From 5bf8c3729bbda046cb9ac59207acd7854d512851 Mon Sep 17 00:00:00 2001 From: acf00a978da766b41fd85a723e4a5fc2 Date: Mon, 9 Sep 2024 09:39:40 +0000 Subject: [PATCH] local file saved --- module2/exo5/analyse-syndromes-grippaux.ipynb | 6 + .../influenza-like-illness-analysis.ipynb | 1276 ++++++++++++++++- 2 files changed, 1238 insertions(+), 44 deletions(-) create mode 100644 module2/exo5/analyse-syndromes-grippaux.ipynb diff --git a/module2/exo5/analyse-syndromes-grippaux.ipynb b/module2/exo5/analyse-syndromes-grippaux.ipynb new file mode 100644 index 0000000..7fec515 --- /dev/null +++ b/module2/exo5/analyse-syndromes-grippaux.ipynb @@ -0,0 +1,6 @@ +{ + "cells": [], + "metadata": {}, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/module3/exo1/influenza-like-illness-analysis.ipynb b/module3/exo1/influenza-like-illness-analysis.ipynb index 87092fc..8672bad 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", @@ -30,13 +28,11 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": true - }, + "execution_count": 31, + "metadata": {}, "outputs": [], "source": [ - "data_url = \"http://www.sentiweb.fr/datasets/incidence-PAY-3.csv\"" + "data_url = \"C:/Users/Utilisateur/Downloads/incidence-PAY-3.csv\"" ] }, { @@ -63,9 +59,28 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 32, "metadata": {}, - "outputs": [], + "outputs": [ + { + "ename": "FileNotFoundError", + "evalue": "File b'C:/Users/Utilisateur/Downloads/incidence-PAY-3.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_url\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", + "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36m_read\u001b[0;34m(filepath_or_buffer, kwds)\u001b[0m\n\u001b[1;32m 447\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 448\u001b[0m \u001b[0;31m# Create the parser.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 449\u001b[0;31m \u001b[0mparser\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mTextFileReader\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfilepath_or_buffer\u001b[0m\u001b[0;34m,\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 450\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 451\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mchunksize\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0miterator\u001b[0m\u001b[0;34m:\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;36m__init__\u001b[0;34m(self, f, engine, **kwds)\u001b[0m\n\u001b[1;32m 816\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0moptions\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'has_index_names'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mkwds\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'has_index_names'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 817\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 818\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_make_engine\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mengine\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 819\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 820\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mclose\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + 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"raw_data = pd.read_csv(data_url, skiprows=1)\n", "raw_data" @@ -80,9 +95,73 @@ }, { "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
020243533126524260.038270.04736.058.0FRFrance
120243432672220975.032469.04031.049.0FRFrance
220243332062315349.025897.03123.039.0FRFrance
320243232318717532.028842.03527.043.0FRFrance
420243132603520267.031803.03930.048.0FRFrance
520243033639328593.044193.05543.067.0FRFrance
620242933956032592.046528.05949.069.0FRFrance
720242835434245781.062903.08168.094.0FRFrance
820242734736440234.054494.07160.082.0FRFrance
920242634421936956.051482.06655.077.0FRFrance
1020242534720440300.054108.07161.081.0FRFrance
1120242434111034671.047549.06252.072.0FRFrance
1220242333587530610.041140.05446.062.0FRFrance
1320242233377228274.039270.05143.059.0FRFrance
1420242132196317556.026370.03326.040.0FRFrance
1520242032005715780.024334.03024.036.0FRFrance
1620241931537511274.019476.02317.029.0FRFrance
1720241832240917653.027165.03427.041.0FRFrance
1820241732704221410.032674.04133.049.0FRFrance
1920241632888223305.034459.04335.051.0FRFrance
2020241533022924648.035810.04537.053.0FRFrance
2120241433181326529.037097.04840.056.0FRFrance
2220241333509029607.040573.05345.061.0FRFrance
2320241234063934582.046696.06152.070.0FRFrance
2420241135026843331.057205.07565.085.0FRFrance
2520241036010752623.067591.09079.0101.0FRFrance
2620240937112162920.079322.010795.0119.0FRFrance
27202408310456694520.0114612.0157142.0172.0FRFrance
282024073138078127050.0149106.0207190.0224.0FRFrance
292024063190062177955.0202169.0285267.0303.0FRFrance
.................................
