diff --git a/module3/exo1/analyse-syndrome-grippal.ipynb b/module3/exo1/analyse-syndrome-grippal.ipynb index b49bc272c5a0beb7d3867a98aa64929d15efe58e..3c1a85d30bddcadb8098e2ddc3c4d23a83e8bc0f 100644 --- a/module3/exo1/analyse-syndrome-grippal.ipynb +++ b/module3/exo1/analyse-syndrome-grippal.ipynb @@ -9,7 +9,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 23, "metadata": {}, "outputs": [], "source": [ @@ -61,35 +61,983 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 24, "metadata": {}, "outputs": [], "source": [ - "data_csv_path = \"inc-3-PAY-ds2.csv\"" + "data_csv_path = \"inc-3-PAY.csv\"" ] }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 25, "metadata": {}, "outputs": [ { - "ename": "FileNotFoundError", - "evalue": "File b'inc-3-PAY-ds2.csv' does not exist", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mFileNotFoundError\u001b[0m Traceback (most recent call last)", - "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mraw_data\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread_csv\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata_csv_path\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mskiprows\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2\u001b[0m \u001b[0mraw_data\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36mparser_f\u001b[0;34m(filepath_or_buffer, sep, delimiter, header, names, index_col, usecols, squeeze, prefix, mangle_dupe_cols, dtype, engine, converters, true_values, false_values, skipinitialspace, skiprows, nrows, na_values, keep_default_na, na_filter, verbose, skip_blank_lines, parse_dates, infer_datetime_format, keep_date_col, date_parser, dayfirst, iterator, chunksize, compression, thousands, decimal, lineterminator, quotechar, quoting, escapechar, comment, encoding, dialect, tupleize_cols, error_bad_lines, warn_bad_lines, skipfooter, skip_footer, doublequote, delim_whitespace, as_recarray, compact_ints, use_unsigned, low_memory, buffer_lines, memory_map, float_precision)\u001b[0m\n\u001b[1;32m 707\u001b[0m skip_blank_lines=skip_blank_lines)\n\u001b[1;32m 708\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 709\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0m_read\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfilepath_or_buffer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 710\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 711\u001b[0m \u001b[0mparser_f\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__name__\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - 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weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_name
020244335495646518.063394.08269.095.0FRFrance
120244236832860465.076191.010290.0114.0FRFrance
220244137943571386.087484.0119107.0131.0FRFrance
320244038496576555.093375.0127114.0140.0FRFrance
420243939166082937.0100383.0137124.0150.0FRFrance
520243839178682903.0100669.0138125.0151.0FRFrance
620243735646049319.063601.08574.096.0FRFrance
720243633365727906.039408.05041.059.0FRFrance
820243532740422036.032772.04133.049.0FRFrance
920243432671721003.032431.04031.049.0FRFrance
1020243332062315349.025897.03123.039.0FRFrance
1120243232318717532.028842.03527.043.0FRFrance
1220243132603520267.031803.03930.048.0FRFrance
1320243033639328593.044193.05543.067.0FRFrance
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1620242734736440234.054494.07160.082.0FRFrance
1720242634421936956.051482.06655.077.0FRFrance
1820242534720440300.054108.07161.081.0FRFrance
1920242434111034671.047549.06252.072.0FRFrance
2020242333587530610.041140.05446.062.0FRFrance
2120242233377228274.039270.05143.059.0FRFrance
2220242132196317556.026370.03326.040.0FRFrance
2320242032005715780.024334.03024.036.0FRFrance
2420241931537511274.019476.02317.029.0FRFrance
2520241832240917653.027165.03427.041.0FRFrance
2620241732704221410.032674.04133.049.0FRFrance
2720241632888223305.034459.04335.051.0FRFrance
2820241533022924648.035810.04537.053.0FRFrance
2920241433181326529.037097.04840.056.0FRFrance
.................................
