unfccc_code_ch4.ipynb

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   "cell_type": "code",
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   "id": "b1da3be5-6994-409b-a59d-d05979d6030d",
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   "outputs": [],
   "source": [
    "#!/usr/bin/env python3\n",
    "# -*- coding: utf-8 -*-\n",
    "\"\"\"\n",
    "Created on Fri Apr  3 10:25:44 2020\n",
    "Updated on Thur Jun 24 14:39:00 2021\n",
    "\n",
    "@author: KStanely\n",
    "\n",
    "\n",
    "\n",
    "Code created to scrape, download and process UNFCCC CRF data.\n",
    "\n",
    "Functions included in package: \n",
    "    unfccc:\n",
    "        - Overarching script that scrapes UNFCCC data, unzips the data, processes\n",
    "          data into a common format by gas and by country and plots data by region\n",
    "          or country. Function calls:\n",
    "            - unfccc_scrape\n",
    "            - unfccc_unzip\n",
    "            - crf_import\n",
    "            - crf_plot\n",
    "        - Requires:\n",
    "            - year = the year (as a string) of the data to scrape.\n",
    "            - data_path = a base directory of where the data will be stored.\n",
    "            - scrape = True/False depending if you want to (re)scrape data from\n",
    "                       UNFCCC website and store zip files in\n",
    "                       data_path/year/data/zip/.\n",
    "            - unzip = True/False depending if you want to (re-)unzip downloaded\n",
    "                      zip files in data_path/year/data/zip/.\n",
    "            - process = True/False depending if you want to (re)process unzipped\n",
    "                        files in data_path/year/data/zip/ and store in\n",
    "                        data_path/year/data/.\n",
    "            - plot = True/False depending if you want to (re)plot data.\n",
    "            - plot_country = see crf_plot explanation for information.\n",
    "            - plot_region = see crf_plot explanation for information.\n",
    "        - Output is stored in data_path:\n",
    "            - raw data: in data_path/year/data/zip/ by country.\n",
    "            - scraped file: csv file containing all countries and urls scraped\n",
    "                            from UNFCCC website in data_path/year/scraped_urls.csv.\n",
    "            - unzipped data: in data_path/year/data/ by country.\n",
    "            - processed data: csv files in data_path/processed_data in country files\n",
    "                              for all gases (Country_NIR_YYYY_all_gases_yearly.csv)\n",
    "                              and gas specific (i.e. Australia_NIR_2019_SF6.csv).\n",
    "            - plots: png files in data_path/year/plots/ by country/region plotted.\n",
    "    unfccc_scrape:\n",
    "        - Used to scrape URLs from UNFCCC website.\n",
    "        - Requires the specific version of chromdriver (line 152) that matches\n",
    "          your version of Chrome. Chromedriver can be downloaded from \n",
    "          https://chromedriver.chromium.org/downloads\n",
    "        - Requires:\n",
    "            - year = the year (as a string) of the data to scrape.\n",
    "            - data_path = a base directory of where the data will be stored\n",
    "        - Output is a list of lists called: unfccc_urls\n",
    "    unfccc_unzip:\n",
    "        - used to unzip data folders scraped from UNFCCC website by unfccc_scrape()\n",
    "        - Requires:\n",
    "            - year = the year (as a string) of the data.\n",
    "            - data_path = a base directory of where the data will be stored\n",
    "        - Output is country specific folders with excel files in\n",
    "    crf_import:\n",
    "        - Used to import excel datafiles unzipped by unfccc_unzip\n",
    "        - Requires:\n",
    "            - year = the year (as a string) of the data.\n",
    "            - data_path = a base directory of where the data will be stored\n",
    "        - Output is country specific and gas specific data in excel files, stored\n",
    "          in the data_path/year/processed_data/\n",
    "    crf_plot:\n",
    "        - Used to plot up CRF data\n",
    "        - Requires:\n",
    "            - year = the year (as a string) of the data to scrape.\n",
    "            - data_path = a base directory of where the plots will be stored\n",
    "            - plot_country = string indicating data to plot. Requires capital leter\n",
    "                        at start of name and no spaces, e.g. NewZealand. For The\n",
    "                        Netherlands\n",
    "            - plot_regions = string indicating Annex I regions to plot data, from\n",
    "                             the following:\n",
    "                - all = all Annex I countries, EU27 as a total (not by individual states)\n",
    "                - EU = EU27 states, excludes UK\n",
    "                - EU28 = EU27 states, plus UK\n",
    "                - EU+ = EU27 states, plus UK, Liechtenstein, Iceland, Monaco,\n",
    "                        Norway and Switzerland\n",
    "                - NAFTA = USA & Canada\n",
    "                - Australasia = Australia, New Zealand & Japan\n",
    "                - EITs = Economies in transition: Belarus, Croatia, Czech Republic,\n",
    "                         Estonia, Hungary, Kazakhstan, Latvia, Lithuania, Poland,\n",
    "                         Romania, Russia, Slovakia, Slovenia & Ukraine\n",
    "                - Soviet = Former soviet states: Belarus, Estonia, Kazakhstan,\n",
    "                         Latvia, Lithuania, Russia & Ukraine\n",
    "        - Output is in png format and stored in the data_path/year/plots/ by\n",
    "          country/region.\n",
    "\"\"\"\n",
    "\n",
    "\n",
    "###############################################################################\n",
