{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"pygments_lexer":"ipython3","nbconvert_exporter":"python","version":"3.6.4","file_extension":".py","codemirror_mode":{"name":"ipython","version":3},"name":"python","mimetype":"text/x-python"}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"markdown","source":"# MLB PLAYER DIGITAL ENGAGEMENT FORCASTING\n\n## 1. INTRODUCTION\n\n\n\nMLB teamed up with Google Cloud, hold this Kaggle competition to transform the fan experience through data.\n\nIn this competition, we will predict how fans engage with MLB players’ digital content on a daily basis for a future date range.\n\nWe will have access to player performance data, social media data, and team factors like market size. \n\nwe are going to find features that are related to fan engagement such as home run, and by using the features, the model predicts the fan engagement values.\n\n","metadata":{}},{"cell_type":"code","source":"import numpy as np\nimport pandas as pd\nfrom pathlib import Path\nfrom sklearn.metrics import mean_absolute_error\nfrom datetime import timedelta\nfrom functools import reduce\nfrom tqdm import tqdm\nimport lightgbm as lgbm\nimport mlb\nBASE_DIR = Path('../input/mlb-player-digital-engagement-forecasting')\nTRAIN_DIR = Path('../input/mlb-pdef-train-dataset')","metadata":{"execution":{"iopub.status.busy":"2022-02-22T07:16:29.926205Z","iopub.execute_input":"2022-02-22T07:16:29.926733Z","iopub.status.idle":"2022-02-22T07:16:29.931647Z","shell.execute_reply.started":"2022-02-22T07:16:29.9267Z","shell.execute_reply":"2022-02-22T07:16:29.930696Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"pd.read_csv(BASE_DIR / 'example_sample_submission.csv')","metadata":{"execution":{"iopub.status.busy":"2022-02-22T07:16:33.925753Z","iopub.execute_input":"2022-02-22T07:16:33.926112Z","iopub.status.idle":"2022-02-22T07:16:33.952408Z","shell.execute_reply.started":"2022-02-22T07:16:33.926084Z","shell.execute_reply":"2022-02-22T07:16:33.951361Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"Let's see an example submission that we have to submit for the competition. \n\nIn this competition, we have to find fan engagement scores (target 1,2,3,4) by date and player with given data.\n\nIn column 0, the fan engagement result (target 1 to 4) of PlayerId 656669 on Apr 27 are all Zero.\n\nwe can guess on the date 2021 April 26 a day before the 27th, there were no games or the player did not play the game based on fan engagement values.\n\n\n","metadata":{}},{"cell_type":"markdown","source":" If the given information is highly related to the 4 target values, we can find the most correlated features. \n \n The first time, I guessed information such as ‘Homerun’ or ‘no-hit no run’ can be the most important features. \n \n However, 4 target values are not correlated with these kinds of features. \n \n ![image.png](attachment:c43c2a63-5127-4a70-a78c-f96d22f2f911.png)\n \n **The Picture of an EDA result of 'AVG target values by Year-Month' from the Kaggle NB => https://www.kaggle.com/ryanholbrook/getting-started-with-mlb-player-digital-engagement**\n \n \n Instead of the previous hypothesis, 4 target values show some trends by time. \n \n Therefore, this competition is similar to time series data prediction such as temperature prediction or stock price prediction.","metadata":{},"attachments":{"c43c2a63-5127-4a70-a78c-f96d22f2f911.png":{"image/png":"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"}}},{"cell_type":"markdown","source":"## 2. MODEL ##\n\n\nBefore explaining our model, I will explain the time period of train and test data.\n\n\nWe got train data from **2018 to 24 April 2021**. \n\nPublic Leader Board provides **25 April 2021 to the last day of April 2021.**\n\nAt the End of the competition, the model has to predict some other period time **later than May 1, 2021.** Which is evaluation test data.\n\nI will call 2018 to 31 March 2021 as **train data**, 1 April 2021 to 24th April 2021 as **valid test data.**\n\nPublic Leader Board provides data from 25 April 2021 to the last day of April 2021. With train data, Most of the groups made their valid test data from 1 April 2021 to 24th April 2021.\n\n\n\n\n### a. THE FIRST MODEL ###\n\n\n\n\n","metadata":{}},{"cell_type":"code","source":"First_model_feature_cols = ['label_playerId', 'label_primaryPositionName', 'label_teamId',\n       'label_status', 'battingOrder', 'gamesPlayedBatting', 'flyOuts',\n       'groundOuts', 'runsScored', 'doubles', 'triples', 'homeRuns',\n       'strikeOuts', 'baseOnBalls', 'intentionalWalks', 'hits', 'hitByPitch',\n       'atBats', 'caughtStealing', 'stolenBases', 'groundIntoDoublePlay',\n       'groundIntoTriplePlay', 'plateAppearances', 'totalBases', 'rbi',\n       'leftOnBase', 'sacBunts', 'sacFlies', 'catchersInterference',\n       'pickoffs', 'gamesPlayedPitching', 'gamesStartedPitching',\n       'completeGamesPitching', 'shutoutsPitching', 'winsPitching',\n       'lossesPitching', 'flyOutsPitching', 'airOutsPitching',\n       'groundOutsPitching', 'runsPitching', 'doublesPitching',\n       'triplesPitching', 'homeRunsPitching', 'strikeOutsPitching',\n       'baseOnBallsPitching', 'intentionalWalksPitching', 'hitsPitching',\n       'hitByPitchPitching', 'atBatsPitching', 'caughtStealingPitching',\n       'stolenBasesPitching', 'inningsPitched', 'saveOpportunities',\n       'earnedRuns', 'battersFaced', 'outsPitching', 'pitchesThrown', 'balls',\n       'strikes', 'hitBatsmen', 'balks', 'wildPitches', 'pickoffsPitching',\n       'rbiPitching', 'gamesFinishedPitching', 'inheritedRunners',\n       'inheritedRunnersScored', 'catchersInterferencePitching',\n       'sacBuntsPitching', 'sacFliesPitching', 'saves', 'holds', 'blownSaves',\n       'assists', 'putOuts', 'errors', 'chances', \n'target1_mean',\n 'target1_median',\n 'target1_std',\n 'target1_min',\n 'target1_max',\n 'target1_prob',\n 'target2_mean',\n 'target2_median',\n 'target2_std',\n 'target2_min',\n 'target2_max',\n 'target2_prob',\n 'target3_mean',\n 'target3_median',\n 'target3_std',\n 'target3_min',\n 'target3_max',\n 'target3_prob',\n 'target4_mean',\n 'target4_median',\n 'target4_std',\n 'target4_min',\n 'target4_max',\n 'target4_prob'\n               ]","metadata":{"execution":{"iopub.status.busy":"2022-02-22T09:41:57.45498Z","iopub.execute_input":"2022-02-22T09:41:57.455489Z","iopub.status.idle":"2022-02-22T09:41:57.46572Z","shell.execute_reply.started":"2022-02-22T09:41:57.455442Z","shell.execute_reply":"2022-02-22T09:41:57.464553Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"\n\n\n","metadata":{}},{"cell_type":"markdown","source":"\nI put game features on the LightGBM model such as ‘homerun’, ‘playerId’, ‘TeamId’.