205719852132609619621.032571.04735.059.0FRFrance
205819852032789620885.034907.05138.064.0FRFrance
205919851934315432821.053487.07859.097.0FRFrance
206019851834055529935.051175.07455.093.0FRFrance
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206219851635036236451.064273.09166.0116.0FRFrance
206319851536388145538.082224.011683.0149.0FRFrance
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20651985133197206176080.0218332.0357319.0395.0FRFrance
20661985123245240223304.0267176.0445405.0485.0FRFrance
20671985113276205252399.0300011.0501458.0544.0FRFrance
20681985103353231326279.0380183.0640591.0689.0FRFrance
20691985093369895341109.0398681.0670618.0722.0FRFrance
20701985083389886359529.0420243.0707652.0762.0FRFrance
20711985073471852432599.0511105.0855784.0926.0FRFrance
20721985063565825518011.0613639.01026939.01113.0FRFrance
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20741985043424937390794.0459080.0770708.0832.0FRFrance
20751985033213901174689.0253113.0388317.0459.0FRFrance
207619850239758680949.0114223.0177147.0207.0FRFrance
207719850138548965918.0105060.0155120.0190.0FRFrance
207819845238483060602.0109058.0154110.0198.0FRFrance
2079198451310172680242.0123210.0185146.0224.0FRFrance
20801984503123680101401.0145959.0225184.0266.0FRFrance
2081198449310107381684.0120462.0184149.0219.0FRFrance
208219844837862060634.096606.0143110.0176.0FRFrance
208319844737202954274.089784.013199.0163.0FRFrance
208419844638733067686.0106974.0159123.0195.0FRFrance
20851984453135223101414.0169032.0246184.0308.0FRFrance
208619844436842220056.0116788.012537.0213.0FRFrance
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2087 rows × 10 columns

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202425 3 47204 40300.0 54108.0 71 61.0 \n", + "19 202424 3 41110 34671.0 47549.0 62 52.0 \n", + "20 202423 3 35875 30610.0 41140.0 54 46.0 \n", + "21 202422 3 33772 28274.0 39270.0 51 43.0 \n", + "22 202421 3 21963 17556.0 26370.0 33 26.0 \n", + "23 202420 3 20057 15780.0 24334.0 30 24.0 \n", + "24 202419 3 15375 11274.0 19476.0 23 17.0 \n", + "25 202418 3 22409 17653.0 27165.0 34 27.0 \n", + "26 202417 3 27042 21410.0 32674.0 41 33.0 \n", + "27 202416 3 28882 23305.0 34459.0 43 35.0 \n", + "28 202415 3 30229 24648.0 35810.0 45 37.0 \n", + "29 202414 3 31813 26529.0 37097.0 48 40.0 \n", + "... ... ... ... ... ... ... ... \n", + "2057 198521 3 26096 19621.0 32571.0 47 35.0 \n", + "2058 198520 3 27896 20885.0 34907.0 51 38.0 \n", + "2059 198519 3 43154 32821.0 53487.0 78 59.0 \n", + "2060 198518 3 40555 29935.0 51175.0 74 55.0 \n", + "2061 198517 3 34053 24366.0 43740.0 62 44.0 \n", + "2062 198516 3 50362 36451.0 64273.0 91 66.0 \n", + "2063 198515 3 63881 45538.0 82224.0 116 83.0 \n", + 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FR France \n", + "26 49.0 FR France \n", + "27 51.0 FR France \n", + "28 53.0 FR France \n", + "29 56.0 FR France \n", + "... ... ... ... \n", + "2057 59.0 FR France \n", + "2058 64.0 FR France \n", + "2059 97.0 FR France \n", + "2060 93.0 FR France \n", + "2061 80.0 FR France \n", + "2062 116.0 FR France \n", + "2063 149.0 FR France \n", + "2064 281.0 FR France \n", + "2065 395.0 FR France \n", + "2066 485.0 FR France \n", + "2067 544.0 FR