    "### unfccc_scrape function\n",
    "###############################################################################\n",
    "\n",
    "def unfccc(process_year = '2022', data_path = '/Users/ks15697/Documents/Python/UNFCCC/',\n",
    "           scrape = True, unzip = True, process = True, plot = True,\n",
    "           plot_country = \"Germany\", plot_region = None):\n",
    "\n",
    "    if scrape == True:\n",
    "        unfccc_scrape(year = process_year, data_path = data_path)\n",
    "        input(\"Press Enter to continue...\")\n",
    "\n",
    "    if unzip == True:\n",
    "        unfccc_unzip(year = process_year, data_path = data_path)\n",
    "\n",
    "    if process == True:\n",
    "        crf_import(year = process_year, data_path = data_path)\n",
    "\n",
    "    if plot == True:\n",
    "        crf_plot(year = process_year, data_path = data_path, plot_country = plot_country,\n",
    "                 plot_region = plot_region)\n",
    "\n",
    "###############################################################################\n",
    "### unfccc_scrape function\n",
    "###############################################################################\n",
    "\n",
    "def unfccc_scrape(year = '2022', data_path = '/Users/ks15697/Documents/Python/UNFCCC/'):\n",
    "    from selenium import webdriver\n",
    "    from selenium.webdriver.chrome.options import Options\n",
    "    #from webdriver_manager.chrome import ChromeDriverManager\n",
    "    import os\n",
    "    import pandas as pd\n",
    "    import glob\n",
    "    import time\n",
    "    \n",
    "    ### country naming dictionary\n",
    "    country_dict = {'ausl':'Australia', 'aus':'Australia',\n",
    "                  'aut':'Austria',\n",
    "                  'bel':'Belgium',\n",
    "                  'bgr':'Bulgaria',\n",
    "                  'blr':'Belarus',\n",
    "                  'can':'Canada',\n",
    "                  'che':'Switzerland',\n",
    "                  'cyp':'Cyprus',\n",
    "                  'cze':'CzechRepublic',\n",
    "                  'deu':'Germany',\n",
    "                  'dnk':'Denmark',\n",
    "                  'esp':'Spain',\n",
    "                  'est':'Estonia',\n",
    "                  'eua':'European Union',\n",
    "                  'fin':'Finland',\n",
    "                  'fra':'France',\n",
    "                  'frk':'France',\n",
    "                  'gbk':'United Kingdom', 'gbr':'United Kingdom',\n",
    "                  'grc':'Greece',\n",
    "                  'hrv':'Croatia',\n",
    "                  'hun':'Hungary',\n",
    "                  'irl':'Ireland',\n",
    "                  'isl':'Iceland',\n",
    "                  'ita':'Italy',\n",
    "                  'jpn':'Japan',\n",
    "                  'kaz':'Kazakhstan', 'Kaz':'Kazakhstan',\n",
    "                  'lie':'Liechtenstein',\n",
    "                  'ltu':'Lithuania',\n",
    "                  'lux':'Luxembourg',\n",
    "                  'lva':'Latvia',\n",
    "                  'mco':'Monaco',\n",
    "                  'mlt':'Malta',\n",
    "                  'nld':'Netherlands',\n",
    "                  'nor':'Norway',\n",
    "                  'nzl':'New Zealand',\n",
    "                  'pol':'Poland',\n",
    "                  'prt':'Portugal',\n",
    "                  'rou':'Romania',\n",
    "                  'rus':'Russian Federation',\n",
    "                  'svk':'Slovakia',\n",
    "                  'svn':'Slovenia',\n",
    "                  'swe':'Sweden',\n",
    "                  'tur':'Turkey',\n",
    "                  'ukr':'Ukraine',\n",
    "                  'usa':'United States'}\n",
    "\n",
    "    ### Check if correct file structure for year exists:\n",
    "    print(\"Checking folder structure...\")\n",
    "    if os.path.isdir(data_path+year) == False:\n",
    "        os.mkdir(data_path+year)\n",
    "        os.mkdir(data_path+year+\"\\\\data\")\n",
    "        os.mkdir(data_path+year+\"\\\\data\\\\zip\")\n",
    "    elif os.path.isdir(data_path+year+\"\\\\data\") == False:\n",
    "        os.mkdir(data_path+year+\"\\\\data\")\n",
    "        os.mkdir(data_path+year+\"\\\\data\\\\zip\")\n",
    "    else:\n",
    "        print(\"...Folder structure correct\")\n",
    "    zip_dir = data_path+year+r'/data/zip/'\n",
    "\n",
    "    \n",
    "    print(\"\\nScaping \",year,\" UNFCCC country CRF URLs...\")\n",
    "\n",
    "    ### set website to look at:\n",
    "    #website = \"https://unfccc.int/process-and-meetings/transparency-and-reporting/reporting-and-review-under-the-convention/greenhouse-gas-inventories-annex-i-parties/national-inventory-submissions-\"+year\n",
    "    website = \"https://unfccc.int/ghg-inventories-annex-i-parties/\"+year\n",
    "\n",
    "    ### Setup system to run the web scraping\n",
    "    chrome_options = Options()\n",
    "    #chrome_options.add_argument(\"--headless\")\n",
    "    prefs = {}\n",
    "    prefs[\"profile.default_content_settings.popups\"]=0\n",
    "    prefs[\"download.default_directory\"]='C:\\\\Users\\\\amar1\\\\UNFCCC_data_local\\\\2022\\\\data\\\\zip\\\\'#zip_dir\n",
    "    chrome_options.add_experimental_option(\"prefs\", prefs)\n",
    "    chrome_options.binary_location = r'C:\\Program Files\\Google\\Chrome\\Application\\chrome.exe'\n",
    "    driver = webdriver.Chrome(executable_path= r'C:/Users/amar1/Downloads/chromedriver_win32/chromedriver.exe',\n",
    "                              chrome_options=chrome_options)\n",
    "\n",
    "    ### Scrape website\n",
    "    driver.get(website)\n",
    "\n",
    "\n",
    "    results = driver.find_elements(\"css selector\",\"tbody\")\n",
    "\n",
    "    # create empty array to store data\n",
    "    unfccc_urls = []\n",
    "    # loop over results\n",
    "    for result in results:\n",
    "        lines = result.find_elements(\"tag name\" ,\"tr\")\n",
