \n", + "17 61.0 FR France \n", + "18 80.0 FR France \n", + "19 82.0 FR France \n", + "20 82.0 FR France \n", + "21 72.0 FR France \n", + "22 69.0 FR France \n", + "23 51.0 FR France \n", + "24 39.0 FR France \n", + "25 26.0 FR France \n", + "26 18.0 FR France \n", + "27 15.0 FR France \n", + "28 16.0 FR France \n", + "29 25.0 FR France \n", + "... ... ... ... \n", + "1971 59.0 FR France \n", + "1972 64.0 FR France \n", + "1973 97.0 FR France \n", + "1974 93.0 FR France \n", + "1975 80.0 FR France \n", + "1976 116.0 FR France \n", + "1977 149.0 FR France \n", + "1978 281.0 FR France \n", + "1979 395.0 FR France \n", + "1980 485.0 FR France \n", + "1981 544.0 FR France \n", + "1982 689.0 FR France \n", + "1983 722.0 FR France \n", + "1984 762.0 FR France \n", + "1985 926.0 FR France \n", + "1986 1113.0 FR France \n", + "1987 1236.0 FR France \n", + "1988 832.0 FR France \n", + "1989 459.0 FR France \n", + "1990 207.0 FR France \n", + "1991 190.0 FR France \n", + "1992 198.0 FR France \n", + "1993 224.0 FR France \n", + "1994 266.0 FR France \n", + "1995 219.0 FR France \n", + "1996 176.0 FR France \n", + "1997 163.0 FR France \n", + "1998 195.0 FR France \n", + "1999 308.0 FR France \n", + "2000 213.0 FR France \n", + "\n", + "[2001 rows x 10 columns]" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "raw_data = pd.read_csv(data_url, skiprows=1)\n", "raw_data" @@ -80,9 +1043,73 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
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weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_name
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weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_name
020230937172962525.080933.010894.0122.0FRFrance
120230837709068677.085503.0116103.0129.0FRFrance
220230738985180397.099305.0135121.0149.0FRFrance
320230639736887636.0107100.0146131.0161.0FRFrance
420230539546986268.0104670.0144130.0158.0FRFrance
520230437490166916.082886.0113101.0125.0FRFrance
620230336957061893.077247.010593.0117.0FRFrance
720230237826070090.086430.0118106.0130.0FRFrance
82023013121773111024.0132522.0183167.0199.0FRFrance
92022523155383142015.0168751.0234214.0254.0FRFrance
102022513248311232120.0264502.0374350.0398.0FRFrance
112022503234279219533.0249025.0353331.0375.0FRFrance
122022493163421151727.0175115.0246228.0264.0FRFrance
132022483121884111932.0131836.0184169.0199.0FRFrance
1420224739644787259.0105635.0145131.0159.0FRFrance
1520224636773560075.075395.010290.0114.0FRFrance
1620224534530638909.051703.06858.078.0FRFrance
1720224433471328880.040546.05243.061.0FRFrance
1820224334476936884.052654.06856.080.0FRFrance
1920224234746240773.054151.07262.082.0FRFrance
2020224134858342388.054778.07364.082.0FRFrance
2120224034192736115.047739.06354.072.0FRFrance
2220223933990234168.045636.06051.069.0FRFrance
2320223832878123733.033829.04335.051.0FRFrance
2420223732139517076.025714.03225.039.0FRFrance
2520223631412010487.017753.02116.026.0FRFrance
26202235392836485.012081.01410.018.0FRFrance
27202234374984731.010265.0117.015.0FRFrance
28202233375864442.010730.0116.016.0FRFrance
292022323122227749.016695.01811.025.0FRFrance
.................................