France \n", + "2068 689.0 FR France \n", + "2069 722.0 FR France \n", + "2070 762.0 FR France \n", + "2071 926.0 FR France \n", + "2072 1113.0 FR France \n", + "2073 1236.0 FR France \n", + "2074 832.0 FR France \n", + "2075 459.0 FR France \n", + "2076 207.0 FR France \n", + "2077 190.0 FR France \n", + "2078 198.0 FR France \n", + "2079 224.0 FR France \n", + "2080 266.0 FR France \n", + "2081 219.0 FR France \n", + "2082 176.0 FR France \n", + "2083 163.0 FR France \n", + "2084 195.0 FR France \n", + "2085 308.0 FR France \n", + "2086 213.0 FR 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weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_name
020244335495646518.063394.08269.095.0FRFrance
120244236832860465.076191.010290.0114.0FRFrance
220244137943571386.087484.0119107.0131.0FRFrance
320244038496576555.093375.0127114.0140.0FRFrance
420243939166082937.0100383.0137124.0150.0FRFrance
520243839178682903.0100669.0138125.0151.0FRFrance
620243735646049319.063601.08574.096.0FRFrance
720243633365727906.039408.05041.059.0FRFrance
820243532740422036.032772.04133.049.0FRFrance
920243432671721003.032431.04031.049.0FRFrance
1020243332062315349.025897.03123.039.0FRFrance
1120243232318717532.028842.03527.043.0FRFrance
1220243132603520267.031803.03930.048.0FRFrance
1320243033639328593.044193.05543.067.0FRFrance
1420242933956032592.046528.05949.069.0FRFrance
1520242835434245781.062903.08168.094.0FRFrance
1620242734736440234.054494.07160.082.0FRFrance
1720242634421936956.051482.06655.077.0FRFrance
1820242534720440300.054108.07161.081.0FRFrance
1920242434111034671.047549.06252.072.0FRFrance
2020242333587530610.041140.05446.062.0FRFrance
2120242233377228274.039270.05143.059.0FRFrance
2220242132196317556.026370.03326.040.0FRFrance
2320242032005715780.024334.03024.036.0FRFrance
2420241931537511274.019476.02317.029.0FRFrance
2520241832240917653.027165.03427.041.0FRFrance
2620241732704221410.032674.04133.049.0FRFrance
2720241632888223305.034459.04335.051.0FRFrance
2820241533022924648.035810.04537.053.0FRFrance
2920241433181326529.037097.04840.056.0FRFrance
.................................
205719852132609619621.032571.04735.059.0FRFrance
205819852032789620885.034907.05138.064.0FRFrance
205919851934315432821.053487.07859.097.0FRFrance
206019851834055529935.051175.07455.093.0FRFrance
206119851733405324366.043740.06244.080.0FRFrance
206219851635036236451.064273.09166.0116.0FRFrance
206319851536388145538.082224.011683.0149.0FRFrance
20641985143134545114400.0154690.0244207.0281.0FRFrance
20651985133197206176080.0218332.0357319.0395.0FRFrance
20661985123245240223304.0267176.0445405.0485.0FRFrance
20671985113276205252399.0300011.0501458.0544.0FRFrance
20681985103353231326279.0380183.0640591.0689.0FRFrance
20691985093369895341109.0398681.0670618.0722.0FRFrance
20701985083389886359529.0420243.0707652.0762.0FRFrance
20711985073471852432599.0511105.0855784.0926.0FRFrance
20721985063565825518011.0613639.01026939.01113.0FRFrance
20731985053637302592795.0681809.011551074.01236.0FRFrance
20741985043424937390794.0459080.0770708.0832.0FRFrance
20751985033213901174689.0253113.0388317.0459.0FRFrance
207619850239758680949.0114223.0177147.0207.0FRFrance
207719850138548965918.0105060.0155120.0190.0FRFrance