    "        for line in lines:\n",
    "            temp = []\n",
    "            country = line.find_elements(\"tag name\" ,\"th\")[0].text\n",
    "            temp.append(country)\n",
    "            sdate = line.find_elements(\"tag name\" ,\"td\")[0].text\n",
    "            if any(map(str.isdigit, sdate)) == False:\n",
    "                blank = [\"NaN\", \"NaN\", \"NaN\"]\n",
    "                temp.extend(blank)\n",
    "            else:\n",
    "                temp.append(sdate)\n",
    "                crf_check = line.find_elements(\"tag name\" ,\"a\")[0].text\n",
    "                if len(crf_check) > 3:\n",
    "                    crf_check_temp = crf_check.split(\" \")\n",
    "                    crf_check = crf_check_temp[0]\n",
    "                if crf_check == 'CRF':\n",
    "                    link = line.find_elements(\"tag name\" ,\"a\")[0]\n",
    "                else:\n",
    "                    for ii in range(0,10):\n",
    "                        crf_check = line.find_elements(\"tag name\" ,\"a\")[ii].text\n",
    "                        if len(crf_check) > 3:\n",
    "                            crf_check_temp = crf_check.split(\" \")\n",
    "                            crf_check = crf_check_temp[0]\n",
    "                        link = line.find_elements(\"tag name\" ,\"a\")[ii]\n",
    "                        if crf_check == 'CRF(Convention)': break\n",
    "                        elif crf_check == 'CRF': break\n",
    "                temp.append(crf_check)\n",
    "                base_link = link.get_attribute(\"href\")\n",
    "                temp.append(base_link)\n",
    "                # append dict to array\n",
    "            unfccc_urls.append(temp)\n",
    "\n",
    "    # close driver\n",
    "    driver.quit()\n",
    "\n",
    "    print(year,\" UNFCCC country CRF URLs scraped!!!\")\n",
    "\n",
    "\n",
    "    ### get url of zip files for UNFCCC CRF data\n",
    "    print(\"\\nScaping individual countries \",year,\" CRF zip file URLs...\")\n",
    "\n",
    "    for i in range(len(unfccc_urls)):\n",
    "        if unfccc_urls[i][1] != \"NaN\":\n",
    "            print(\"\\nScraping\", unfccc_urls[i][0], \"UNFCCC CRF URL...\")\n",
    "            driver = webdriver.Chrome(executable_path= r'C:\\Users\\amar1\\Downloads\\chromedriver_win32\\chromedriver.exe',   chrome_options=chrome_options)\n",
    "            driver.get(unfccc_urls[i][3])\n",
    "            link = driver.find_element(\"xpath\", \"/html/body/div[1]/div[3]/div/section/div/article/div/div/div[2]/div[1]/div/section[1]/div/div/a\")\n",
    "            zip_link = link.get_attribute(\"href\")\n",
    "            # add to unfccc_urls\n",
    "            unfccc_urls[i].append(zip_link)\n",
    "            print(unfccc_urls[i][0], \"UNFCCC CRF URL scraped!!!\")\n",
    "            driver.find_element(\"xpath\", \"/html/body/div[1]/div[3]/div/section/div/article/div/div/div[2]/div[1]/div/section[1]/div/div/a\").click()\n",
    "            print(unfccc_urls[i][0], \"UNFCCC CRF zip data downloaded!!!\")\n",
    "        else:\n",
    "            print(\"\\nNo\", unfccc_urls[i][0], \"UNFCCC CRF data to scrape!\")\n",
    "            unfccc_urls[i].append(\"NaN\")\n",
    "        time.sleep(15)\n",
    "        driver.quit()\n",
    "\n",
    "    ### Write csv with all scraped URLs\n",
    "    df = pd.DataFrame(unfccc_urls)\n",
    "    df.columns = [\"Country\", \"Submission_date\", \"Data_type\", \"Country_URL\", \"Data_URL\"]\n",
    "    df.to_csv(data_path+year+\"/scraped_urls.csv\")\n",
    "    \n",
    "    ### Check all files downloaded correctly\n",
    "    print(\"\\n...Checking\",year,\"scraped files...\")\n",
    "    all_zip_files = [f for f in glob.glob(data_path+year+\"/data/zip/*[!.zip]\", \n",
    "                                 recursive=False)]\n",
    "    for j in range(len(all_zip_files)):\n",
    "        import_country = country_dict[all_zip_files[j].split('/')[-1].split('-')[0]]\n",
    "        \n",
    "        for i in unfccc_urls:\n",
    "            if i[0] == import_country:\n",
    "                import_country_loc = i\n",
    "                break\n",
    "        \n",
    "        print(\"\\nRescraping\", import_country, \"UNFCCC CRF URL...\")\n",
    "        driver = webdriver.Chrome(executable_path= r'C:\\Users\\amar1\\Downloads\\chromedriver_win32\\chromedriver.exe',   chrome_options=chrome_options)\n",
    "        driver.get(import_country_loc[3])\n",
    "\n",
    "        driver.find_element(\"xpath\", \"/html/body/div[1]/div[3]/div/section/div/article/div/div/div[2]/div[1]/div/section[1]/div/div/a\").click()\n",
    "        print(import_country, \"UNFCCC CRF zip data downloaded!!!\")\n",
    "        \n",
    "        os.remove(all_zip_files[j])\n",
    "\n",
    "    print(\"\\n\",year,\"UNFCCC CRF zip file URLs scraped!!!\")\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "###############################################################################\n",
    "### unfccc_download\n",
    "###############################################################################\n",
    "\n",
    "def unfccc_unzip(year = '2021', data_path = '/Users/ks15697/Documents/Python/UNFCCC/'):\n",
    "    import os\n",
    "    import glob\n",
    "    from zipfile import ZipFile\n",
    "    from distutils.dir_util import copy_tree\n",
    "\n",
    "    # set the base directory\n",
    "    base_dir = data_path+year+\"/data/\"\n",
    "\n",
    "    ### country naming dictionary\n",
    "    names_dict = {'ausl':'Australia_NIR_'+year,\n",
    "                  'aus':'Australia_NIR_'+year,\n",
    "                  'aut':'Austria_NIR_'+year,\n",
    "                  'bel':'Belgium_NIR_'+year,\n",
    "                  'bgr':'Bulgaria_NIR_'+year,\n",
    "                  'blr':'Belarus_NIR_'+year,\n",
    "                  'can':'Canada_NIR_'+year,\n",
    "                  'che':'Switzerland_NIR_'+year,\n",
