{ "nbformat": 4, "nbformat_minor": 0, "metadata": { "colab": { "name": "Kaggle_EPL1.ipynb", "provenance": [], "collapsed_sections": [], "include_colab_link": true }, "kernelspec": { "name": "python3", "display_name": "Python 3" } }, "cells": [ { "cell_type": "markdown", "metadata": { "id": "view-in-github", "colab_type": "text" }, "source": [ "\"Open" ] }, { "cell_type": "markdown", "source": [ "Data source: http://www.kaggle.com\n" ], "metadata": { "id": "XZ3aTtRmZn3d" } }, { "metadata": { "id": "DIf2PtekjPtY" }, "cell_type": "markdown", "source": [ "# Installing the [Kaggle API](https://github.com/Kaggle/kaggle-api) in Colab" ] }, { "cell_type": "code", "source": [ "from google.colab import drive\n", "drive.mount('/content/drive')" ], "metadata": { "id": "-qO6K2shH1of", "outputId": "a2af26b0-0ce5-4e21-e9af-5060a96aebb3", "colab": { "base_uri": "https://localhost:8080/" } }, "execution_count": 1, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Mounted at /content/drive\n" ] } ] }, { "metadata": { "id": "OppyMnCuWjzJ", "colab": { "base_uri": "https://localhost:8080/" }, "outputId": "d869e27c-d4af-4ea1-9d28-fc5f6f767b73" }, "cell_type": "code", "source": [ "!pip install kaggle" ], "execution_count": 25, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Requirement already satisfied: kaggle in /usr/local/lib/python3.7/dist-packages (1.5.12)\n", "Requirement already satisfied: six>=1.10 in /usr/local/lib/python3.7/dist-packages (from kaggle) (1.15.0)\n", "Requirement already satisfied: certifi in /usr/local/lib/python3.7/dist-packages (from kaggle) (2021.10.8)\n", "Requirement already satisfied: python-slugify in /usr/local/lib/python3.7/dist-packages (from kaggle) (6.1.2)\n", "Requirement already satisfied: tqdm in /usr/local/lib/python3.7/dist-packages (from kaggle) (4.64.0)\n", "Requirement already satisfied: requests in /usr/local/lib/python3.7/dist-packages (from kaggle) (2.23.0)\n", "Requirement already satisfied: urllib3 in /usr/local/lib/python3.7/dist-packages (from kaggle) (1.24.3)\n", "Requirement already satisfied: python-dateutil in /usr/local/lib/python3.7/dist-packages (from kaggle) (2.8.2)\n", "Requirement already satisfied: text-unidecode>=1.3 in /usr/local/lib/python3.7/dist-packages (from python-slugify->kaggle) (1.3)\n", "Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.7/dist-packages (from requests->kaggle) (3.0.4)\n", "Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.7/dist-packages (from requests->kaggle) (2.10)\n" ] } ] }, { "metadata": { "id": "hMY4CFezjcG-" }, "cell_type": "markdown", "source": [ "# Authenticating with Kaggle using kaggle.json\n", "\n", "Navigate to https://www.kaggle.com. Then go to the [Account tab of your user profile](https://www.kaggle.com/me/account) and select Create API Token. This will trigger the download of kaggle.json, a file containing your API credentials.