207819845238483060602.0109058.0154110.0198.0FRFrance
2079198451310172680242.0123210.0185146.0224.0FRFrance
20801984503123680101401.0145959.0225184.0266.0FRFrance
2081198449310107381684.0120462.0184149.0219.0FRFrance
208219844837862060634.096606.0143110.0176.0FRFrance
208319844737202954274.089784.013199.0163.0FRFrance
208419844638733067686.0106974.0159123.0195.0FRFrance
20851984453135223101414.0169032.0246184.0308.0FRFrance
208619844436842220056.0116788.012537.0213.0FRFrance
\n", + "

2086 rows × 10 columns

\n", + "
" + ], + "text/plain": [ + " week indicator inc inc_low inc_up inc100 inc100_low \\\n", + "0 202443 3 54956 46518.0 63394.0 82 69.0 \n", + "1 202442 3 68328 60465.0 76191.0 102 90.0 \n", + "2 202441 3 79435 71386.0 87484.0 119 107.0 \n", + "3 202440 3 84965 76555.0 93375.0 127 114.0 \n", + "4 202439 3 91660 82937.0 100383.0 137 124.0 \n", + "5 202438 3 91786 82903.0 100669.0 138 125.0 \n", + "6 202437 3 56460 49319.0 63601.0 85 74.0 \n", + "7 202436 3 33657 27906.0 39408.0 50 41.0 \n", + "8 202435 3 27404 22036.0 32772.0 41 33.0 \n", + "9 202434 3 26717 21003.0 32431.0 40 31.0 \n", + "10 202433 3 20623 15349.0 25897.0 31 23.0 \n", + "11 202432 3 23187 17532.0 28842.0 35 27.0 \n", + "12 202431 3 26035 20267.0 31803.0 39 30.0 \n", + "13 202430 3 36393 28593.0 44193.0 55 43.0 \n", + "14 202429 3 39560 32592.0 46528.0 59 49.0 \n", + "15 202428 3 54342 45781.0 62903.0 81 68.0 \n", + "16 202427 3 47364 40234.0 54494.0 71 60.0 \n", + "17 202426 3 44219 36956.0 51482.0 66 55.0 \n", + "18 202425 3 47204 40300.0 54108.0 71 61.0 \n", + "19 202424 3 41110 34671.0 47549.0 62 52.0 \n", + "20 202423 3 35875 30610.0 41140.0 54 46.0 \n", + "21 202422 3 33772 28274.0 39270.0 51 43.0 \n", + "22 202421 3 21963 17556.0 26370.0 33 26.0 \n", + "23 202420 3 20057 15780.0 24334.0 30 24.0 \n", + "24 202419 3 15375 11274.0 19476.0 23 17.0 \n", + "25 202418 3 22409 17653.0 27165.0 34 27.0 \n", + "26 202417 3 27042 21410.0 32674.0 41 33.0 \n", + "27 202416 3 28882 23305.0 34459.0 43 35.0 \n", + "28 202415 3 30229 24648.0 35810.0 45 37.0 \n", + "29 202414 3 31813 26529.0 37097.0 48 40.0 \n", + "... ... ... ... ... ... ... ... \n", + "2057 198521 3 26096 19621.0 32571.0 47 35.0 \n", + "2058 198520 3 27896 20885.0 34907.0 51 38.0 \n", + "2059 198519 3 43154 32821.0 53487.0 78 59.0 \n", + "2060 198518 3 40555 29935.0 51175.0 74 55.0 \n", + "2061 198517 3 34053 24366.0 43740.0 62 44.0 \n", + "2062 198516 3 50362 36451.0 64273.0 91 66.0 \n", + "2063 198515 3 63881 45538.0 82224.0 116 83.0 \n", + "2064 198514 3 134545 114400.0 154690.0 244 207.0 \n", + "2065 198513 3 197206 176080.0 218332.0 357 319.0 \n", + "2066 198512 3 245240 223304.0 267176.0 445 405.0 \n", + "2067 198511 3 276205 252399.0 300011.0 501 458.0 \n", + "2068 198510 3 353231 326279.0 380183.0 640 591.0 \n", + "2069 198509 3 369895 341109.0 398681.0 670 618.0 \n", + "2070 198508 3 389886 359529.0 420243.0 707 652.0 \n", + "2071 198507 3 471852 432599.0 511105.0 855 784.0 \n", + "2072 198506 3 565825 518011.0 613639.0 1026 939.0 \n", + "2073 198505 3 637302 592795.0 681809.0 1155 1074.0 \n", + "2074 198504 3 424937 390794.0 459080.0 770 708.0 \n", + "2075 198503 3 213901 174689.0 253113.0 388 317.0 \n", + "2076 198502 