    "                  'cyp':'Cyprus_NIR_'+year,\n",
    "                  'cze':'CzechRepublic_NIR_'+year,\n",
    "                  'deu':'Germany_NIR_'+year,\n",
    "                  'dnk':'Denmark_NIR_'+year,\n",
    "                  'esp':'Spain_NIR_'+year,\n",
    "                  'est':'Estonia_NIR_'+year,\n",
    "                  'eua':'Europe_NIR_'+year,\n",
    "                  'fin':'Finland_NIR_'+year,\n",
    "                  'fra':'France_NIR_'+year,\n",
    "                  'frk':'France_NIR_'+year,\n",
    "                  'gbk':'UK_NIR_'+year,\n",
    "                  'gbr':'UK_NIR_'+year,\n",
    "                  'grc':'Greece_NIR_'+year,\n",
    "                  'hrv':'Croatia_NIR_'+year,\n",
    "                  'hun':'Hungary_NIR_'+year,\n",
    "                  'irl':'Ireland_NIR_'+year,\n",
    "                  'isl':'Iceland_NIR_'+year,\n",
    "                  'ita':'Italy_NIR_'+year,\n",
    "                  'jpn':'Japan_NIR_'+year,\n",
    "                  'kaz':'Kazakhstan_NIR_'+year,\n",
    "                  'Kaz':'Kazakhstan_NIR_'+year,\n",
    "                  'lie':'Liechtenstein_NIR_'+year,\n",
    "                  'ltu':'Lithuania_NIR_'+year,\n",
    "                  'lux':'Luxembourg_NIR_'+year,\n",
    "                  'lva':'Latvia_NIR_'+year,\n",
    "                  'mco':'Monaco_NIR_'+year,\n",
    "                  'mlt':'Malta_NIR_'+year,\n",
    "                  'nld':'Netherlands_NIR_'+year,\n",
    "                  'nor':'Norway_NIR_'+year,\n",
    "                  'nzl':'NewZealand_NIR_'+year,\n",
    "                  'pol':'Poland_NIR_'+year,\n",
    "                  'prt':'Portugal_NIR_'+year,\n",
    "                  'rou':'Romania_NIR_'+year,\n",
    "                  'rus':'Russia_NIR_'+year,\n",
    "                  'svk':'Slovakia_NIR_'+year,\n",
    "                  'svn':'Slovenia_NIR_'+year,\n",
    "                  'swe':'Sweden_NIR_'+year,\n",
    "                  'tur':'Turkey_NIR_'+year,\n",
    "                  'ukr':'Ukraine_NIR_'+year,\n",
    "                  'usa':'USA_NIR_'+year}\n",
    "\n",
    "\n",
    "    ### Unzip downloaded data\n",
    "    filelis = sorted([f for f in os.listdir(base_dir+\"zip/\") if f.endswith('.zip')])\n",
    "\n",
    "    print(\"Unzipping UNFCCC CRF data...\")\n",
    "\n",
    "    for j in range(len(filelis)):\n",
    "        acronym = filelis[j].split(\"-\")\n",
    "        print(\"... \", acronym[0])\n",
    "        # Make a folder for the files\n",
    "        country_path = base_dir+names_dict[acronym[0]]\n",
    "        os.mkdir(country_path)\n",
    "        # Create a ZipFile Object and load sample.zip in it\n",
    "        zip_path = base_dir + \"zip/\" + filelis[j]\n",
    "        with ZipFile(zip_path, 'r') as zipObj:\n",
    "            # Extract all the contents of zip file in different directory\n",
    "            zipObj.extractall(country_path)\n",
    "        print(acronym[0], \" done!\")\n",
    "\n",
    "    print(\"Checking data...\")\n",
    "    ignored = {\"zip\", \".DS_Store\"}\n",
    "    dirlis = [x for x in os.listdir(base_dir) if x not in ignored]\n",
    "    for jj in dirlis:\n",
    "        subdir = base_dir + jj + \"/\"\n",
    "        subdir_test = set([os.path.dirname(subdir) for p in glob.glob(subdir +\"*/*\")])\n",
    "        if len(subdir_test) > 0:\n",
    "            print(\"Copying \",jj,\" subfolder data to correct directory...\")\n",
    "            copydir = os.listdir(subdir)\n",
    "            copy_tree(subdir + copydir[0], subdir)\n",
    "\n",
    "\n",
    "    print(\"All UNFCCC CRF files unzipped!!!\")\n",
    "\n",
    "###############################################################################\n",
    "### crf_import_ch4\n",
    "###############################################################################\n",
    "\n",
    "def crf_import_ch4(year = '2022', data_path = '/Users/ks15697/Documents/Python/UNFCCC/'): \n",
    "    import os\n",
    "    import pandas as pd\n",
    "    import csv\n",
    "    import numpy as np\n",
    "\n",
    "    ### Add folder for processed data to be stored in\n",
    "    if os.path.isdir(data_path+year+\"/processed_data/\") == False:\n",
    "        os.mkdir(data_path+year+\"/processed_data/\")\n",
    "        os.mkdir(data_path+year+\"/processed_data/totals/\")\n",
    "        os.mkdir(data_path+year+\"/processed_data/totals_co2/\")\n",
    "        os.mkdir(data_path+year+\"/processed_data/species_specific/\")\n",
    "    if os.path.isdir(data_path+year+\"/processed_data/totals/\") == False:\n",
    "        os.mkdir(data_path+year+\"/processed_data/totals/\")\n",
    "    if os.path.isdir(data_path+year+\"/processed_data/totals_co2/\") == False:\n",
    "        os.mkdir(data_path+year+\"/processed_data/totals_co2/\")\n",
    "    if os.path.isdir(data_path+year+\"/processed_data/species_specific/\") == False:\n",
    "        os.mkdir(data_path+year+\"/processed_data/species_specific/\")\n",
    "\n",
    "    ### Create lists for each gas to go into for country totals\n",
    "\n",
    "    ### Can this be changed to create lists for each YEAR (headers for Table10s3 are years rather than gases)???\n",
    "\n",
    "    years = [\"Year\", \"base_year\"]\n",
    "    years_list = [str(i) for i in range(1990,int(year)-1)]\n",
    "    years.extend(years_list)\n",
    "    years.extend([\"change_from_baseline\"])\n",
    "\n",
    "    ### Import each country data\n",
    "    print(\"Importing CRF data...\")\n",
    "\n",
    "    ### Create list of folders within data_path/year/data/\n",
    "    folderlis = sorted([f for f in os.listdir(data_path+year+\"/data/\") if f.endswith(year)])\n",
    "\n",
    "    #for k in folderlis:\n",
    "        #crf_list = sorted(os.listdir(data_path+year+\\\"/data/\\\"+k))\n",