\n", "\n", "Make sure you expire all other API keys first. \n", "\n", "Then run the cell below to upload kaggle.json to your Colab runtime." ] }, { "metadata": { "id": "0HtGf0HEXEa5", "outputId": "1dcf6956-aac3-4b74-d70d-593249b121e9", "colab": { "resources": { "http://localhost:8080/nbextensions/google.colab/files.js": { "data": "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", "ok": true, "headers": [ [ "content-type", "application/javascript" ] ], "status": 200, "status_text": "" } }, "base_uri": "https://localhost:8080/", "height": 90 } }, "cell_type": "code", "source": [ "from google.colab import files\n", "\n", "uploaded = files.upload()\n", "\n", "for fn in uploaded.keys():\n", " print('User uploaded file \"{name}\" with length {length} bytes'.format(\n", " name=fn, length=len(uploaded[fn])))\n", " \n", "# Then move kaggle.json into the folder where the API expects to find it.\n", "!mkdir -p ~/.kaggle/ && mv kaggle.json ~/.kaggle/ && chmod 600 ~/.kaggle/kaggle.json" ], "execution_count": 4, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "" ], "text/html": [ "\n", " \n", " \n", " Upload widget is only available when the cell has been executed in the\n", " current browser session. Please rerun this cell to enable.\n", " \n", " " ] }, "metadata": {} }, { "output_type": "stream", "name": "stdout", "text": [ "Saving kaggle.json to kaggle.json\n", "User uploaded file \"kaggle.json\" with length 63 bytes\n" ] } ] }, { "metadata": { "id": "HMk7Zz4ZkpCe" }, "cell_type": "markdown", "source": [ "# Using the Kaggle API\n", "\n", "For a more complete list of what you can do with the API, visit https://github.com/Kaggle/kaggle-api." ] }, { "cell_type": "code", "source": [ "mypath = '/content/drive/My Drive/Colab Notebooks/kaggle/'" ], "metadata": { "id": "SE9HweiXKrBi" }, "execution_count": 2, "outputs": [] }, { "cell_type": "code", "source": [ "" ], "metadata": { "id": "08xJuaZRQclq" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "!kaggle competitions list -s sports" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "DhUkIo5eQceM", "outputId": "d2e60898-b0d2-47ef-a7c4-90f4899fb9f0" }, "execution_count": 5, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "ref deadline category reward teamCount userHasEntered \n", "---------------------------------------- ------------------- ---------- --------- --------- -------------- \n", "nfl-big-data-bowl-2020 2020-01-06 23:59:00 Featured $75,000 2038 False \n", "mens-march-mania-2022 2022-04-05 04:00:00 Featured $25,000 930 False \n", "ncaam-march-mania-2021 2021-04-06 04:00:00 Playground Prizes 707 False \n", "womens-march-mania-2022 2022-04-04 15:00:00 Featured $25,000 651 False \n", "march-machine-learning-mania-2017 2017-04-04 15:00:00 Playground Swag 441 False \n", "ncaaw-march-mania-2021 2021-04-05 12:01:00 Playground Prizes 451 False \n", "mens-machine-learning-competition-2019 2019-04-09 06:00:00 Featured $25,000 862 False \n", "march-machine-learning-mania-2016 2016-04-05 06:00:00 Featured $25,000 596 False \n", "womens-machine-learning-competition-2019 2019-04-08 05:10:00 Featured $25,000 497 False \n", "march-machine-learning-mania-2015 2015-04-07 23:59:00 Featured $15,000 340 False \n", "nfl-impact-detection 2021-01-04 23:59:00 Featured $75,000 459 False \n", "march-machine-learning-mania-2014 2014-04-08 23:59:00 Featured $15,000 248 False \n", "kobe-bryant-shot-selection 