3 97586 80949.0 114223.0 177 147.0 \n", + "2077 198501 3 85489 65918.0 105060.0 155 120.0 \n", + "2078 198452 3 84830 60602.0 109058.0 154 110.0 \n", + "2079 198451 3 101726 80242.0 123210.0 185 146.0 \n", + "2080 198450 3 123680 101401.0 145959.0 225 184.0 \n", + "2081 198449 3 101073 81684.0 120462.0 184 149.0 \n", + "2082 198448 3 78620 60634.0 96606.0 143 110.0 \n", + "2083 198447 3 72029 54274.0 89784.0 131 99.0 \n", + "2084 198446 3 87330 67686.0 106974.0 159 123.0 \n", + "2085 198445 3 135223 101414.0 169032.0 246 184.0 \n", + "2086 198444 3 68422 20056.0 116788.0 125 37.0 \n", + "\n", + " inc100_up geo_insee geo_name \n", + "0 95.0 FR France \n", + "1 114.0 FR France \n", + "2 131.0 FR France \n", + "3 140.0 FR France \n", + "4 150.0 FR France \n", + "5 151.0 FR France \n", + "6 96.0 FR France \n", + "7 59.0 FR France \n", + "8 49.0 FR France \n", + "9 49.0 FR France \n", + "10 39.0 FR France \n", + "11 43.0 FR France \n", + "12 48.0 FR France \n", + "13 67.0 FR France \n", + "14 69.0 FR France \n", + "15 94.0 FR France \n", + "16 82.0 FR France \n", + "17 77.0 FR France \n", + "18 81.0 FR France \n", + "19 72.0 FR France \n", + "20 62.0 FR France \n", + "21 59.0 FR France \n", + "22 40.0 FR France \n", + "23 36.0 FR France \n", + "24 29.0 FR France \n", + "25 41.0 FR France \n", + "26 49.0 FR France \n", + "27 51.0 FR France \n", + "28 53.0 FR France \n", + "29 56.0 FR France \n", + "... ... ... ... \n", + "2057 59.0 FR France \n", + "2058 64.0 FR France \n", + "2059 97.0 FR France \n", + "2060 93.0 FR France \n", + "2061 80.0 FR France \n", + "2062 116.0 FR France \n", + "2063 149.0 FR France \n", + "2064 281.0 FR France \n", + "2065 395.0 FR France \n", + "2066 485.0 FR France \n", + "2067 544.0 FR France \n", + "2068 689.0 FR France \n", + "2069 722.0 FR France \n", + "2070 762.0 FR France \n", + "2071 926.0 FR France \n", + "2072 1113.0 FR France \n", + "2073 1236.0 FR France \n", + "2074 832.0 FR France \n", + "2075 459.0 FR France \n", + "2076 207.0 FR France \n", + "2077 190.0 FR France \n", + "2078 198.0 FR France \n", + "2079 224.0 FR France \n", + "2080 266.0 FR France \n", + "2081 219.0 FR France \n", + "2082 176.0 FR France \n", + "2083 163.0 FR France \n", + "2084 195.0 FR France \n", + "2085 308.0 FR France \n", + "2086 213.0 FR France \n", + "\n", + "[2086 rows x 10 columns]" + ] + }, + "execution_count": 27, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "data = raw_data.dropna().copy()\n", "data" @@ -150,7 +2129,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 28, "metadata": {}, "outputs": [], "source": [ @@ -180,10 +2159,8 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": true - }, + "execution_count": 29, + "metadata": {}, "outputs": [], "source": [ "sorted_data = data.set_index('period').sort_index()" @@ -207,9 +2184,17 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 30, "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", @@ -218,6 +2203,88 @@ " print(p1, p2)" ] }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "period\n", + "1984-10-29/1984-11-04 68422\n", + "1984-11-05/1984-11-11 135223\n", + "1984-11-12/1984-11-18 87330\n", + "1984-11-19/1984-11-25 72029\n", + "1984-11-26/1984-12-02 