    "    crf_list = sorted([f for f in os.listdir(data_path+year+\"/data/UK_NIR_2022\") if f.endswith('xlsx')])\n",
    "    country_name = \"UK_NIR_2022\".split(\"_\")\n",
    "    print(\"...\", country_name[0], \"CRF data\")\n",
    "        \n",
    "        ### Read in country data\n",
    "    xls = pd.ExcelFile(data_path+year+\"/data/\"+\"UK_NIR_2022\"+\"/\"+crf_list[-1])\n",
    "    crf = pd.read_excel(xls, 'Table10s3', header = 4)\n",
    "    \n",
    "    return crf\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "e0b11f3c-98c8-43ed-afe2-7ba03d6ef05b",
   "metadata": {},
   "outputs": [],
   "source": [
    "###############################################################################\n",
    "### crf_import_n2o\n",
    "###############################################################################\n",
    "\n",
    "def crf_import_n2o(year = '2022', data_path = '/Users/ks15697/Documents/Python/UNFCCC/'): \n",
    "    import os\n",
    "    import pandas as pd\n",
    "    import csv\n",
    "    import numpy as np\n",
    "\n",
    "    ### Add folder for processed data to be stored in\n",
    "    if os.path.isdir(data_path+year+\"/processed_data/\") == False:\n",
    "        os.mkdir(data_path+year+\"/processed_data/\")\n",
    "        os.mkdir(data_path+year+\"/processed_data/totals/\")\n",
    "        os.mkdir(data_path+year+\"/processed_data/totals_co2/\")\n",
    "        os.mkdir(data_path+year+\"/processed_data/species_specific/\")\n",
    "    if os.path.isdir(data_path+year+\"/processed_data/totals/\") == False:\n",
    "        os.mkdir(data_path+year+\"/processed_data/totals/\")\n",
    "    if os.path.isdir(data_path+year+\"/processed_data/totals_co2/\") == False:\n",
    "        os.mkdir(data_path+year+\"/processed_data/totals_co2/\")\n",
    "    if os.path.isdir(data_path+year+\"/processed_data/species_specific/\") == False:\n",
    "        os.mkdir(data_path+year+\"/processed_data/species_specific/\")\n",
    "\n",
    "    ### Create lists for each gas to go into for country totals\n",
    "\n",
    "    ### Can this be changed to create lists for each YEAR (headers for Table10s3 are years rather than gases)???\n",
    "\n",
    "    years = [\"Year\", \"base_year\"]\n",
    "    years_list = [str(i) for i in range(1990,int(year)-1)]\n",
    "    years.extend(years_list)\n",
    "    years.extend([\"change_from_baseline\"])\n",
    "\n",
    "    ### Import each country data\n",
    "    print(\"Importing CRF data...\")\n",
    "\n",
    "    ### Create list of folders within data_path/year/data/\n",
    "    folderlis = sorted([f for f in os.listdir(data_path+year+\"/data/\") if f.endswith(year)])\n",
    "\n",
    "    #for k in folderlis:\n",
    "        #crf_list = sorted(os.listdir(data_path+year+\\\"/data/\\\"+k))\n",
    "    crf_list = sorted([f for f in os.listdir(data_path+year+\"/data/UK_NIR_2022\") if f.endswith('xlsx')])\n",
    "    country_name = \"UK_NIR_2022\".split(\"_\")\n",
    "    print(\"...\", country_name[0], \"CRF data\")\n",
    "        \n",
    "        ### Read in country data\n",
    "    xls = pd.ExcelFile(data_path+year+\"/data/\"+\"UK_NIR_2022\"+\"/\"+crf_list[-1])\n",
    "    crf = pd.read_excel(xls, 'Table10s4', header = 4)\n",
    "    \n",
    "    return crf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0e99a31e-1a83-4178-a5a4-4a3f12f234b8",
   "metadata": {},
   "outputs": [],
   "source": [
    "unfccc_scrape(year = '2022', data_path = r'C:/Users/amar1/UNFCCC_data_local/')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4e9075ec-b3b5-4438-9512-7ab80b734513",
   "metadata": {},
   "outputs": [],
   "source": [
    "unfccc_unzip(year=\"2022\", data_path = r'C:/Users/amar1/UNFCCC_data_local/')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "4f7fc489-d19f-412f-8c86-ce4c290be759",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Importing CRF data...\n",
      "... UK CRF data\n"
     ]
    },
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>GREENHOUSE GAS SOURCE AND SINK CATEGORIES</th>\n",
       "      <th>Base year(1)</th>\n",
       "      <th>1990</th>\n",
       "      <th>1991</th>\n",
       "      <th>1992</th>\n",
       "      <th>1993</th>\n",
       "      <th>1994</th>\n",
       "      <th>1995</th>\n",
       "      <th>1996</th>\n",
       "      <th>1997</th>\n",
       "      <th>...</th>\n",
       "      <th>2012</th>\n",
       "      <th>2013</th>\n",
       "      <th>2014</th>\n",
       "      <th>2015</th>\n",
       "      <th>2016</th>\n",
       "      <th>2017</th>\n",
       "      <th>2018</th>\n",
       "      <th>2019</th>\n",
       "      <th>2020</th>\n",
       "      <th>Change from base to latest reported year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>(kt)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1. Energy</td>\n",
       "      <td>1496.198346</td>\n",
       "      <td>1496.198346</td>\n",
       "      <td>1516.883409</td>\n",
       "      <td>1498.019022</td>\n",
       "      <td>1420.993629</td>\n",
       "      <td>1120.636638</td>\n",
       "      <td>1154.969761</td>\n",
       "      <td>1092.643012</td>\n",
       "      <td>1006.961661</td>\n",
       "      <td>...</td>\n",
       "      <td>384.369606</td>\n",
       "      <td>337.847767</td>\n",
       "      <td>320.953039</td>\n",
       "      <td>303.773576</td>\n",
       "      <td>265.857528</td>\n",
       "      <td>263.057614</td>\n",
       "      <td>262.56135</td>\n",
       "      <td>253.997777</td>\n",
       "      <td>235.556764</td>\n",
       "      <td>-84.256314</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>A. Fuel combustion (sectoral approach)</td>\n",
       "      <td>129.43946</td>\n",
       "      <td>129.43946</td>\n",
       "      <td>134.46966</td>\n",
       "      <td>127.281609</td>\n",
       "      <td>130.133233</td>\n",
       "      <td>118.014832</td>\n",
       "      <td>102.281655</td>\n",
       "      <td>102.989162</td>\n",