2016-06-13 23:59:00 Playground Knowledge 1117 False \n", "nfl-health-and-safety-helmet-assignment 2021-11-02 23:59:00 Featured $100,000 825 False \n", "mens-machine-learning-competition-2018 2018-04-02 23:59:00 Featured $50,000 933 False \n", "ncaam-march-mania-2021-spread 2021-04-06 04:00:00 Playground Knowledge 96 False \n", "ncaaw-march-mania-2021-spread 2021-04-05 12:01:00 Playground Knowledge 70 False \n", "march-madness-analytics-2020 2020-04-30 23:59:00 Analytics $25,000 0 False \n", "NFL-Punt-Analytics-Competition 2019-01-09 23:59:00 Analytics $80,000 0 False \n", "nfl-playing-surface-analytics 2020-01-02 23:59:00 Analytics $75,000 0 False \n" ] } ] }, { "cell_type": "code", "source": [ "!kaggle competitions list -s finance" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "OHlc1g9oe6Tl", "outputId": "727f3d6c-d884-48e8-db3f-04825d578b2d" }, "execution_count": 6, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "ref deadline category reward teamCount userHasEntered \n", "----------------------------------------- ------------------- ---------- -------- --------- -------------- \n", "ubiquant-market-prediction 2022-07-18 23:59:00 Featured $100,000 2810 False \n", "jpx-tokyo-stock-exchange-prediction 2022-07-05 23:59:00 Featured $63,000 1056 False \n", "santander-value-prediction-challenge 2018-08-20 23:59:00 Featured $60,000 4463 False \n", "jane-street-market-prediction 2021-08-23 23:59:00 Featured $100,000 4245 False \n", "optiver-realized-volatility-prediction 2022-01-10 18:36:00 Featured $100,000 3852 False \n", "two-sigma-financial-modeling 2017-03-01 23:59:00 Featured $100,000 2063 False \n", "g-research-crypto-forecasting 2022-05-03 23:59:00 Featured $125,000 1946 False \n", "the-winton-stock-market-challenge 2016-01-26 23:59:00 Featured $50,000 829 False \n", "two-sigma-financial-news 2019-08-05 23:59:00 Featured $100,000 2927 False \n", "elo-merchant-category-recommendation 2019-02-26 23:59:00 Featured $50,000 4110 False \n", "santander-customer-satisfaction 2016-05-02 23:59:00 Featured $60,000 5115 False \n", "santander-customer-transaction-prediction 2019-04-10 23:59:00 Featured $65,000 8751 False \n", "home-credit-default-risk 2018-08-29 23:59:00 Featured $70,000 7176 False \n", "santander-product-recommendation 2016-12-21 23:59:00 Featured $60,000 1779 False \n", "bnp-paribas-cardif-claims-management 2016-04-18 23:59:00 Featured $30,000 2920 False \n", "sberbank-russian-housing-market 2017-06-29 23:59:00 Featured $25,000 3264 False \n", "tabular-playground-series-aug-2021 2021-08-31 23:59:00 Playground Swag 1753 False \n", "donorschoose-application-screening 2018-04-25 23:59:00 Playground Swag 580 False \n" ] } ] }, { "cell_type": "code", "source": [ "!kaggle competitions list -s movies" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "0v-piZvTe6Mv", "outputId": "6bfb8db0-5a8b-4398-8134-eab959ace03d" }, "execution_count": 7, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "ref deadline category reward teamCount userHasEntered \n", "-------------------------- ------------------- --------------- --------- --------- -------------- \n", "tmdb-box-office-prediction 