\nAnd also I include statistical data such as 'target1_median', 'target_2_std' ect... \n\nThese are the valid test scores for our LightGBM model. **Target 1 for about 0.675, Target 2: 1.43 Target 3: 0.55 target 4: 1.12.** The average of the Mean absolute error is **0.947.** All the hyperparameters are tuned to get high valid test scores.","metadata":{}},{"cell_type":"markdown","source":"![image.png](attachment:74734b30-b379-4308-85bf-93d5a78ad3a0.png)\n\n\nNow we will see the feature importance from target 1 to target 4.\n\n**Player Id** is the most important feature for the target 1 prediction LightGBM model.\n\n**Target4_min** which is one of the statistical values is the most important feature for the target 2 prediction LightGBM model.\n\n**Player Id** is the most important feature for the target 3 prediction LightGBM model.\n\n**Player Id** is the most important feature for the target 4 prediction LightGBM model.\n\nThis result shows **statistical information** and **player_id** is a good feature for the model. However, when we think about the result, It is common sense that a popular MLB player is always highlighted by others while a non-popular MLB player is not.\n","metadata":{},"attachments":{"74734b30-b379-4308-85bf-93d5a78ad3a0.png":{"image/png":"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"}}},{"cell_type":"markdown","source":"\n### b. THE ADVENCED MODEL ###\n\n![image.png](attachment:fd1d4db1-e082-4bea-8aa9-325fba1a6ba9.png)\n![image.png](attachment:658dd6a0-64c0-49e2-a1dd-3f1b528a619a.png)\n\nFirst, I tried to change statistical features. \n\nIf we see the feature importance, most of the statistical features are highly ranked. I got the mean values of each target by applying the 'group by' function with playerId, month, and Year. The previous EDA picture gave me the idea for applying the 'group by' function with month and Year. \n\nIn addition, the previous model’s feature importance gives me the idea for applying the 'group by' function with playerID. Also, I put Day, Month, Year to the features for the new model. I assume that the LighGBM model finds a connection between the statistical features and Day Month Years by expanding its 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"},"fd1d4db1-e082-4bea-8aa9-325fba1a6ba9.png":{"image/png":"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"}}},{"cell_type":"markdown","source":"\n\nFor the result, I reduced valid test scores from 0.95(first model valid test score) to 0.90. \n\nThe previous valid test score is from a fully tuned model while the new model’s hyperparameter is never tuned. \nIf we see the feature importance lists, we can see new features are highly ranked.\n\n![image.png](attachment:b20e0513-1b92-4917-bb80-31b718413814.png)\n\nI put more statistical features into the model. \nI put not only the mean target values applying with groupby function, but also max, min std median with groupby fuction.\nThe valid test score became 0.86 and this score is also without any parameter tuning. \n**Even without hyperparameter tunning, the model shows a similar valid train score with many other groups who are in the top public leaderboard score.**\n","metadata":{},"attachments":{"b20e0513-1b92-4917-bb80-31b718413814.png":{"image/png":"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"}}},{"cell_type":"markdown","source":"\n\nIn this competition discussion board, many participants who got top public test scores have argued that top scores models on the boards are overfitted or used leaked data. If we see the public test data, it starts from 25 April to 30 April 2021. And Train data includes 2021 April data. The models might be fit to find a good score for the April 2021 test data. However, the competition's final private test data is starting from May 2021. Therefore, **I decided to use a totally different approach to train the model.**","metadata":{}},{"cell_type":"markdown","source":"\n\n\n","metadata":{}},{"cell_type":"markdown","source":"### Statistical Features for the New train data\n#### 1. Same month but previous year\n#### Player A(May. 15. 2021) : Player A target mean value (May 2020 , May 2019)\n","metadata":{}},{"cell_type":"markdown","source":"I decided to add target mean values with the same month but the previous year each row for the train data.\n\nIf there is a May 15th, 2021 train data row for player A, I calculated target mean values of May 2020 and May 2019 and put them into features for the model.\n\nWhen we compare sales revenues by quarters for a company, usually economists compare present quarter revenue with not the previous quarter's revenues but same quarter revenues in a previous year.  My first feature engineering idea came from this.","metadata":{}},{"cell_type":"markdown","source":"\n#### 2. Target mean values with previous month and next month but the previous years'\n#### Player A(May. 15. 2021) : Player A harget mean value (April 2020 , Jun 2020)","metadata":{}},{"cell_type":"markdown","source":"\n\nIf there is a May 15th, 2021 train data row for player A, I calculated target mean values of April 2020 and Jun 2020 for player A and put them into features for the model.\n\n Based on the EDA graph, If I want to get one of May's target values, April and Jun data can be a good feature. However, in the test set, we cannot get future-month of statistical features. Therefore, instead of 2021 April and Jun mean target values, I put 2020 April and Jun mean target values in this example case. But these features are from the previous year one, therefore, I thought it require something that helps to connect the previous year (2020) and this year(2021)","metadata":{}},{"cell_type":"markdown","source":"\n#### 3. A ratio of this year target mean values by previous year target mean values\n#### Player A (May. 15. 2021):  Player A target mean value(Jan+Feb+Mar 2021) **/** Player A target mean value(Jan+Feb+Mar 2020)","metadata":{}},{"cell_type":"markdown","source":"\n\nTo connect precious year and this year, I calculated a ratio of this year's target mean values by the previous year's target mean value. \n\nHowever, in the train data. when we think about the period of our train data, 2021 target values are ends April 25. Since Jan Feb Mar data are complete data, each year of Jan, Feb, Mar target values are used to get the ratio.