       "      <td>95.268341</td>\n",
       "      <td>...</td>\n",
       "      <td>43.364553</td>\n",
       "      <td>44.386653</td>\n",
       "      <td>43.105705</td>\n",
       "      <td>45.153607</td>\n",
       "      <td>46.465766</td>\n",
       "      <td>47.673054</td>\n",
       "      <td>49.478277</td>\n",
       "      <td>49.131183</td>\n",
       "      <td>48.218358</td>\n",
       "      <td>-62.748332</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1.  Energy industries</td>\n",
       "      <td>9.327453</td>\n",
       "      <td>9.327453</td>\n",
       "      <td>9.296994</td>\n",
       "      <td>9.501829</td>\n",
       "      <td>9.922269</td>\n",
       "      <td>10.060215</td>\n",
       "      <td>10.488551</td>\n",
       "      <td>10.775702</td>\n",
       "      <td>11.090562</td>\n",
       "      <td>...</td>\n",
       "      <td>11.252326</td>\n",
       "      <td>11.241765</td>\n",
       "      <td>12.737843</td>\n",
       "      <td>13.304238</td>\n",
       "      <td>14.164167</td>\n",
       "      <td>14.788899</td>\n",
       "      <td>15.170421</td>\n",
       "      <td>15.508386</td>\n",
       "      <td>15.282</td>\n",
       "      <td>63.838936</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2.  Manufacturing industries and construction</td>\n",
       "      <td>4.589083</td>\n",
       "      <td>4.589083</td>\n",
       "      <td>4.711231</td>\n",
       "      <td>4.728609</td>\n",
       "      <td>4.377738</td>\n",
       "      <td>4.663597</td>\n",
       "      <td>4.541524</td>\n",
       "      <td>4.210813</td>\n",
       "      <td>3.877838</td>\n",
       "      <td>...</td>\n",
       "      <td>3.38953</td>\n",
       "      <td>3.569429</td>\n",
       "      <td>4.073298</td>\n",
       "      <td>4.273278</td>\n",
       "      <td>4.37072</td>\n",
       "      <td>4.833171</td>\n",
       "      <td>5.192234</td>\n",
       "      <td>5.1501</td>\n",
       "      <td>5.366701</td>\n",
       "      <td>16.944962</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>Long-term storage of C in waste disposal sites</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>Indirect N2O</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>Indirect CO2 (3)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>Note: All footnotes for this table are given a...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>62 rows × 34 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            GREENHOUSE GAS SOURCE AND SINK CATEGORIES Base year(1)  \\\n",
       "0                                                 NaN         (kt)   \n",
       "1                                           1. Energy  1496.198346   \n",
       "2              A. Fuel combustion (sectoral approach)    129.43946   \n",
       "3                               1.  Energy industries     9.327453   \n",
       "4       2.  Manufacturing industries and construction     4.589083   \n",
       "..                                                ...          ...   \n",
       "57     Long-term storage of C in waste disposal sites          NaN   \n",
       "58                                       Indirect N2O          NaN   \n",
       "59                                   Indirect CO2 (3)          NaN   \n",
       "60                                                NaN          NaN   \n",
       "61  Note: All footnotes for this table are given a...          NaN   \n",
       "\n",
       "           1990         1991         1992         1993         1994  \\\n",
       "0           NaN          NaN          NaN          NaN          NaN   \n",
       "1   1496.198346  1516.883409  1498.019022  1420.993629  1120.636638   \n",
       "2     129.43946    134.46966   127.281609   130.133233   118.014832   \n",
       "3      9.327453     9.296994     9.501829     9.922269    10.060215   \n",
       "4      4.589083     4.711231     4.728609     4.377738     4.663597   \n",
       "..          ...          ...          ...          ...          ...   \n",
       "57          NaN          NaN          NaN          NaN          NaN   \n",
       "58          NaN          NaN          NaN          NaN          NaN   \n",
       "59          NaN          NaN          NaN          NaN          NaN   \n",
       "60          NaN          NaN          NaN          NaN          NaN   \n",
       "61          NaN          NaN          NaN          NaN          NaN   \n",
       "\n",
       "           1995         1996         1997  ...        2012        2013  \\\n",
       "0           NaN          NaN          NaN  ...         NaN         NaN   \n",
       "1   1154.969761  1092.643012  1006.961661  ...  384.369606  337.847767   \n",
       "2    102.281655   102.989162    95.268341  ...   43.364553   44.386653   \n",
       "3     10.488551    10.775702    11.090562  ...   11.252326   11.241765   \n",
       "4      4.541524     4.210813     3.877838  ...     3.38953    3.569429   \n",
       "..          ...          ...          ...  ...         ...         ...   \n",
       "57          NaN          NaN          NaN  ...         NaN         NaN   \n",
       "58          NaN          NaN          NaN  ...         NaN         NaN   \n",
       "59          NaN          NaN          NaN  ...         NaN         NaN   \n",
       "60          NaN          NaN          NaN  ...         NaN         NaN   \n",
       "61          NaN          NaN          NaN  ...         NaN         NaN   \n",
       "\n",
       "          2014        2015        2016        2017       2018        2019  \\\n",
       "0          NaN         NaN         NaN         NaN        NaN         NaN   \n",
       "1   320.953039  303.773576  265.857528  263.057614  262.56135  253.997777   \n",
       "2    43.105705   45.153607   46.465766   47.673054  49.478277   49.131183   \n",
       "3    12.737843   13.304238   14.164167   14.788899  15.170421   15.508386   \n",