2019-05-30 23:59:00 Playground Knowledge 1395 False \n", "santa-2021 2022-01-12 23:59:00 Featured $25,000 867 False \n", "word2vec-nlp-tutorial 2015-06-30 23:59:00 Getting Started Knowledge 577 False \n" ] } ] }, { "cell_type": "code", "source": [ "!kaggle competitions list --category research" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "Ch8g_RIuQcaw", "outputId": "4bf0f65f-81f8-47e0-ace2-ebd28ef20095" }, "execution_count": 8, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "ref deadline category reward teamCount userHasEntered \n", "----------------------------------------------- ------------------- -------- --------- --------- -------------- \n", "smartphone-decimeter-2022 2022-07-29 23:59:00 Research $10,000 145 False \n", "uw-madison-gi-tract-image-segmentation 2022-07-14 23:59:00 Research $25,000 573 False \n", "image-matching-challenge-2022 2022-06-02 23:59:00 Research $10,000 571 False \n", "herbarium-2022-fgvc9 2022-05-30 23:59:00 Research Knowledge 123 False \n", "iwildcam2022-fgvc9 2022-05-30 23:59:00 Research Knowledge 17 False \n", "sorghum-id-fgvc-9 2022-05-30 23:59:00 Research Knowledge 248 False \n", "hotel-id-to-combat-human-trafficking-2022-fgvc9 2022-05-30 23:59:00 Research Knowledge 76 False \n", "birdclef-2022 2022-05-24 23:59:00 Research $10,000 777 False \n", "geolifeclef-2022-lifeclef-2022-fgvc9 2022-05-24 23:59:00 Research Knowledge 50 False \n", "happy-whale-and-dolphin 2022-04-18 23:59:00 Research $25,000 1588 False \n", "tensorflow-great-barrier-reef 2022-02-14 23:59:00 Research $150,000 2025 False \n", "petfinder-pawpularity-score 2022-01-14 23:59:00 Research $25,000 3537 False \n", "chaii-hindi-and-tamil-question-answering 2021-11-15 23:59:00 Research $10,000 943 False \n", "ventilator-pressure-prediction 2021-11-03 23:59:00 Research $7,500 2605 False \n", "landmark-retrieval-2021 2021-10-01 23:59:00 Research Swag 263 False \n", "landmark-recognition-2021 2021-10-01 23:59:00 Research Swag 383 False \n", "g2net-gravitational-wave-detection 2021-09-29 23:59:00 Research $15,000 1219 False \n", "seti-breakthrough-listen 2021-08-18 23:59:00 Research $15,000 768 False \n", "google-smartphone-decimeter-challenge 2021-08-04 23:59:00 Research $10,000 810 False \n", "birdclef-2021 2021-06-01 23:59:00 Research $5,000 816 False \n" ] } ] }, { "cell_type": "code", "source": [ "!kaggle competitions files march-madness-analytics-2020 " ], "metadata": { "colab": 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01(Sat) 19 Aug 1995 (W33)Aston Villa FC3-13-0Manchester United FC1995ENG3130230
11(Sat) 19 Aug 1995 (W33)Blackburn Rovers FC1-01-0Queens Park Rangers FC1995ENG1010130
21(Sat) 19 Aug 1995 (W33)Chelsea FC0-00-0Everton FC1995ENG0000011
31(Sat) 19 Aug 1995 (W33)Liverpool FC1-00-0Sheffield Wednesday FC1995ENG1000130
41(Sat) 19 Aug 1995 (W33)Manchester City FC1-10-1Tottenham Hotspur FC1995ENG1101011
................................................
4426426(Sun) 8 Mar 2020 (W10)AC Milan1-20-2Genoa CFC2019IT1202103
4426526(Sun) 8 Mar 2020 (W10)UC Sampdoria2-10-1Hellas Verona FC2019IT2101130
4426626(Sun) 8 Mar 2020 (W10)Udinese Calcio0-00-0ACF Fiorentina2019IT0000011
