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weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_name
\n", + "
" + ], + "text/plain": [ + "Empty DataFrame\n", + "Columns: [week, indicator, inc, inc_low, inc_up, inc100, inc100_low, inc100_up, geo_insee, geo_name]\n", + "Index: []" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "raw_data[raw_data.isnull().any(axis=1)]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "no data missing" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "convert data to year" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "data = raw_data\n", + "def convert_week(year_and_week_int):\n", + " year_and_week_str = str(year_and_week_int)\n", + " year = int(year_and_week_str[:4])\n", + " week = int(year_and_week_str[4:])\n", + " w = isoweek.Week(year, week)\n", + " return pd.Period(w.day(0), 'W')\n", + "\n", + "data['period'] = [convert_week(yw) for yw in data['week']]" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "sorted_data = data.set_index('period').sort_index()" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [], + "source": [ + "#see some missing?\n", + "periods = sorted_data.index\n", + "for p1, p2 in zip(periods[:-1], periods[1:]):\n", + " delta = p2.to_timestamp() - p1.end_time\n", + " if delta > pd.Timedelta('1s'):\n", + " print(p1, p2)" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "1991-07-29/1991-08-04\n", + "1992-07-27/1992-08-02\n", + "1993-07-26/1993-08-01\n", + "1994-08-01/1994-08-07\n", + "1995-07-31/1995-08-06\n", + "1996-07-29/1996-08-04\n", + "1997-07-28/1997-08-03\n", + "1998-07-27/1998-08-02\n", + "1999-07-26/1999-08-01\n", + "2000-07-31/2000-08-06\n", + "2001-07-30/2001-08-05\n", + "2002-07-29/2002-08-04\n", + "2003-07-28/2003-08-03\n", + "2004-07-26/2004-08-01\n", + "2005-08-01/2005-08-07\n", + "2006-07-31/2006-08-06\n", + "2007-07-30/2007-08-05\n", + "2008-07-28/2008-08-03\n", + "2009-07-27/2009-08-02\n", + "2010-07-26/2010-08-01\n", + "2011-08-01/2011-08-07\n", + "2012-07-30/2012-08-05\n", + "2013-07-29/2013-08-04\n", + "2014-07-28/2014-08-03\n", + "2015-07-27/2015-08-02\n", + "2016-08-01/2016-08-07\n", + "2017-07-31/2017-08-06\n", + "2018-07-30/2018-08-05\n", + "2019-07-29/2019-08-04\n", + "2020-07-27/2020-08-02\n", + "2021-07-26/2021-08-01\n", + "2022-08-01/2022-08-07\n", + "2023-07-31/2023-08-06\n" + ] + } + ], + "source": [ + "first_august_week = [pd.Period(pd.Timestamp(y, 8, 1), 'W')\n", + " for y in range(1991,\n", + " sorted_data.index[-1].year)]\n", + "\n", + "for i in first_august_week:\n", + " print(i)" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Year 1991: Total 'inc' sum = 679607\n", + "Year 1992: Total 'inc' sum = 843500\n", + "Year 1993: Total 'inc' sum = 611264\n", + "Year 1994: Total 'inc' sum = 670292\n", + "Year 1995: Total 'inc' sum = 667294\n", + "Year 1996: Total 'inc' sum = 646644\n", + "Year 1997: Total 'inc' sum = 643524\n", + "Year 1998: Total 'inc' sum = 785055\n", + "Year 1999: Total 'inc' sum = 670819\n", + "Year 2000: Total 'inc' sum = 656975\n", + "Year 2001: Total 'inc' sum = 569744\n", + "Year 2002: Total 'inc' sum = 612129\n", + "Year 2003: Total 'inc' sum = 703899\n", + "Year 2004: Total 'inc' sum = 850765\n", + "Year 2005: Total 'inc' sum = 672315\n", + "Year 2006: Total 'inc' sum = 574493\n", + "Year 2007: Total 'inc' sum = 798899\n", + "Year 2008: Total 'inc' sum = 766066\n", + "Year 2009: Total 'inc' sum = 875937\n", + "Year 2010: Total 'inc' sum = 794691\n", + "Year 2011: Total 'inc' sum = 655146\n", + "Year 2012: Total 'inc' sum = 720814\n", + "Year 2013: Total 'inc' sum = 680822\n", + "Year 2014: Total 'inc' sum = 664026\n", + "Year 2015: Total 'inc' sum = 649742\n", + "Year 2016: Total 'inc' sum = 744389\n", + "Year 2017: Total 'inc' sum = 564245\n", + "Year 2018: Total 'inc' sum = 577351\n", + "Year 2019: Total 'inc' sum = 550709\n", + "Year 2020: Total 'inc' sum = 229985\n", + "Year 2021: Total 'inc' sum = 441771\n", + "Year 2022: Total 'inc' sum = 582916\n", + "Year 2023: Total 'inc' sum = 382480\n" + ] + } + ], + "source": [ + "import pandas as pd\n", + "\n", + "# Initialize a dictionary to store annual sums\n", + "annual_sums = {}\n", + "\n", + "# Iterate over each year's first week of August\n", + "for week_start in first_august_week:\n", + " year = week_start.year\n", + "\n", + " year_data = sorted_data[str(year)]\n", + " annual_sum = year_data['inc'].sum()\n", + " \n", + " # Store the annual sum in the dictionary\n", + " annual_sums[year] = annual_sum\n", + "\n", + "# Print annual sums\n", + "for year, total_inc in annual_sums.items():\n", + " print(f\"Year {year}: Total 'inc' sum = {total_inc}\")\n" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "875937\n", + "229985\n" + ] + } + ], + "source": [ + "max_sum = max(annual_sums.values())\n", + "min_sum = min(annual_sums.values())\n", + "print(max_sum)\n", + "print(min_sum)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], "metadata": { "kernelspec": { "display_name": "Python 3", @@ -16,10 +1269,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.3" + "version": "3.6.4" } }, "nbformat": 4, "nbformat_minor": 2 } - -- 2.18.1