       "4     4.073298    4.273278     4.37072    4.833171   5.192234      5.1501   \n",
       "..         ...         ...         ...         ...        ...         ...   \n",
       "57         NaN         NaN         NaN         NaN        NaN         NaN   \n",
       "58         NaN         NaN         NaN         NaN        NaN         NaN   \n",
       "59         NaN         NaN         NaN         NaN        NaN         NaN   \n",
       "60         NaN         NaN         NaN         NaN        NaN         NaN   \n",
       "61         NaN         NaN         NaN         NaN        NaN         NaN   \n",
       "\n",
       "          2020 Change from base to latest reported year  \n",
       "0          NaN                                        %  \n",
       "1   235.556764                               -84.256314  \n",
       "2    48.218358                               -62.748332  \n",
       "3       15.282                                63.838936  \n",
       "4     5.366701                                16.944962  \n",
       "..         ...                                      ...  \n",
       "57         NaN                                      NaN  \n",
       "58         NaN                                      NaN  \n",
       "59         NaN                                      NaN  \n",
       "60         NaN                                      NaN  \n",
       "61         NaN                                      NaN  \n",
       "\n",
       "[62 rows x 34 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ch4 = crf_import_ch4(year = '2022', data_path = r'C:/Users/amar1/UNFCCC_data_local/')\n",
    "ch4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "68ade39f-e780-4718-aec2-9d84cab6b9f9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Importing CRF data...\n",
      "... UK CRF data\n"
     ]
    },
    {
     "data": {
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>GREENHOUSE GAS SOURCE AND SINK CATEGORIES</th>\n",
       "      <th>Base year(1)</th>\n",
       "      <th>1990</th>\n",
       "      <th>1991</th>\n",
       "      <th>1992</th>\n",
       "      <th>1993</th>\n",
       "      <th>1994</th>\n",
       "      <th>1995</th>\n",
       "      <th>1996</th>\n",
       "      <th>1997</th>\n",
       "      <th>...</th>\n",
       "      <th>2012</th>\n",
       "      <th>2013</th>\n",
       "      <th>2014</th>\n",
       "      <th>2015</th>\n",
       "      <th>2016</th>\n",
       "      <th>2017</th>\n",
       "      <th>2018</th>\n",
       "      <th>2019</th>\n",
       "      <th>2020</th>\n",
       "      <th>Change from base to latest reported year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>(kt)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1. Energy</td>\n",
       "      <td>12.399834</td>\n",
       "      <td>12.399834</td>\n",
       "      <td>12.32051</td>\n",
       "      <td>12.126234</td>\n",
       "      <td>12.005137</td>\n",
       "      <td>12.267934</td>\n",
       "      <td>12.600877</td>\n",
       "      <td>12.107575</td>\n",
       "      <td>11.725449</td>\n",
       "      <td>...</td>\n",
       "      <td>8.71365</td>\n",
       "      <td>8.628428</td>\n",
       "      <td>8.386046</td>\n",
       "      <td>8.46204</td>\n",
       "      <td>7.961422</td>\n",
       "      <td>7.92665</td>\n",
       "      <td>8.042293</td>\n",
       "      <td>7.921735</td>\n",
       "      <td>7.227956</td>\n",
       "      <td>-41.709255</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>A. Fuel combustion (sectoral approach)</td>\n",
       "      <td>12.249575</td>\n",
       "      <td>12.249575</td>\n",
       "      <td>12.174791</td>\n",
       "      <td>11.978783</td>\n",
       "      <td>11.850275</td>\n",
       "      <td>12.075453</td>\n",
       "      <td>12.397266</td>\n",
       "      <td>11.899059</td>\n",
       "      <td>11.539965</td>\n",
       "      <td>...</td>\n",
       "      <td>8.58924</td>\n",
       "      <td>8.510284</td>\n",
       "      <td>8.268197</td>\n",
       "      <td>8.342556</td>\n",
       "      <td>7.838041</td>\n",
       "      <td>7.802034</td>\n",
       "      <td>7.916938</td>\n",
       "      <td>7.797677</td>\n",
       "      <td>7.124227</td>\n",
       "      <td>-41.841029</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1.  Energy industries</td>\n",
       "      <td>4.821621</td>\n",
       "      <td>4.821621</td>\n",
       "      <td>4.773376</td>\n",
       "      <td>4.616961</td>\n",
       "      <td>4.171165</td>\n",
       "      <td>4.055918</td>\n",
       "      <td>3.990189</td>\n",
       "      <td>3.837661</td>\n",
       "      <td>3.603327</td>\n",
       "      <td>...</td>\n",
       "      <td>3.835712</td>\n",
       "      <td>3.716935</td>\n",
       "      <td>3.326995</td>\n",
       "      <td>3.210666</td>\n",
       "      <td>2.553062</td>\n",
       "      <td>2.390532</td>\n",
       "      <td>2.417321</td>\n",
       "      <td>2.39708</td>\n",
       "      <td>2.352618</td>\n",
       "      <td>-51.206911</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2.  Manufacturing industries and construction</td>\n",
       "      <td>1.058335</td>\n",
       "      <td>1.058335</td>\n",
       "      <td>1.052081</td>\n",
       "      <td>1.042331</td>\n",
       "      <td>1.008378</td>\n",
       "      <td>1.046156</td>\n",
       "      <td>1.009588</td>\n",
       "      <td>0.97332</td>\n",
       "      <td>0.921806</td>\n",
       "      <td>...</td>\n",
       "      <td>0.690587</td>\n",
       "      <td>0.63024</td>\n",
       "      <td>0.700639</td>\n",
       "      <td>0.748686</td>\n",
       "      <td>0.754312</td>\n",
       "      <td>0.826021</td>\n",
       "      <td>0.880824</td>\n",
       "      <td>0.837112</td>\n",
       "      <td>0.841022</td>\n",