4426726(Sun) 8 Mar 2020 (W10)Juventus2-00-0FC Internazionale Milano2019IT2000230
4426826(Mon) 9 Mar 2020 (W11)US Sassuolo Calcio3-01-0Brescia2019IT3010330
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\n", " " ] }, "metadata": {}, "execution_count": 17 } ] }, { "cell_type": "code", "source": [ "" ], "metadata": { "id": "elGOrfinL3yJ" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "" ], "metadata": { "id": "0EvesrfnL3vD" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "!kaggle datasets files gravix/european-soccer " ], "metadata": { "id": "yn_8ecKCL3tP", "colab": { "base_uri": "https://localhost:8080/" }, "outputId": "c5740944-bfd8-4565-d847-0b75b79d99df" }, "execution_count": 18, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "name size creationDate \n", "------------------- ---- ------------------- \n", "european_soccer.csv 21MB 2019-10-25 10:04:33 \n" ] } ] }, { "cell_type": "code", "source": [ "!kaggle datasets download gravix/european-soccer " ], "metadata": { "id": "eW-BZjYGL3p6", "colab": { "base_uri": "https://localhost:8080/" }, "outputId": "ac4e837c-fd0c-4e5b-a78a-6bcbc38b3522" }, "execution_count": 19, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Downloading european-soccer.zip to /content\n", " 93% 5.00M/5.39M [00:00<00:00, 17.0MB/s]\n", "100% 5.39M/5.39M [00:00<00:00, 18.2MB/s]\n" ] } ] }, { "cell_type": "code", "source": [ "!unzip european-soccer.zip" ], "metadata": { "id": "Wknuf-nML3nq", "colab": { "base_uri": "https://localhost:8080/" }, "outputId": "fba2d5dd-3cf4-4fc5-97c7-b7f115e03c43" }, "execution_count": 20, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Archive: european-soccer.zip\n", " inflating: european_soccer.csv \n" ] } ] }, { "cell_type": "code", "source": [ "df = pd.read_csv('european_soccer.csv')" ], "metadata": { "id": "35gXKURFL3kv", "colab": { "base_uri": "https://localhost:8080/" }, "outputId": "f890a6dc-dc96-43cd-c683-552e80c803f1" }, "execution_count": 21, "outputs": [ { "output_type": "stream", "name": "stderr", "text": [ "/usr/local/lib/python3.7/dist-packages/IPython/core/interactiveshell.py:2882: DtypeWarning: Columns (52,86) have mixed types.Specify dtype option on import or set low_memory=False.\n", " exec(code_obj, self.user_global_ns, self.user_ns)\n" ] } ] }, { "cell_type": "code", "source": [ "df" ], "metadata": { "id": "QvD9O17BL3iD", "colab": { "base_uri": "https://localhost:8080/", "height": 661 }, "outputId": "47d681b9-fc37-4ea5-8a33-aabbe1f083e6" }, "execution_count": 22, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ " Div Date HomeTeam AwayTeam FTHG FTAG FTR HTHG HTAG \\\n", "0 B1 2010-07-30 Standard Waregem 1.0 1.0 D 0.0 1.0 \n", "1 B1 2010-07-31 Anderlecht Eupen 4.0 1.0 H 0.0 1.0 \n", "2 B1 2010-07-31 Kortrijk Club Brugge 1.0 0.0 H 0.0 0.0 \n", "3 B1 2010-07-31 Mechelen Lokeren 2.0 0.0 H 0.0 0.0 \n", "4 B1 2010-07-31 St Truiden Lierse 1.0 0.0 H 1.0 0.0 \n", "... .. ... ... ... ... ... .. ... ... \n", "55501 I1 2019-10-20 Parma Genoa 5.0 1.0 H 3.0 0.0 \n", "55502 I1 2019-10-20 Milan Lecce 2.0 2.0 D 1.0 0.0 \n", "55503 D2 2019-10-20 Bochum Karlsruhe 3.0 3.0 D 3.0 2.0 \n", "55504 I1 2019-10-20 Sassuolo Inter 3.0 4.0 A 1.0 3.0 \n", "55505 F1 2019-10-20 Marseille Strasbourg 2.0 0.0 H 1.0 0.0 \n", "\n", " HTR ... B365CAHH B365CAHA PCAHH PCAHA MaxCAHH MaxCAHA AvgCAHH \\\n", "0 A ... NaN NaN NaN NaN NaN NaN NaN \n", "1 A ... NaN NaN NaN NaN NaN NaN NaN \n", "2 D ... NaN NaN NaN NaN NaN NaN NaN \n", "3 D ... NaN NaN NaN NaN NaN NaN NaN \n", "4 H ... NaN NaN NaN NaN NaN NaN NaN \n", "... .. ... ... ... ... ... ... ... ... \n", "55501 H ... 