\nThen this can represent a hypothetical rising MLB star showing higher target values year by year with this ratio features.","metadata":{}},{"cell_type":"markdown","source":"\n\n","metadata":{}},{"cell_type":"markdown","source":"#### Result for the advenced model\n![image.png](attachment:01b0e031-065d-4c6f-a2a8-af4a34503e7d.png)\n![image.png](attachment:0c5dc52b-fd8e-4a87-a103-ea0af1082c63.png)\n","metadata":{},"attachments":{"0c5dc52b-fd8e-4a87-a103-ea0af1082c63.png":{"image/png":"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"},"01b0e031-065d-4c6f-a2a8-af4a34503e7d.png":{"image/png":"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"}}},{"cell_type":"markdown","source":"\nHere is the result for the advanced model.\n\nThe valid test score is not good as the previous model (0.85 to 1) however, I think this model is made by my logical sequence to avoid overfitting. According to the feature importance result,**surprisingly this model seems to found some relationships between player, date, and feature that I made.**","metadata":{}},{"cell_type":"code","source":"","metadata":{"execution":{"iopub.status.busy":"2021-07-31T23:41:29.044165Z","iopub.execute_input":"2021-07-31T23:41:29.044544Z","iopub.status.idle":"2021-07-31T23:41:29.052078Z","shell.execute_reply.started":"2021-07-31T23:41:29.044504Z","shell.execute_reply":"2021-07-31T23:41:29.05083Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"players = pd.read_csv(BASE_DIR / 'players.csv')\nrosters = pd.read_pickle(TRAIN_DIR / 'rosters_train.pkl')\ntargets = pd.read_pickle(TRAIN_DIR / 'nextDayPlayerEngagement_train.pkl')\nscores = pd.read_pickle(TRAIN_DIR / 'playerBoxScores_train.pkl')\nscores = scores.groupby(['playerId', 'date']).sum().reset_index()","metadata":{"execution":{"iopub.status.busy":"2021-07-31T23:41:29.054097Z","iopub.execute_input":"2021-07-31T23:41:29.054418Z","iopub.status.idle":"2021-07-31T23:41:33.673878Z","shell.execute_reply.started":"2021-07-31T23:41:29.05439Z","shell.execute_reply":"2021-07-31T23:41:33.672594Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"targets_cols = ['playerId', 'target1', 'target2', 'target3', 'target4', 'date']\nplayers_cols = ['playerId', 'primaryPositionName']\nrosters_cols = ['playerId', 'teamId', 'status', 'date']\nscores_cols = ['playerId', 'battingOrder', 'gamesPlayedBatting', 'flyOuts',\n       'groundOuts', 'runsScored', 'doubles', 'triples', 'homeRuns',\n       'strikeOuts', 'baseOnBalls', 'intentionalWalks', 'hits', 'hitByPitch',\n       'atBats', 'caughtStealing', 'stolenBases', 'groundIntoDoublePlay',\n       'groundIntoTriplePlay', 'plateAppearances', 'totalBases', 'rbi',\n       'leftOnBase', 'sacBunts', 'sacFlies', 'catchersInterference',\n       'pickoffs', 'gamesPlayedPitching', 'gamesStartedPitching',\n       'completeGamesPitching', 'shutoutsPitching', 'winsPitching',\n       'lossesPitching', 'flyOutsPitching', 'airOutsPitching',\n       'groundOutsPitching', 'runsPitching', 'doublesPitching',\n       'triplesPitching', 'homeRunsPitching', 'strikeOutsPitching',\n       'baseOnBallsPitching', 'intentionalWalksPitching', 'hitsPitching',\n       'hitByPitchPitching', 'atBatsPitching', 'caughtStealingPitching',\n       'stolenBasesPitching', 'inningsPitched', 'saveOpportunities',\n       'earnedRuns', 'battersFaced', 'outsPitching', 'pitchesThrown', 'balls',\n       'strikes', 'hitBatsmen', 'balks', 'wildPitches', 'pickoffsPitching',\n       'rbiPitching', 'gamesFinishedPitching', 'inheritedRunners',\n       'inheritedRunnersScored', 'catchersInterferencePitching',\n       'sacBuntsPitching', 'sacFliesPitching', 'saves', 'holds', 'blownSaves',\n       'assists', 'putOuts', 'errors', 'chances', 'date']\n\nfeature_cols = ['label_playerId', 'label_primaryPositionName', 'label_teamId',\n       'label_status', 'battingOrder', 'gamesPlayedBatting', 'flyOuts',\n       'groundOuts', 'runsScored', 'doubles', 'triples', 'homeRuns',\n       'strikeOuts', 'baseOnBalls', 'intentionalWalks', 'hits', 'hitByPitch',\n       'atBats', 'caughtStealing', 'stolenBases', 'groundIntoDoublePlay',\n       'groundIntoTriplePlay', 'plateAppearances', 'totalBases', 'rbi',\n       'leftOnBase', 'sacBunts', 'sacFlies', 'catchersInterference',\n       'pickoffs', 'gamesPlayedPitching', 'gamesStartedPitching',\n       'completeGamesPitching', 'shutoutsPitching', 'winsPitching',\n       'lossesPitching', 'flyOutsPitching', 'airOutsPitching',\n       'groundOutsPitching', 'runsPitching', 'doublesPitching',\n       'triplesPitching', 'homeRunsPitching', 'strikeOutsPitching',\n       'baseOnBallsPitching', 'intentionalWalksPitching', 'hitsPitching',\n       'hitByPitchPitching', 'atBatsPitching', 'caughtStealingPitching',\n       'stolenBasesPitching', 'inningsPitched', 'saveOpportunities',\n       'earnedRuns', 'battersFaced', 'outsPitching', 'pitchesThrown', 'balls',\n       'strikes', 'hitBatsmen', 'balks', 'wildPitches', 'pickoffsPitching',\n       'rbiPitching', 'gamesFinishedPitching', 'inheritedRunners',\n       'inheritedRunnersScored', 'catchersInterferencePitching',\n       'sacBuntsPitching', 'sacFliesPitching', 'saves', 'holds', 'blownSaves',\n       'assists', 'putOuts', 'errors', 'chances', \n\n               ]","metadata":{"execution":{"iopub.status.busy":"2021-07-31T23:41:33.676027Z","iopub.execute_input":"2021-07-31T23:41:33.676453Z","iopub.status.idle":"2021-07-31T23:41:33.693724Z","shell.execute_reply.started":"2021-07-31T23:41:33.676409Z","shell.execute_reply":"2021-07-31T23:41:33.692462Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train = pd.read_csv(\"../input/wsl-dc/mycsvfile.csv\")","metadata":{"execution":{"iopub.status.busy":"2021-07-31T23:41:33.695167Z","iopub.execute_input":"2021-07-31T23:41:33.695464Z","iopub.status.idle":"2021-07-31T23:42:09.901052Z","shell.execute_reply.started":"2021-07-31T23:41:33.695425Z","shell.execute_reply":"2021-07-31T23:42:09.898228Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"player_target_stats = pd.read_csv(\"../input/player-target-stats/player_target_stats.csv\")\n","metadata":{"execution":{"iopub.status.busy":"2021-07-31T23:42:09.905771Z","iopub.execute_input":"2021-07-31T23:42:09.906798Z","iopub.status.idle":"2021-07-31T23:42:09.951184Z","shell.execute_reply.started":"2021-07-31T23:42:09.906601Z","shell.execute_reply":"2021-07-31T23:42:09.949795Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"","metadata":{},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"# label