       "      <td>-20.533441</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>Long-term storage of C in waste disposal sites</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>Indirect N2O</td>\n",
       "      <td>14.114362</td>\n",
       "      <td>14.114362</td>\n",
       "      <td>13.794607</td>\n",
       "      <td>13.49868</td>\n",
       "      <td>12.859003</td>\n",
       "      <td>12.717212</td>\n",
       "      <td>12.277937</td>\n",
       "      <td>11.847634</td>\n",
       "      <td>11.073066</td>\n",
       "      <td>...</td>\n",
       "      <td>6.079931</td>\n",
       "      <td>5.759218</td>\n",
       "      <td>5.395422</td>\n",
       "      <td>5.219106</td>\n",
       "      <td>4.753065</td>\n",
       "      <td>4.628073</td>\n",
       "      <td>4.420606</td>\n",
       "      <td>4.182834</td>\n",
       "      <td>3.69858</td>\n",
       "      <td>-73.79563</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>Indirect CO2 (3)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>Note: All footnotes for this table are given a...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>62 rows × 34 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            GREENHOUSE GAS SOURCE AND SINK CATEGORIES Base year(1)       1990  \\\n",
       "0                                                 NaN         (kt)        NaN   \n",
       "1                                           1. Energy    12.399834  12.399834   \n",
       "2              A. Fuel combustion (sectoral approach)    12.249575  12.249575   \n",
       "3                               1.  Energy industries     4.821621   4.821621   \n",
       "4       2.  Manufacturing industries and construction     1.058335   1.058335   \n",
       "..                                                ...          ...        ...   \n",
       "57     Long-term storage of C in waste disposal sites          NaN        NaN   \n",
       "58                                       Indirect N2O    14.114362  14.114362   \n",
       "59                                   Indirect CO2 (3)          NaN        NaN   \n",
       "60                                                NaN          NaN        NaN   \n",
       "61  Note: All footnotes for this table are given a...          NaN        NaN   \n",
       "\n",
       "         1991       1992       1993       1994       1995       1996  \\\n",
       "0         NaN        NaN        NaN        NaN        NaN        NaN   \n",
       "1    12.32051  12.126234  12.005137  12.267934  12.600877  12.107575   \n",
       "2   12.174791  11.978783  11.850275  12.075453  12.397266  11.899059   \n",
       "3    4.773376   4.616961   4.171165   4.055918   3.990189   3.837661   \n",
       "4    1.052081   1.042331   1.008378   1.046156   1.009588    0.97332   \n",
       "..        ...        ...        ...        ...        ...        ...   \n",
       "57        NaN        NaN        NaN        NaN        NaN        NaN   \n",
       "58  13.794607   13.49868  12.859003  12.717212  12.277937  11.847634   \n",
       "59        NaN        NaN        NaN        NaN        NaN        NaN   \n",
       "60        NaN        NaN        NaN        NaN        NaN        NaN   \n",
       "61        NaN        NaN        NaN        NaN        NaN        NaN   \n",
       "\n",
       "         1997  ...      2012      2013      2014      2015      2016  \\\n",
       "0         NaN  ...       NaN       NaN       NaN       NaN       NaN   \n",
       "1   11.725449  ...   8.71365  8.628428  8.386046   8.46204  7.961422   \n",
       "2   11.539965  ...   8.58924  8.510284  8.268197  8.342556  7.838041   \n",
       "3    3.603327  ...  3.835712  3.716935  3.326995  3.210666  2.553062   \n",
       "4    0.921806  ...  0.690587   0.63024  0.700639  0.748686  0.754312   \n",
       "..        ...  ...       ...       ...       ...       ...       ...   \n",
       "57        NaN  ...       NaN       NaN       NaN       NaN       NaN   \n",
       "58  11.073066  ...  6.079931  5.759218  5.395422  5.219106  4.753065   \n",
       "59        NaN  ...       NaN       NaN       NaN       NaN       NaN   \n",
       "60        NaN  ...       NaN       NaN       NaN       NaN       NaN   \n",
       "61        NaN  ...       NaN       NaN       NaN       NaN       NaN   \n",
       "\n",
       "        2017      2018      2019      2020  \\\n",
       "0        NaN       NaN       NaN       NaN   \n",
       "1    7.92665  8.042293  7.921735  7.227956   \n",
       "2   7.802034  7.916938  7.797677  7.124227   \n",
       "3   2.390532  2.417321   2.39708  2.352618   \n",
       "4   0.826021  0.880824  0.837112  0.841022   \n",
       "..       ...       ...       ...       ...   \n",
       "57       NaN       NaN       NaN       NaN   \n",
       "58  4.628073  4.420606  4.182834   3.69858   \n",
       "59       NaN       NaN       NaN       NaN   \n",
       "60       NaN       NaN       NaN       NaN   \n",
       "61       NaN       NaN       NaN       NaN   \n",
       "\n",
       "   Change from base to latest reported year  \n",
       "0                                         %  \n",
       "1                                -41.709255  \n",
       "2                                -41.841029  \n",
       "3                                -51.206911  \n",
       "4                                -20.533441  \n",
       "..                                      ...  \n",
       "57                                      NaN  \n",
       "58                                -73.79563  \n",
       "59                                      NaN  \n",
       "60                                      NaN  \n",
       "61                                      NaN  \n",
       "\n",
       "[62 rows x 34 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "n2o = crf_import_n2o(year = '2022', data_path = r'C:/Users/amar1/UNFCCC_data_local/')\n",
    "n2o"
   ]
  }
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