1.92 2.01 1.90 2.01 1.93 2.10 1.89 \n", "55502 H ... 1.94 1.99 1.93 2.00 2.00 2.05 1.93 \n", "55503 H ... 1.77 2.10 1.79 2.11 1.88 2.17 1.80 \n", "55504 A ... 2.06 1.87 2.05 1.87 2.08 1.88 2.02 \n", "55505 H ... 1.83 2.10 1.83 2.09 1.85 2.10 1.81 \n", "\n", " AvgCAHA CurrentDivision DayOfWeek \n", "0 NaN 1 4 \n", "1 NaN 1 5 \n", "2 NaN 1 5 \n", "3 NaN 1 5 \n", "4 NaN 1 5 \n", "... ... ... ... \n", "55501 1.99 1 6 \n", "55502 1.95 1 6 \n", "55503 2.06 2 6 \n", "55504 1.86 1 6 \n", "55505 2.06 1 6 \n", "\n", "[55506 rows x 150 columns]" ], "text/html": [ "\n", "
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DivDateHomeTeamAwayTeamFTHGFTAGFTRHTHGHTAGHTR...B365CAHHB365CAHAPCAHHPCAHAMaxCAHHMaxCAHAAvgCAHHAvgCAHACurrentDivisionDayOfWeek
0B12010-07-30StandardWaregem1.01.0D0.01.0A...NaNNaNNaNNaNNaNNaNNaNNaN14
1B12010-07-31AnderlechtEupen4.01.0H0.01.0A...NaNNaNNaNNaNNaNNaNNaNNaN15
2B12010-07-31KortrijkClub Brugge1.00.0H0.00.0D...NaNNaNNaNNaNNaNNaNNaNNaN15
3B12010-07-31MechelenLokeren2.00.0H0.00.0D...NaNNaNNaNNaNNaNNaNNaNNaN15
4B12010-07-31St TruidenLierse1.00.0H1.00.0H...NaNNaNNaNNaNNaNNaNNaNNaN15
..................................................................
55501I12019-10-20ParmaGenoa5.01.0H3.00.0H...1.922.011.902.011.932.101.891.9916
55502I12019-10-20MilanLecce2.02.0D1.00.0H...1.941.991.932.002.002.051.931.9516
55503D22019-10-20BochumKarlsruhe3.03.0D3.02.0H...1.772.101.792.111.882.171.802.0626
55504I12019-10-20SassuoloInter3.04.0A1.03.0A...2.061.872.051.872.081.882.021.8616
55505F12019-10-20MarseilleStrasbourg2.00.0H1.00.0H...1.832.101.832.091.852.101.812.0616
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55506 rows × 150 columns

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DivDateHomeTeamAwayTeamFTHGFTAGFTRHTHGHTAGHTR...B365CAHHB365CAHAPCAHHPCAHAMaxCAHHMaxCAHAAvgCAHHAvgCAHACurrentDivisionDayOfWeek
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1B12010-07-31AnderlechtEupen4.01.0H0.01.0A...NaNNaNNaNNaNNaNNaNNaNNaN15
2B12010-07-31KortrijkClub Brugge1.00.0H0.00.0D...NaNNaNNaNNaNNaNNaNNaNNaN15
3B12010-07-31MechelenLokeren2.00.0H0.00.0D...NaNNaNNaNNaNNaNNaNNaNNaN15
4B12010-07-31St TruidenLierse1.00.0H1.00.0H...NaNNaNNaNNaNNaNNaNNaNNaN15
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995SP12010-09-26HerculesSevilla2.00.0H2.00.0H...NaNNaNNaNNaNNaNNaNNaNNaN16
996D12010-09-26KaiserslauternHannover0.01.0A0.01.0A...NaNNaNNaNNaNNaNNaNNaNNaN16
997D12010-09-26WolfsburgFreiburg2.01.0H1.01.0D...NaNNaNNaNNaNNaNNaNNaNNaN16
998I12010-09-26JuventusCagliari4.02.0H2.01.0H...NaNNaNNaNNaNNaNNaNNaNNaN16
999I12010-09-26FiorentinaParma2.00.0H0.00.0D...NaNNaNNaNNaNNaNNaNNaNNaN16
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