encoding\nplayer2num = {c: i for i, c in enumerate(train['playerId'].unique())}\nposition2num = {c: i for i, c in enumerate(train['primaryPositionName'].unique())}\nteamid2num = {c: i for i, c in enumerate(train['teamId'].unique())}\nstatus2num = {c: i for i, c in enumerate(train['status'].unique())}\ntrain['label_playerId'] = train['playerId'].map(player2num)\ntrain['label_primaryPositionName'] = train['primaryPositionName'].map(position2num)\ntrain['label_teamId'] = train['teamId'].map(teamid2num)\ntrain['label_status'] = train['status'].map(status2num)","metadata":{"execution":{"iopub.status.busy":"2021-07-31T23:42:09.952852Z","iopub.execute_input":"2021-07-31T23:42:09.953277Z","iopub.status.idle":"2021-07-31T23:42:11.260802Z","shell.execute_reply.started":"2021-07-31T23:42:09.953235Z","shell.execute_reply":"2021-07-31T23:42:11.259674Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"#original model.","metadata":{"execution":{"iopub.status.busy":"2021-07-31T23:42:11.263106Z","iopub.execute_input":"2021-07-31T23:42:11.263427Z","iopub.status.idle":"2021-07-31T23:42:11.268762Z","shell.execute_reply.started":"2021-07-31T23:42:11.263399Z","shell.execute_reply":"2021-07-31T23:42:11.267595Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"#mae: 1.1210108475080813\n#score: 0.9470136325539955","metadata":{"execution":{"iopub.status.busy":"2021-07-31T23:42:11.271481Z","iopub.execute_input":"2021-07-31T23:42:11.272156Z","iopub.status.idle":"2021-07-31T23:42:11.280572Z","shell.execute_reply.started":"2021-07-31T23:42:11.272108Z","shell.execute_reply":"2021-07-31T23:42:11.279374Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"\n    ","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"# #IDYM\n# train['Month']=train['date'].apply(lambda x : int(str(x)[4:6]))\n# train['Year']=train['date'].apply(lambda x : int(str(x)[2:4]))\n# train['Day']=train['date'].apply(lambda x : int(str(x)[6:8]))\n# #converted model\n\nmean_IdYM=train[['target1','target2','target3','target4',\"playerId\",\"Year\",\"Month\"]].groupby([\"playerId\",\"Year\",\"Month\"]).mean()\n\n# #mean_IdYM.iloc(112526,18,1)\n# #mean_IdYM=train[['target1','target2','target3','target4',\"playerId\",\"Year\",\"Month\"]].groupby([\"playerId\",\"Year\",\"Month\"]).mean()#.get_group((628317,19,1))","metadata":{"execution":{"iopub.status.busy":"2021-07-31T23:42:11.282739Z","iopub.execute_input":"2021-07-31T23:42:11.283146Z","iopub.status.idle":"2021-07-31T23:42:11.523123Z","shell.execute_reply.started":"2021-07-31T23:42:11.283105Z","shell.execute_reply":"2021-07-31T23:42:11.52206Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"            tr_pId = train['playerId']==547989\n            tr_M = train['Year']==20\n            tr_Y = train['Month']==7\n            c = tr_pId & tr_M & tr_Y\n            ","metadata":{"execution":{"iopub.status.busy":"2021-07-31T23:42:11.524767Z","iopub.execute_input":"2021-07-31T23:42:11.525168Z","iopub.status.idle":"2021-07-31T23:42:11.543438Z","shell.execute_reply.started":"2021-07-31T23:42:11.525129Z","shell.execute_reply":"2021-07-31T23:42:11.542167Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"# train.loc[train[c].index,'Last_YpM_mean_1']=mean_IdYM.loc[(547989,20,7)].target1\n#a.Last_YpM_mean_1=mean_IdYM.loc[(547989,19,7)].target1","metadata":{"execution":{"iopub.status.busy":"2021-07-31T23:42:11.544526Z","iopub.execute_input":"2021-07-31T23:42:11.544831Z","iopub.status.idle":"2021-07-31T23:42:11.553007Z","shell.execute_reply.started":"2021-07-31T23:42:11.544804Z","shell.execute_reply":"2021-07-31T23:42:11.550386Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"#mean_IdYM.loc[(547989,20,7)].target1","metadata":{"execution":{"iopub.status.busy":"2021-07-31T23:42:11.554658Z","iopub.execute_input":"2021-07-31T23:42:11.555066Z","iopub.status.idle":"2021-07-31T23:42:11.561621Z","shell.execute_reply.started":"2021-07-31T23:42:11.555033Z","shell.execute_reply":"2021-07-31T23:42:11.560693Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"#train[c]","metadata":{"execution":{"iopub.status.busy":"2021-07-31T23:42:11.563231Z","iopub.execute_input":"2021-07-31T23:42:11.563548Z","iopub.status.idle":"2021-07-31T23:42:11.576427Z","shell.execute_reply.started":"2021-07-31T23:42:11.563518Z","shell.execute_reply":"2021-07-31T23:42:11.575018Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"# train['Last_YpM_mean_1']=0\n# train['Last_YpM_mean_2']=0\n# train['Last_YpM_mean_3']=0\n# train['Last_YpM_mean_4']=0        \n# train['Last_YnM_mean_1']=0\n# train['Last_YnM_mean_2']=0\n# train['Last_YnM_mean_3']=0\n# train['Last_YnM_mean_4']=0\n\n# for num,Id in enumerate(train['playerId'].unique()):\n#     if num%20==0:\n#         print(num)\n#     for year in [18,19,20,21]:\n#         for month in [1,2,3,4,5,6,7,8,9,10,11,12]:\n#             Yp = year -1\n#             Yn = year -1\n#             Mp = month -1\n#             Mn = month +1\n            \n#             if month==1:\n#                 Yp=year-2\n#                 Mp=12\n#             elif month==12:\n#                 Yn=year\n#                 Mn=1\n            \n#             tr_pId = train['playerId']==Id\n#             tr_M = train['Month']==month\n#             tr_Y = train['Year']==year\n#             c = tr_pId & tr_M & tr_Y\n#             try:\n#                 train.loc[train[c].index,'Last_YpM_mean_1']=mean_IdYM.loc[(Id,Yp,Mp)].target1\n#             except:\n#                 train.loc[train[c].index,'Last_YpM_mean_1']=np.nan\n#             try:\n#                 train.loc[train[c].index,'Last_YpM_mean_2']=mean_IdYM.loc[(Id,Yp,Mp)].target2\n#             except:\n#                 train.loc[train[c].index,'Last_YpM_mean_2']=np.nan\n#             try:\n#                 train.loc[train[c].index,'Last_YpM_mean_3']=mean_IdYM.loc[(Id,Yp,Mp)].target3\n#             except:\n#                 train.loc[train[c].index,'Last_YpM_mean_3']=np.nan\n#             try:\n#                 train.loc[train[c].index,'Last_YpM_mean_4']=mean_IdYM.loc[(Id,Yp,Mp)].target4\n#             except:\n#                 train.loc[train[c].index,'Last_YpM_mean_4']=np.nan            \n            \n            \n#             try:\n#                 train.loc[train[c].index,'Last_YnM_mean_1']=mean_IdYM.loc[(Id,Yn,Mn)].target1\n#             except:\n#                 train.loc[train[c].index,'Last_YnM_mean_1']=np.nan\n#             try:\n#                 