204919852132609619621.032571.04735.059.0FRFrance
205019852032789620885.034907.05138.064.0FRFrance
205119851934315432821.053487.07859.097.0FRFrance
205219851834055529935.051175.07455.093.0FRFrance
205319851733405324366.043740.06244.080.0FRFrance
205419851635036236451.064273.09166.0116.0FRFrance
205519851536388145538.082224.011683.0149.0FRFrance
20561985143134545114400.0154690.0244207.0281.0FRFrance
20571985133197206176080.0218332.0357319.0395.0FRFrance
20581985123245240223304.0267176.0445405.0485.0FRFrance
20591985113276205252399.0300011.0501458.0544.0FRFrance
20601985103353231326279.0380183.0640591.0689.0FRFrance
20611985093369895341109.0398681.0670618.0722.0FRFrance
20621985083389886359529.0420243.0707652.0762.0FRFrance
20631985073471852432599.0511105.0855784.0926.0FRFrance
20641985063565825518011.0613639.01026939.01113.0FRFrance
20651985053637302592795.0681809.011551074.01236.0FRFrance
20661985043424937390794.0459080.0770708.0832.0FRFrance
20671985033213901174689.0253113.0388317.0459.0FRFrance
206819850239758680949.0114223.0177147.0207.0FRFrance
206919850138548965918.0105060.0155120.0190.0FRFrance
207019845238483060602.0109058.0154110.0198.0FRFrance
2071198451310172680242.0123210.0185146.0224.0FRFrance
20721984503123680101401.0145959.0225184.0266.0FRFrance
2073198449310107381684.0120462.0184149.0219.0FRFrance
207419844837862060634.096606.0143110.0176.0FRFrance
207519844737202954274.089784.013199.0163.0FRFrance
207619844638733067686.0106974.0159123.0195.0FRFrance
20771984453135223101414.0169032.0246184.0308.0FRFrance
207819844436842220056.0116788.012537.0213.0FRFrance
\n", + "

2078 rows × 10 columns

\n", + "
" + ], + "text/plain": [ + " week indicator inc inc_low inc_up inc100 inc100_low \\\n", + "0 202435 3 31265 24260.0 38270.0 47 36.0 \n", + "1 202434 3 26722 20975.0 32469.0 40 31.0 \n", + "2 202433 3 20623 15349.0 25897.0 31 23.0 \n", + "3 202432 3 23187 17532.0 28842.0 35 27.0 \n", + "4 202431 3 26035 20267.0 31803.0 39 30.0 \n", + "5 202430 3 36393 28593.0 44193.0 55 43.0 \n", + "6 202429 3 39560 32592.0 46528.0 59 49.0 \n", + "7 202428 3 54342 45781.0 62903.0 81 68.0 \n", + "8 202427 3 47364 40234.0 54494.0 71 60.0 \n", + "9 202426 3 44219 36956.0 51482.0 66 55.0 \n", + "10 202425 3 47204 40300.0 54108.0 71 61.0 \n", + "11 202424 3 41110 34671.0 47549.0 62 52.0 \n", + "12 202423 3 35875 30610.0 41140.0 54 46.0 \n", + "13 202422 3 33772 28274.0 39270.0 51 43.0 \n", + "14 202421 3 21963 17556.0 26370.0 33 26.0 \n", + "15 202420 3 20057 15780.0 24334.0 30 24.0 \n", + "16 202419 3 15375 11274.0 19476.0 23 17.0 \n", + "17 202418 3 22409 17653.0 27165.0 34 27.0 \n", + "18 202417 3 27042 21410.0 32674.0 41 33.0 \n", + "19 202416 3 28882 23305.0 34459.0 43 35.0 \n", + "20 202415 3 30229 24648.0 35810.0 45 37.0 \n", + "21 202414 3 31813 26529.0 37097.0 48 40.0 \n", + "22 202413 3 35090 29607.0 40573.0 53 45.0 \n", + "23 202412 3 40639 34582.0 46696.0 61 52.0 \n", + "24 202411 3 50268 43331.0 57205.0 75 65.0 \n", + "25 202410 3 60107 52623.0 67591.0 90 79.0 \n", + "26 202409 3 71121 62920.0 79322.0 107 95.0 \n", + "27 202408 3 104566 94520.0 114612.0 157 142.0 \n", + "28 202407 3 138078 127050.0 149106.0 207 190.0 \n", + "29 202406 3 190062 177955.0 202169.0 285 267.0 \n", + "... ... ... ... ... ... ... ... \n", + "2049 198521 3 26096 19621.0 32571.0 47 35.0 \n", + "2050 198520 3 27896 20885.0 34907.0 51 38.0 \n", + "2051 198519 3 43154 32821.0 53487.0 78 59.0 \n", + "2052 198518 3 40555 29935.0 51175.0 74 55.0 \n", + "2053 198517 3 34053 24366.0 43740.0 62 44.0 \n", + "2054 198516 3 50362 36451.0 64273.0 91 66.0 \n", + "2055 198515 3 63881 45538.0 82224.0 116 83.0 \n", + "2056 198514 3 134545 114400.0 154690.0 244 207.0 \n", + "2057 198513 3 197206 176080.0 218332.0 357 319.0 \n", + "2058 198512 3 245240 223304.0 267176.0 445 405.0 \n", + "2059 198511 3 276205 252399.0 300011.0 501 458.0 \n", + "2060 198510 3 353231 326279.0 380183.0 640 591.0 \n", + "2061 198509 3 369895 341109.0 398681.0 670 618.0 \n", + "2062 198508 3 389886 359529.0 420243.0 707 652.0 \n", + "2063 198507 3 471852 432599.0 511105.0 855 784.0 \n", + "2064 198506 3 565825 518011.0 613639.0 1026 939.0 \n", + "2065 198505 3 637302 