197119852132609619621.032571.04735.059.0FRFrance
197219852032789620885.034907.05138.064.0FRFrance
197319851934315432821.053487.07859.097.0FRFrance
197419851834055529935.051175.07455.093.0FRFrance
197519851733405324366.043740.06244.080.0FRFrance
197619851635036236451.064273.09166.0116.0FRFrance
197719851536388145538.082224.011683.0149.0FRFrance
19781985143134545114400.0154690.0244207.0281.0FRFrance
19791985133197206176080.0218332.0357319.0395.0FRFrance
19801985123245240223304.0267176.0445405.0485.0FRFrance
19811985113276205252399.0300011.0501458.0544.0FRFrance
19821985103353231326279.0380183.0640591.0689.0FRFrance
19831985093369895341109.0398681.0670618.0722.0FRFrance
19841985083389886359529.0420243.0707652.0762.0FRFrance
19851985073471852432599.0511105.0855784.0926.0FRFrance
19861985063565825518011.0613639.01026939.01113.0FRFrance
19871985053637302592795.0681809.011551074.01236.0FRFrance
19881985043424937390794.0459080.0770708.0832.0FRFrance
19891985033213901174689.0253113.0388317.0459.0FRFrance
199019850239758680949.0114223.0177147.0207.0FRFrance
199119850138548965918.0105060.0155120.0190.0FRFrance
199219845238483060602.0109058.0154110.0198.0FRFrance
1993198451310172680242.0123210.0185146.0224.0FRFrance
19941984503123680101401.0145959.0225184.0266.0FRFrance
1995198449310107381684.0120462.0184149.0219.0FRFrance
199619844837862060634.096606.0143110.0176.0FRFrance
199719844737202954274.089784.013199.0163.0FRFrance
199819844638733067686.0106974.0159123.0195.0FRFrance
19991984453135223101414.0169032.0246184.0308.0FRFrance
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2000 rows × 10 columns

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" + ], + "text/plain": [ + " week indicator inc inc_low inc_up inc100 inc100_low \\\n", + "0 202309 3 71729 62525.0 80933.0 108 94.0 \n", + "1 202308 3 77090 68677.0 85503.0 116 103.0 \n", + "2 202307 3 89851 80397.0 99305.0 135 121.0 \n", + "3 202306 3 97368 87636.0 107100.0 146 131.0 \n", + "4 202305 3 95469 86268.0 104670.0 144 130.0 \n", + "5 202304 3 74901 66916.0 82886.0 113 101.0 \n", + "6 202303 3 69570 61893.0 77247.0 105 93.0 \n", + "7 202302 3 78260 70090.0 86430.0 118 106.0 \n", + "8 202301 3 121773 111024.0 132522.0 183 167.0 \n", + "9 202252 3 155383 142015.0 168751.0 234 214.0 \n", + "10 202251 3 248311 232120.0 264502.0 374 350.0 \n", + "11 202250 3 234279 219533.0 249025.0 353 331.0 \n", + "12 202249 3 163421 151727.0 175115.0 246 228.0 \n", + "13 202248 3 121884 111932.0 131836.0 184 169.0 \n", + "14 202247 3 96447 87259.0 105635.0 145 131.0 \n", + "15 202246 3 67735 60075.0 75395.0 102 90.0 \n", + "16 202245 3 45306 38909.0 51703.0 68 58.0 \n", + "17 202244 3 34713 28880.0 40546.0 52 43.0 \n", + "18 202243 3 44769 36884.0 52654.0 68 56.0 \n", + "19 202242 3 47462 40773.0 54151.0 72 62.0 \n", + "20 202241 3 48583 42388.0 54778.0 73 64.0 \n", + "21 202240 3 41927 36115.0 47739.0 63 54.0 \n", + "22 202239 3 39902 34168.0 45636.0 60 51.0 \n", + "23 202238 3 28781 23733.0 33829.0 43 35.0 \n", + "24 202237 3 21395 17076.0 25714.0 32 25.0 \n", + "25 202236 3 14120 10487.0 17753.0 21 16.0 \n", + "26 202235 3 9283 6485.0 12081.0 14 10.0 \n", + "27 202234 3 7498 4731.0 10265.0 11 7.0 \n", + "28 202233 3 7586 4442.0 10730.0 11 6.0 \n", + "29 202232 3 12222 7749.0 16695.0 18 11.0 \n", + "... ... ... ... ... ... ... ... \n", + "1971 198521 3 26096 19621.0 32571.0 47 35.0 \n", + "1972 198520 3 27896 20885.0 34907.0 51 38.0 \n", + "1973 198519 3 43154 32821.0 53487.0 78 59.0 \n", + "1974 198518 3 40555 29935.0 51175.0 74 55.0 \n", + "1975 198517 3 34053 24366.0 43740.0 62 44.0 \n", + "1976 198516 3 50362 36451.0 64273.0 91 66.0 \n", + "1977 198515 3 63881 45538.0 82224.0 116 83.0 \n", + "1978 198514 3 134545 114400.0 154690.0 244 207.0 \n", + "1979 198513 3 197206 176080.0 218332.0 357 319.0 \n", + "1980 198512 3 245240 223304.0 267176.0 445 405.0 \n", + "1981 198511 3 276205 252399.0 300011.0 501 458.0 \n", + "1982 198510 3 353231 326279.0 380183.0 640 591.0 \n", + "1983 198509 3 369895 341109.0 398681.0 670 618.0 \n", + "1984 198508 3 389886 359529.0 420243.0 707 652.0 \n", + "1985 198507 3 471852 432599.0 511105.0 855 784.0 \n", + "1986 198506 3 565825 518011.0 613639.0 1026 939.0 \n", + "1987 198505 3 637302 592795.0 681809.0 1155 1074.0 \n", + "1988 198504 3 424937 390794.0 459080.0 770 708.0 \n", + "1989 198503 3 213901 174689.0 253113.0 388 317.0 \n", + "1990 198502 3 97586 80949.0 114223.0 177 147.0 \n", + "1991 198501 3 85489 65918.0 105060.0 155 120.0 \n", + "1992 198452 3 84830 60602.0 109058.0 154 110.0 \n", + "1993 198451 3 101726 80242.0 123210.0 185 146.0 \n", + "1994 198450 3 123680 101401.0 145959.0 225 184.0 \n", + "1995 198449 3 101073 81684.0 120462.0 184 149.0 \n", + "1996 198448 3 78620 60634.0 96606.0 143 110.0 \n", + "1997 198447 3 72029 54274.0 89784.0 131 99.0 \n", + "1998 198446 3 87330 67686.0 106974.0 159 123.0 \n", + "1999 198445 3 135223 101414.0 169032.0 246 184.0 \n", + "2000 198444 3 68422 20056.0 116788.0 125 37.0 \n", + "\n", + " inc100_up geo_insee geo_name \n", + "0 122.0 FR France \n", + "1 129.0 FR France \n", + "2 149.0 FR France \n", + "3 161.0 FR France \n", + "4 158.0 FR France \n", + "5 125.0 FR France \n", + "6 117.0 FR France \n", + "7 130.0 FR France \n", + "8 199.0 FR France \n", + "9 254.0 FR France \n", + "10 398.0 FR France \n", + "11 375.0 FR France \n", + "12 264.0 FR France \n", + "13 199.0 FR France \n", + "14 159.0 FR France \n", + "15 114.0 FR France \n", + "16 78.0 FR France \n", + "17 61.0 FR France \n", + "18 80.0 FR France \n", + "19 82.0 FR France \n", + "20 82.0 FR France \n", + "21 72.0 FR France \n", + "22 69.0 FR France \n", + "23 51.0 FR France \n", + "24 39.0 FR France \n", + "25 26.0 FR France \n", + "26 18.0 FR France \n", + "27 15.0 FR France \n", + "28 16.0 FR France \n", + "29 25.0 FR France \n", + "... ... ... ... \n", + "1971 59.0 FR France \n", + "1972 64.0 FR France \n", + "1973 97.0 FR France \n", + "1974 93.0 FR France \n", + "1975 80.0 FR France \n", + "1976 116.0 FR France \n", + "1977 149.0 FR France \n", + "1978 281.0 FR France \n", + "1979 395.0 FR France \n", + "1980 485.0 FR France \n", + "1981 544.0 FR France \n", + "1982 689.0 FR France \n", + "1983 722.0 FR France \n", + "1984 762.0 FR France \n", + "1985 926.0 FR France \n", + "1986 1113.0 FR France \n", + "1987 1236.0 FR France \n", + "1988 832.0 FR France \n", + "1989 459.0 FR France \n", + "1990 207.0 FR France \n", + "1991 190.0 FR France \n", + "1992 198.0 FR France \n", + "1993 224.0 FR France \n", + "1994 266.0 FR France \n", + "1995 219.0 FR France \n", + "1996 176.0 FR France \n", + "1997 163.0 FR France \n", + "1998 195.0 FR France \n", + "1999 308.0 FR France \n", + "2000 213.0 FR France \n", + "\n", + "[2000 rows x 10 columns]" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "data = raw_data.dropna().copy()\n", "data" @@ -123,10 +2117,8 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": true - }, + "execution_count": 6, + "metadata": {}, "outputs": [], "source": [ "def convert_week(year_and_week_int):\n", @@ -154,10 +2146,8 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": true - }, + "execution_count": 7, + "metadata": {}, "outputs": [], "source": [ "sorted_data = data.set_index('period').sort_index()" @@ -180,9 +2170,17 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 8, "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", @@ -200,9 +2198,32 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 9, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 9, + "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()" ] @@ -251,10 +2295,8 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": true - }, + "execution_count": 11, + "metadata": {}, "outputs": [], "source": [ "first_august_week = [pd.Period(pd.Timestamp(y, 8, 1), 'W')\n", @@ -273,10 +2315,8 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": true - }, + "execution_count": 12, + "metadata": {}, "outputs": [], "source": [ "year = []\n", @@ -299,9 +2339,32 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 13, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 13, + "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='*')" ] @@ -315,9 +2378,57 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 14, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "2021 743449\n", + "2014 1600941\n", + "1991 1659249\n", + "1995 1840410\n", + "2020 2010315\n", + "2022 2060360\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": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "yearly_incidence.sort_values()" ] @@ -330,23 +2441,71 @@ "but are rare: there were three of them in the course of 35 years. The typical epidemic affects only half as many people." ] }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "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.hist(xrot=20)" + ] + }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ - "yearly_incidence.hist(xrot=20)" + "# Define the name of the local file\n", + "local_data_file = \"incidence-PAY-3.csv\"" ] }, { "cell_type": "code", "execution_count": null, - "metadata": { - "collapsed": true - }, + "metadata": {}, "outputs": [], - "source": [] + "source": [ + "# Check if the local file exists\n", + "if not os.path.isfile(local_data_file):\n", + " # If the local file does not exist, download the data from the remote URL\n", + " response = requests.get(remote_data_url)\n", + " with open(local_data_file, \"w\") as f:\n", + " f.write(response.text)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Read the data from the local file into a Pandas DataFrame\n", + "raw_data = pd.read_csv(local_data_file, skiprows=1)" + ] } ], "metadata": {