train.loc[train[c].index,'Last_YnM_mean_2']=mean_IdYM.loc[(Id,Yn,Mn)].target2\n#             except:\n#                 train.loc[train[c].index,'Last_YnM_mean_2']=np.nan\n#             try:\n#                 train.loc[train[c].index,'Last_YnM_mean_3']=mean_IdYM.loc[(Id,Yn,Mn)].target3\n#             except:\n#                 train.loc[train[c].index,'Last_YnM_mean_3']=np.nan\n#             try:\n#                 train.loc[train[c].index,'Last_YnM_mean_4']=mean_IdYM.loc[(Id,Yn,Mn)].target4\n#             except:\n#                 train.loc[train[c].index,'Last_YnM_mean_4']=np.nan\n                \n                \n \n                \n                    \n            \n    \n        \n    ","metadata":{"execution":{"iopub.status.busy":"2021-07-31T23:42:11.578505Z","iopub.execute_input":"2021-07-31T23:42:11.578871Z","iopub.status.idle":"2021-07-31T23:42:11.590486Z","shell.execute_reply.started":"2021-07-31T23:42:11.578815Z","shell.execute_reply":"2021-07-31T23:42:11.588938Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"raw","source":"","metadata":{}},{"cell_type":"code","source":"","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"# ","metadata":{"execution":{"iopub.status.busy":"2021-07-31T23:42:11.592719Z","iopub.execute_input":"2021-07-31T23:42:11.593047Z","iopub.status.idle":"2021-07-31T23:42:11.605759Z","shell.execute_reply.started":"2021-07-31T23:42:11.593017Z","shell.execute_reply":"2021-07-31T23:42:11.604764Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"","metadata":{},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"######################################\ndef reduce_mem_usage(df):\n    \"\"\" iterate through all the columns of a dataframe and modify the data type\n        to reduce memory usage.        \n    \"\"\"\n    start_mem = df.memory_usage().sum() / 1024**2\n    print('Memory usage of dataframe is {:.2f} MB'.format(start_mem))\n    \n    for col in df.columns:\n        col_type = df[col].dtype\n        \n        if col_type == 'datetime64[ns]':\n            continue\n        if col_type != object:\n            c_min = df[col].min()\n            c_max = df[col].max()\n            if str(col_type)[:3] == 'int':\n                if c_min > np.iinfo(np.int8).min and c_max < np.iinfo(np.int8).max:\n                    df[col] = df[col].astype(np.int8)\n                elif c_min > np.iinfo(np.int16).min and c_max < np.iinfo(np.int16).max:\n                    df[col] = df[col].astype(np.int16)\n                elif c_min > np.iinfo(np.int32).min and c_max < np.iinfo(np.int32).max:\n                    df[col] = df[col].astype(np.int32)\n                elif c_min > np.iinfo(np.int64).min and c_max < np.iinfo(np.int64).max:\n                    df[col] = df[col].astype(np.int64)  \n            else:\n                if c_min > np.finfo(np.float16).min and c_max < np.finfo(np.float16).max:\n                    df[col] = df[col].astype(np.float16)\n                elif c_min > np.finfo(np.float32).min and c_max < np.finfo(np.float32).max:\n                    df[col] = df[col].astype(np.float32)\n                else:\n                    df[col] = df[col].astype(np.float64)\n        else:\n            df[col] = df[col].astype('category')\n\n    end_mem = df.memory_usage().sum() / 1024**2\n    print('Memory usage after optimization is: {:.2f} MB'.format(end_mem))\n    print('Decreased by {:.1f}%'.format(100 * (start_mem - end_mem) / start_mem))\n    \n    return df\ntrain=reduce_mem_usage(train)\n","metadata":{"execution":{"iopub.status.busy":"2021-07-31T23:42:11.607147Z","iopub.execute_input":"2021-07-31T23:42:11.607638Z","iopub.status.idle":"2021-07-31T23:42:57.257944Z","shell.execute_reply.started":"2021-07-31T23:42:11.607593Z","shell.execute_reply":"2021-07-31T23:42:57.256633Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"#mean_IdYM=train[['target1','target2','target3','target4',\"playerId\",\"Year\",\"Month\"]].groupby([\"playerId\",\"Year\",\"Month\"]).mean()#.get_group((628317,19,1))","metadata":{"execution":{"iopub.status.busy":"2021-07-31T23:42:57.260186Z","iopub.execute_input":"2021-07-31T23:42:57.260755Z","iopub.status.idle":"2021-07-31T23:42:57.26563Z","shell.execute_reply.started":"2021-07-31T23:42:57.260701Z","shell.execute_reply":"2021-07-31T23:42:57.2647Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"#train['playerId'].unique()\n#train['Year'].unique()\n#train['Month'].unique()","metadata":{"execution":{"iopub.status.busy":"2021-07-31T23:42:57.267205Z","iopub.execute_input":"2021-07-31T23:42:57.267794Z","iopub.status.idle":"2021-07-31T23:42:57.281586Z","shell.execute_reply.started":"2021-07-31T23:42:57.26775Z","shell.execute_reply":"2021-07-31T23:42:57.280604Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"#train[['target1','target2','target3','target4',\"playerId\",\"Year\",\"Month\"]].groupby([\"playerId\",\"Year\",\"Month\"]).get_group((628317,19,1))","metadata":{"execution":{"iopub.status.busy":"2021-07-31T23:42:57.282958Z","iopub.execute_input":"2021-07-31T23:42:57.283516Z","iopub.status.idle":"2021-07-31T23:42:57.30013Z","shell.execute_reply.started":"2021-07-31T23:42:57.283476Z","shell.execute_reply":"2021-07-31T23:42:57.298713Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"#train[train['Year']==18].groupby([\"playerId\",\"Month\"]).mean()\npre_tr=train[['target1','target2','target3','target4',\"playerId\",\"Year\",\"Month\"]]\npre_tr","metadata":{"execution":{"iopub.status.busy":"2021-07-31T23:42:57.301427Z","iopub.execute_input":"2021-07-31T23:42:57.301758Z","iopub.status.idle":"2021-07-31T23:42:57.870685Z","shell.execute_reply.started":"2021-07-31T23:42:57.301727Z","shell.execute_reply":"2021-07-31T23:42:57.869243Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train","metadata":{"execution":{"iopub.status.busy":"2021-07-31T23:42:57.872192Z","iopub.execute_input":"2021-07-31T23:42:57.872489Z","iopub.status.idle":"2021-07-31T23:42:58.175253Z","shell.execute_reply.started":"2021-07-31T23:42:57.87246Z","shell.execute_reply":"2021-07-31T23:42:58.173997Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"pre_tr","metadata":{"execution":{"iopub.status.busy":"2021-07-31T23:42:58.180973Z","iopub.execute_input":"2021-07-31T23:42:58.181301Z","iopub.status.idle":"2021-07-31T23:42:58.200198Z","shell.execute_reply.started":"2021-07-31T23:42:58.181272Z","shell.execute_reply":"2021-07-31T23:42:58.19917Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"m1 = pre_tr['Month']==1\nm2 = pre_tr['Month']==2\nm3 = pre_tr['Month']==3\nY18 = pre_tr['Year']==18\nY19 = pre_tr['Year']==19\nY20 = pre_tr['Year']==20\nY21 = pre_tr['Year']==21\n\nm1_3=m1|m2|m3\nm1_3Y18=m1_3&Y18\nm1_3Y19=m1_3&Y19\nm1_3Y20=m1_3&Y20\nm1_3Y21=m1_3&Y21\n\ntr_18_123 = pre_tr[m1_3Y18].groupby([\"playerId\"]).mean()\ntr_19_123 = pre_tr[m1_3Y19].groupby([\"playerId\"]).mean()\ntr_20_123 = pre_tr[m1_3Y20].groupby([\"playerId\"]).mean()\ntr_21_123 = pre_tr[m1_3Y21].groupby([\"playerId\"]).mean()","metadata":{"execution":{"iopub.status.busy":"2021-07-31T23:42:58.203176Z","iopub.execute_input":"2021-07-31T23:42:58.20382Z","iopub.status.idle":"2021-07-31T23:42:58.350088Z","shell.execute_reply.started":"2021-07-31T23:42:58.203774Z","shell.execute_reply":"2021-07-31T23:42:58.348742Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"tr_18_123=tr_18_123.drop('Month',axis=1)\ntr_19_123=tr_19_123.drop('Month',axis=1)\ntr_20_123=tr_20_123.drop('Month',axis=1)\ntr_21_123=tr_21_123.drop('Month',axis=1)","metadata":{"execution":{"iopub.status.busy":"2021-07-31T23:42:58.351469Z","iopub.execute_input":"2021-07-31T23:42:58.351926Z","iopub.status.idle":"2021-07-31T23:42:58.361852Z","shell.execute_reply.started":"2021-07-31T23:42:58.351883Z","shell.execute_reply":"2021-07-31T23:42:58.360811Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"tr_21_123","metadata":{"execution":{"iopub.status.busy":"2021-07-31T23:42:58.363423Z","iopub.execute_input":"2021-07-31T23:42:58.363785Z","iopub.status.idle":"2021-07-31T23:42:58.389848Z","shell.execute_reply.started":"2021-07-31T23:42:58.363754Z","shell.execute_reply":"2021-07-31T23:42:58.388769Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train['now_1_mean_123']=0\ntrain['now_2_mean_123']=0\ntrain['now_3_mean_123']=0\ntrain['now_4_mean_123']=0\n\ntr_list=[tr_18_123 ,tr_19_123 ,tr_20_123 ,tr_21_123]\nfor ele in tr_list:\n    train=train.merge(ele,on=[\"playerId\",\"Year\"],how='left',suffixes=('', '_y'))\n    #print(np.nan_to_num(train['target1_y'], copy=False))\n    train['now_1_mean_123']=np.nan_to_num(train['target1_y'], copy=False)+train['now_1_mean_123']\n    train['now_2_mean_123']=np.nan_to_num(train['target2_y'], copy=False)+train['now_2_mean_123']\n    train['now_3_mean_123']=np.nan_to_num(train['target3_y'], copy=False)+train['now_3_mean_123']\n    train['now_4_mean_123']=np.nan_to_num(train['target4_y'], copy=False)+train['now_4_mean_123']\n    train=train.drop(['target1_y','target2_y','target3_y','target4_y'],axis=1)\n    \ntrain['now_1_mean_123']=train['now_1_mean_123'].map(lambda x : np.nan if x==0 else x)\ntrain['now_2_mean_123']=train['now_2_mean_123'].map(lambda x : np.nan if x==0 else x)\ntrain['now_3_mean_123']=train['now_3_mean_123'].map(lambda x : np.nan if x==0 else x)\ntrain['now_4_mean_123']=train['now_4_mean_123'].map(lambda x : np.nan if x==0 else x)","metadata":{"execution":{"iopub.status.busy":"2021-07-31T23:42:58.391322Z","iopub.execute_input":"2021-07-31T23:42:58.391789Z","iopub.status.idle":"2021-07-31T23:43:43.613062Z","shell.execute_reply.started":"2021-07-31T23:42:58.391755Z","shell.execute_reply":"2021-07-31T23:43:43.611705Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train","metadata":{"execution":{"iopub.status.busy":"2021-07-31T23:43:43.614446Z","iopub.execute_input":"2021-07-31T23:43:43.614774Z","iopub.status.idle":"2021-07-31T23:43:43.937517Z","shell.execute_reply.started":"2021-07-31T23:43:43.61474Z","shell.execute_reply":"2021-07-31T23:43:43.936122Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train['pre_1_mean_123']=0\ntrain['pre_2_mean_123']=0\ntrain['pre_3_mean_123']=0\ntrain['pre_4_mean_123']=0\n\ntr_list=[tr_18_123 ,tr_19_123 ,tr_20_123]\nfor ele in tr_list:\n    ele[\"Year\"]=ele[\"Year\"]+1\n    train=train.merge(ele,on=[\"playerId\",\"Year\"],how='left',suffixes=('', '_y'))\n    ele[\"Year\"]=ele[\"Year\"]-1\n    #print(np.nan_to_num(train['target1_y'], copy=False))\n    train['pre_1_mean_123']=np.nan_to_num(train['target1_y'], copy=False)+train['pre_1_mean_123']\n    train['pre_2_mean_123']=np.nan_to_num(train['target2_y'], copy=False)+train['pre_2_mean_123']\n    train['pre_3_mean_123']=np.nan_to_num(train['target3_y'], copy=False)+train['pre_3_mean_123']\n    train['pre_4_mean_123']=np.nan_to_num(train['target4_y'], copy=False)+train['pre_4_mean_123']\n    train=train.drop(['target1_y','target2_y','target3_y','target4_y'],axis=1)\n    \ntrain['pre_1_mean_123']=train['pre_1_mean_123'].map(lambda x : np.nan if x==0 else x)\ntrain['pre_2_mean_123']=train['pre_2_mean_123'].map(lambda x : np.nan if x==0 else x)\ntrain['pre_3_mean_123']=train['pre_3_mean_123'].map(lambda x : np.nan if x==0 else x)\ntrain['pre_4_mean_123']=train['pre_4_mean_123'].map(lambda x : np.nan if x==0 else x)\n","metadata":{"execution":{"iopub.status.busy":"2021-07-31T23:43:43.939075Z","iopub.execute_input":"2021-07-31T23:43:43.939396Z","iopub.status.idle":"2021-07-31T23:44:19.785794Z","shell.execute_reply.started":"2021-07-31T23:43:43.939367Z","shell.execute_reply":"2021-07-31T23:44:19.784545Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"\ntrain['now_pre_ratio_1']=train[\"now_1_mean_123\"]/train[\"pre_1_mean_123\"]\ntrain['now_pre_ratio_2']=train[\"now_2_mean_123\"]/train[\"pre_2_mean_123\"]\ntrain['now_pre_ratio_3']=train[\"now_3_mean_123\"]/train[\"pre_3_mean_123\"]\ntrain['now_pre_ratio_4']=train[\"now_4_mean_123\"]/train[\"pre_4_mean_123\"]","metadata":{"execution":{"iopub.status.busy":"2021-07-31T23:44:19.787123Z","iopub.execute_input":"2021-07-31T23:44:19.787409Z","iopub.status.idle":"2021-07-31T23:44:19.83648Z","shell.execute_reply.started":"2021-07-31T23:44:19.787382Z","shell.execute_reply":"2021-07-31T23:44:19.835473Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"#####################################################################################","metadata":{"execution":{"iopub.status.busy":"2021-07-31T23:44:19.837606Z","iopub.execute_input":"2021-07-31T23:44:19.837915Z","iopub.status.idle":"2021-07-31T23:44:19.842358Z","shell.execute_reply.started":"2021-07-31T23:44:19.837885Z","shell.execute_reply":"2021-07-31T23:44:19.841544Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train['now_pre_ratio_1']","metadata":{"execution":{"iopub.status.busy":"2021-07-31T23:44:19.843722Z","iopub.execute_input":"2021-07-31T23:44:19.844285Z","iopub.status.idle":"2021-07-31T23:44:19.860318Z","shell.execute_reply.started":"2021-07-31T23:44:19.844245Z","shell.execute_reply":"2021-07-31T23:44:19.859627Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"###############################\ntr_18=pre_tr[pre_tr['Year']==18].groupby([\"playerId\",\"Month\"]).mean()\ntr_19=pre_tr[pre_tr['Year']==19].groupby([\"playerId\",\"Month\"]).mean()\ntr_20=pre_tr[pre_tr['Year']==20].groupby([\"playerId\",\"Month\"]).mean()\ntr_21=pre_tr[pre_tr['Year']==21].groupby([\"playerId\",\"Month\"]).mean()\n","metadata":{"execution":{"iopub.status.busy":"2021-07-31T23:44:19.861621Z","iopub.execute_input":"2021-07-31T23:44:19.862081Z","iopub.status.idle":"2021-07-31T23:44:20.306468Z","shell.execute_reply.started":"2021-07-31T23:44:19.862032Z","shell.execute_reply":"2021-07-31T23:44:20.305566Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"#############################\ntrain['now_1_mean']=0\ntrain['now_2_mean']=0\ntrain['now_3_mean']=0\ntrain['now_4_mean']=0\ntr_list=[tr_18,tr_19,tr_20,tr_21]\nfor