592795.0 681809.0 1155 1074.0 \n", + "2066 198504 3 424937 390794.0 459080.0 770 708.0 \n", + "2067 198503 3 213901 174689.0 253113.0 388 317.0 \n", + "2068 198502 3 97586 80949.0 114223.0 177 147.0 \n", + "2069 198501 3 85489 65918.0 105060.0 155 120.0 \n", + "2070 198452 3 84830 60602.0 109058.0 154 110.0 \n", + "2071 198451 3 101726 80242.0 123210.0 185 146.0 \n", + "2072 198450 3 123680 101401.0 145959.0 225 184.0 \n", + "2073 198449 3 101073 81684.0 120462.0 184 149.0 \n", + "2074 198448 3 78620 60634.0 96606.0 143 110.0 \n", + "2075 198447 3 72029 54274.0 89784.0 131 99.0 \n", + "2076 198446 3 87330 67686.0 106974.0 159 123.0 \n", + "2077 198445 3 135223 101414.0 169032.0 246 184.0 \n", + "2078 198444 3 68422 20056.0 116788.0 125 37.0 \n", + "\n", + " inc100_up geo_insee geo_name \n", + "0 58.0 FR France \n", + "1 49.0 FR France \n", + "2 39.0 FR France \n", + "3 43.0 FR France \n", + "4 48.0 FR France \n", + "5 67.0 FR France \n", + "6 69.0 FR France \n", + "7 94.0 FR France \n", + "8 82.0 FR France \n", + "9 77.0 FR France \n", + "10 81.0 FR France \n", + "11 72.0 FR France \n", + "12 62.0 FR France \n", + "13 59.0 FR France \n", + "14 40.0 FR France \n", + "15 36.0 FR France \n", + "16 29.0 FR France \n", + "17 41.0 FR France \n", + "18 49.0 FR France \n", + "19 51.0 FR France \n", + "20 53.0 FR France \n", + "21 56.0 FR France \n", + "22 61.0 FR France \n", + "23 70.0 FR France \n", + "24 85.0 FR France \n", + "25 101.0 FR France \n", + "26 119.0 FR France \n", + "27 172.0 FR France \n", + "28 224.0 FR France \n", + "29 303.0 FR France \n", + "... ... ... ... \n", + "2049 59.0 FR France \n", + "2050 64.0 FR France \n", + "2051 97.0 FR France \n", + "2052 93.0 FR France \n", + "2053 80.0 FR France \n", + "2054 116.0 FR France \n", + "2055 149.0 FR France \n", + "2056 281.0 FR France \n", + "2057 395.0 FR France \n", + "2058 485.0 FR France \n", + "2059 544.0 FR France \n", + "2060 689.0 FR France \n", + "2061 722.0 FR France \n", + "2062 762.0 FR France \n", + "2063 926.0 FR France \n", + "2064 1113.0 FR France \n", + "2065 1236.0 FR France \n", + "2066 832.0 FR France \n", + "2067 459.0 FR France \n", + "2068 207.0 FR France \n", + "2069 190.0 FR France \n", + "2070 198.0 FR France \n", + "2071 224.0 FR France \n", + "2072 266.0 FR France \n", + "2073 219.0 FR France \n", + "2074 176.0 FR France \n", + "2075 163.0 FR France \n", + "2076 195.0 FR France \n", + "2077 308.0 FR France \n", + "2078 213.0 FR France \n", + "\n", + "[2078 rows x 10 columns]" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "data = raw_data.dropna().copy()\n", "data" @@ -123,10 +1169,8 @@ }, { "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 +1198,8 @@ }, { "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 +1222,17 @@ }, { "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", @@ -200,10 +1250,34 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 16, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 16, + "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'] = sorted_data['inc'].astype(int)\n", "sorted_data['inc'].plot()" ] }, @@ -216,9 +1290,32 @@ }, { "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", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], "source": [ "sorted_data['inc'][-200:].plot()" ] @@ -251,10 +1348,8 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": true - }, + "execution_count": 18, + "metadata": {}, "outputs": [], "source": [ "first_august_week = [pd.Period(pd.Timestamp(y, 8, 1), 'W')\n", @@ -273,10 +1368,8 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": true - }, + "execution_count": 19, + "metadata": {}, "outputs": [], "source": [ "year = []\n", @@ -299,9 +1392,32 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 20, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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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": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "yearly_incidence.sort_values()" ] @@ -332,9 +1497,32 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 22, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
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