78620\n", + "1984-12-03/1984-12-09 101073\n", + "1984-12-10/1984-12-16 123680\n", + "1984-12-17/1984-12-23 101726\n", + "1984-12-24/1984-12-30 84830\n", + "1984-12-31/1985-01-06 85489\n", + "1985-01-07/1985-01-13 97586\n", + "1985-01-14/1985-01-20 213901\n", + "1985-01-21/1985-01-27 424937\n", + "1985-01-28/1985-02-03 637302\n", + "1985-02-04/1985-02-10 565825\n", + "1985-02-11/1985-02-17 471852\n", + "1985-02-18/1985-02-24 389886\n", + "1985-02-25/1985-03-03 369895\n", + "1985-03-04/1985-03-10 353231\n", + "1985-03-11/1985-03-17 276205\n", + "1985-03-18/1985-03-24 245240\n", + "1985-03-25/1985-03-31 197206\n", + "1985-04-01/1985-04-07 134545\n", + "1985-04-08/1985-04-14 63881\n", + "1985-04-15/1985-04-21 50362\n", + "1985-04-22/1985-04-28 34053\n", + "1985-04-29/1985-05-05 40555\n", + "1985-05-06/1985-05-12 43154\n", + "1985-05-13/1985-05-19 27896\n", + "1985-05-20/1985-05-26 26096\n", + " ... \n", + "2024-04-01/2024-04-07 31813\n", + "2024-04-08/2024-04-14 30229\n", + "2024-04-15/2024-04-21 28882\n", + "2024-04-22/2024-04-28 27042\n", + "2024-04-29/2024-05-05 22409\n", + "2024-05-06/2024-05-12 15375\n", + "2024-05-13/2024-05-19 20057\n", + "2024-05-20/2024-05-26 21963\n", + "2024-05-27/2024-06-02 33772\n", + "2024-06-03/2024-06-09 35875\n", + "2024-06-10/2024-06-16 41110\n", + "2024-06-17/2024-06-23 47204\n", + "2024-06-24/2024-06-30 44219\n", + "2024-07-01/2024-07-07 47364\n", + "2024-07-08/2024-07-14 54342\n", + "2024-07-15/2024-07-21 39560\n", + "2024-07-22/2024-07-28 36393\n", + "2024-07-29/2024-08-04 26035\n", + "2024-08-05/2024-08-11 23187\n", + "2024-08-12/2024-08-18 20623\n", + "2024-08-19/2024-08-25 26717\n", + "2024-08-26/2024-09-01 27404\n", + "2024-09-02/2024-09-08 33657\n", + "2024-09-09/2024-09-15 56460\n", + "2024-09-16/2024-09-22 91786\n", + "2024-09-23/2024-09-29 91660\n", + "2024-09-30/2024-10-06 84965\n", + "2024-10-07/2024-10-13 79435\n", + "2024-10-14/2024-10-20 68328\n", + "2024-10-21/2024-10-27 54956\n", + "Freq: W-SUN, Name: inc, Length: 2086, dtype: object" + ] + }, + "execution_count": 31, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sorted_data[\"inc\"]" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -227,10 +2294,34 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 37, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 37, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], "source": [ + "sorted_data[\"inc\"] = sorted_data[\"inc\"].astype(int)\n", "sorted_data['inc'].plot()" ] }, @@ -243,9 +2334,32 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 39, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 39, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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\n", 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4111392\n", + "2013 4182691\n", + "1986 5115251\n", + "1990 5235827\n", + "1989 5466192\n", + "dtype: int64" + ] + }, + "execution_count": 43, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "yearly_incidence.sort_values()" ] @@ -359,21 +2543,35 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 44, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 44, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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