ele in tr_list:\n    train=train.merge(ele,on=[\"playerId\",\"Month\",\"Year\"],how='left',suffixes=('', '_y'))\n    #print(np.nan_to_num(train['target1_y'], copy=False))\n    train['now_1_mean']=np.nan_to_num(train['target1_y'], copy=False)+train['now_1_mean']\n    train['now_2_mean']=np.nan_to_num(train['target2_y'], copy=False)+train['now_2_mean']\n    train['now_3_mean']=np.nan_to_num(train['target3_y'], copy=False)+train['now_3_mean']\n    train['now_4_mean']=np.nan_to_num(train['target4_y'], copy=False)+train['now_4_mean']\n    train=train.drop(['target1_y','target2_y','target3_y','target4_y'],axis=1)\n    \ntrain['now_1_mean']=train['now_1_mean'].map(lambda x : np.nan if x==0 else x)\ntrain['now_2_mean']=train['now_2_mean'].map(lambda x : np.nan if x==0 else x)\ntrain['now_3_mean']=train['now_3_mean'].map(lambda x : np.nan if x==0 else x)\ntrain['now_4_mean']=train['now_4_mean'].map(lambda x : np.nan if x==0 else x)","metadata":{"execution":{"iopub.status.busy":"2021-07-31T23:44:20.307819Z","iopub.execute_input":"2021-07-31T23:44:20.308297Z","iopub.status.idle":"2021-07-31T23:45:06.629183Z","shell.execute_reply.started":"2021-07-31T23:44:20.30825Z","shell.execute_reply":"2021-07-31T23:45:06.627967Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"#\ntrain['pre_1_mean']=0\ntrain['pre_2_mean']=0\ntrain['pre_3_mean']=0\ntrain['pre_4_mean']=0\ntr_list=[tr_18,tr_19,tr_20]\nfor ele in tr_list:\n    ele[\"Year\"]=ele[\"Year\"]+1\n    train=train.merge(ele,on=[\"playerId\",\"Month\",\"Year\"],how='left',suffixes=('', '_y'))\n    ele[\"Year\"]=ele[\"Year\"]-1\n    #print(np.nan_to_num(train['target1_y'], copy=False))\n    train['pre_1_mean']=np.nan_to_num(train['target1_y'], copy=False)+train['pre_1_mean']\n    train['pre_2_mean']=np.nan_to_num(train['target2_y'], copy=False)+train['pre_2_mean']\n    train['pre_3_mean']=np.nan_to_num(train['target3_y'], copy=False)+train['pre_3_mean']\n    train['pre_4_mean']=np.nan_to_num(train['target4_y'], copy=False)+train['pre_4_mean']\n    train=train.drop(['target1_y','target2_y','target3_y','target4_y'],axis=1)\n    \ntrain['pre_1_mean']=train['pre_1_mean'].map(lambda x : np.nan if x==0 else x)\ntrain['pre_2_mean']=train['pre_2_mean'].map(lambda x : np.nan if x==0 else x)\ntrain['pre_3_mean']=train['pre_3_mean'].map(lambda x : np.nan if x==0 else x)\ntrain['pre_4_mean']=train['pre_4_mean'].map(lambda x : np.nan if x==0 else x)\n","metadata":{"execution":{"iopub.status.busy":"2021-07-31T23:45:06.631163Z","iopub.execute_input":"2021-07-31T23:45:06.631623Z","iopub.status.idle":"2021-07-31T23:45:43.944342Z","shell.execute_reply.started":"2021-07-31T23:45:06.631571Z","shell.execute_reply":"2021-07-31T23:45:43.943177Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"##############################\ntrain['ppre_1_mean']=0\ntrain['ppre_2_mean']=0\ntrain['ppre_3_mean']=0\ntrain['ppre_4_mean']=0\nfor ele in [tr_18,tr_19]:\n    ele[\"Year\"]=ele[\"Year\"]+2\n    train=train.merge(ele,on=[\"playerId\",\"Month\",\"Year\"],how='left',suffixes=('', '_y'))\n    ele[\"Year\"]=ele[\"Year\"]-2\n    #print(np.nan_to_num(train['target1_y'], copy=False))\n    train['ppre_1_mean']=np.nan_to_num(train['target1_y'], copy=False)+train['ppre_1_mean']\n    train['ppre_2_mean']=np.nan_to_num(train['target2_y'], copy=False)+train['ppre_2_mean']\n    train['ppre_3_mean']=np.nan_to_num(train['target3_y'], copy=False)+train['ppre_3_mean']\n    train['ppre_4_mean']=np.nan_to_num(train['target4_y'], copy=False)+train['ppre_4_mean']\n    train=train.drop(['target1_y','target2_y','target3_y','target4_y'],axis=1)\n    \ntrain['ppre_1_mean']=train['ppre_1_mean'].map(lambda x : np.nan if x==0 else x)\ntrain['ppre_2_mean']=train['ppre_2_mean'].map(lambda x : np.nan if x==0 else x)\ntrain['ppre_3_mean']=train['ppre_3_mean'].map(lambda x : np.nan if x==0 else x)\ntrain['ppre_4_mean']=train['ppre_4_mean'].map(lambda x : np.nan if x==0 else x)","metadata":{"execution":{"iopub.status.busy":"2021-07-31T23:45:43.946343Z","iopub.execute_input":"2021-07-31T23:45:43.946814Z","iopub.status.idle":"2021-07-31T23:46:10.359409Z","shell.execute_reply.started":"2021-07-31T23:45:43.946769Z","shell.execute_reply":"2021-07-31T23:46:10.358627Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"###########################\ntrain['pppre_1_mean']=0\ntrain['pppre_2_mean']=0\ntrain['pppre_3_mean']=0\ntrain['pppre_4_mean']=0\nfor ele in [tr_18]:\n    ele[\"Year\"]=ele[\"Year\"]+3\n    train=train.merge(ele,on=[\"playerId\",\"Month\",\"Year\"],how='left',suffixes=('', '_y'))\n    ele[\"Year\"]=ele[\"Year\"]-3\n    train['pppre_1_mean']=np.nan_to_num(train['target1_y'], copy=False)+train['pppre_1_mean']\n    train['pppre_2_mean']=np.nan_to_num(train['target2_y'], copy=False)+train['pppre_2_mean']\n    train['pppre_3_mean']=np.nan_to_num(train['target3_y'], copy=False)+train['pppre_3_mean']\n    train['pppre_4_mean']=np.nan_to_num(train['target4_y'], copy=False)+train['pppre_4_mean']\n    train=train.drop(['target1_y','target2_y','target3_y','target4_y'],axis=1)\n    \ntrain['pppre_1_mean']=train['pppre_1_mean'].map(lambda x : np.nan if x==0 else x)\ntrain['pppre_2_mean']=train['pppre_2_mean'].map(lambda x : np.nan if x==0 else x)\ntrain['pppre_3_mean']=train['pppre_3_mean'].map(lambda x : np.nan if x==0 else x)\ntrain['pppre_4_mean']=train['pppre_4_mean'].map(lambda x : np.nan if x==0 else x)","metadata":{"execution":{"iopub.status.busy":"2021-07-31T23:46:10.361045Z","iopub.execute_input":"2021-07-31T23:46:10.361635Z","iopub.status.idle":"2021-07-31T23:46:26.304032Z","shell.execute_reply.started":"2021-07-31T23:46:10.361595Z","shell.execute_reply":"2021-07-31T23:46:26.303179Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"##DEFFFFF\n##########################################################################\n\ntr_18=pre_tr[pre_tr['Year']==18].groupby([\"playerId\",\"Month\"]).median()\ntr_19=pre_tr[pre_tr['Year']==19].groupby([\"playerId\",\"Month\"]).median()\ntr_20=pre_tr[pre_tr['Year']==20].groupby([\"playerId\",\"Month\"]).median()\ntr_21=pre_tr[pre_tr['Year']==21].groupby([\"playerId\",\"Month\"]).median()\np_median=[\n    'now_1_median',\n    'now_2_median',\n    'now_3_median',\n    'now_4_median',\n    'pre_1_median',\n'pre_2_median',\n'pre_3_median',\n'pre_4_median',\n'ppre_1_median',\n'ppre_2_median',\n'ppre_3_median',\n'ppre_4_median',\n'pppre_1_median',\n'pppre_2_median',\n'pppre_3_median',\n'pppre_4_median']\n\ntrain['pre_1_median']=0\ntrain['pre_2_median']=0\ntrain['pre_3_median']=0\ntrain['pre_4_median']=0\ntrain['ppre_1_median']=0\ntrain['ppre_2_median']=0\ntrain['ppre_3_median']=0\ntrain['ppre_4_median']=0\ntrain['pppre_1_median']=0\ntrain['pppre_2_median']=0\ntrain['pppre_3_median']=0\ntrain['pppre_4_median']=0\n\ntrain['now_1_median']=0\ntrain['now_2_median']=0\ntrain['now_3_median']=0\ntrain['now_4_median']=0\ntr_list=[tr_18,tr_19,tr_20,tr_21]\nfor ele in tr_list:\n    train=train.merge(ele,on=[\"playerId\",\"Month\",\"Year\"],how='left',suffixes=('', '_y'))\n    #print(np.nan_to_num(train['target1_y'], copy=False))\n    train['now_1_median']=np.nan_to_num(train['target1_y'], copy=False)+train['now_1_median']\n    train['now_2_median']=np.nan_to_num(train['target2_y'], copy=False)+train['now_2_median']\n    train['now_3_median']=np.nan_to_num(train['target3_y'], copy=False)+train['now_3_median']\n    train['now_4_median']=np.nan_to_num(train['target4_y'], copy=False)+train['now_4_median']\n    train=train.drop(['target1_y','target2_y','target3_y','target4_y'],axis=1)\n    \ntrain['now_1_median']=train['now_1_median'].map(lambda x : np.nan if x==0 else x)\ntrain['now_2_median']=train['now_2_median'].map(lambda x : np.nan if x==0 else x)\ntrain['now_3_median']=train['now_3_median'].map(lambda x : np.nan if x==0 else x)\ntrain['now_4_median']=train['now_4_median'].map(lambda x : np.nan if x==0 else x)\n\n\ntr_list=[tr_18,tr_19,tr_20]\nfor ele in tr_list:\n    ele[\"Year\"]=ele[\"Year\"]+1\n    train=train.merge(ele,on=[\"playerId\",\"Month\",\"Year\"],how='left',suffixes=('', '_y'))\n    ele[\"Year\"]=ele[\"Year\"]-1\n    #print(np.nan_to_num(train['target1_y'], copy=False))\n    train['pre_1_median']=np.nan_to_num(train['target1_y'], copy=False)+train['pre_1_median']\n    train['pre_2_median']=np.nan_to_num(train['target2_y'], copy=False)+train['pre_2_median']\n    train['pre_3_median']=np.nan_to_num(train['target3_y'], copy=False)+train['pre_3_median']\n    train['pre_4_median']=np.nan_to_num(train['target4_y'], copy=False)+train['pre_4_median']\n    train=train.drop(['target1_y','target2_y','target3_y','target4_y'],axis=1)\n    \nfor ele in [tr_18,tr_19]:\n    ele[\"Year\"]=ele[\"Year\"]+2\n    train=train.merge(ele,on=[\"playerId\",\"Month\",\"Year\"],how='left',suffixes=('', '_y'))\n    ele[\"Year\"]=ele[\"Year\"]-2\n    #print(np.nan_to_num(train['target1_y'], copy=False))\n    train['ppre_1_median']=np.nan_to_num(train['target1_y'], copy=False)+train['ppre_1_median']\n    train['ppre_2_median']=np.nan_to_num(train['target2_y'], copy=False)+train['ppre_2_median']\n    train['ppre_3_median']=np.nan_to_num(train['target3_y'], copy=False)+train['ppre_3_median']\n    train['ppre_4_median']=np.nan_to_num(train['target4_y'], copy=False)+train['ppre_4_median']\n    train=train.drop(['target1_y','target2_y','target3_y','target4_y'],axis=1)\n\nfor ele in [tr_18]:\n    ele[\"Year\"]=ele[\"Year\"]+3\n    train=train.merge(ele,on=[\"playerId\",\"Month\",\"Year\"],how='left',suffixes=('', '_y'))\n    ele[\"Year\"]=ele[\"Year\"]-3\n    train['pppre_1_median']=np.nan_to_num(train['target1_y'], copy=False)+train['pppre_1_median']\n    train['pppre_2_median']=np.nan_to_num(train['target2_y'], copy=False)+train['pppre_2_median']\n    train['pppre_3_median']=np.nan_to_num(train['target3_y'], copy=False)+train['pppre_3_median']\n    train['pppre_4_median']=np.nan_to_num(train['target4_y'], copy=False)+train['pppre_4_median']\n    train=train.drop(['target1_y','target2_y','target3_y','target4_y'],axis=1)\n    \ntrain['pppre_1_median']=train['pppre_1_median'].map(lambda x : np.nan if x==0 else x)\ntrain['pppre_2_median']=train['pppre_2_median'].map(lambda x : np.nan if x==0 else x)\ntrain['pppre_3_median']=train['pppre_3_median'].map(lambda x : np.nan if x==0 else x)\ntrain['pppre_4_median']=train['pppre_4_median'].map(lambda x : np.nan if x==0 else x)\ntrain['ppre_1_median']=train['ppre_1_median'].map(lambda x : np.nan if x==0 else x)\ntrain['ppre_2_median']=train['ppre_2_median'].map(lambda x : np.nan if x==0 else x)\ntrain['ppre_3_median']=train['ppre_3_median'].map(lambda x : np.nan if x==0 else x)\ntrain['ppre_4_median']=train['ppre_4_median'].map(lambda x : np.nan if x==0 else x)\n    \ntrain['pre_1_median']=train['pre_1_median'].map(lambda x : np.nan if x==0 else x)\ntrain['pre_2_median']=train['pre_2_median'].map(lambda x : np.nan if x==0 else x)\ntrain['pre_3_median']=train['pre_3_median'].map(lambda x : np.nan if x==0 else x)\ntrain['pre_4_median']=train['pre_4_median'].map(lambda x : np.nan if x==0 else x)\n","metadata":{"execution":{"iopub.status.busy":"2021-07-31T23:46:26.305489Z","iopub.execute_input":"2021-07-31T23:46:26.305997Z","iopub.status.idle":"2021-07-31T23:46:56.777955Z","shell.execute_reply.started":"2021-07-31T23:46:26.305965Z","shell.execute_reply":"2021-07-31T23:46:56.775684Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"# a=train['playerId']==628317 \n# b = train['Day']==19\n# c=a&b\n# train[c]","metadata":{"execution":{"iopub.status.busy":"2021-07-31T23:46:56.779297Z","iopub.status.idle":"2021-07-31T23:46:56.779781Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"\n\n#pd.merge(a.pre_1_mean,a.target1_y,how='inner')\n\n","metadata":{"execution":{"iopub.status.busy":"2021-07-31T23:46:56.780703Z","iopub.status.idle":"2021-07-31T23:46:56.781118Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"\n","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"\n","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"#################################################\nL_YM=['Last_YpM_mean_1',\n'Last_YpM_mean_2',\n'Last_YpM_mean_3',\n'Last_YpM_mean_4',     \n'Last_YnM_mean_1',\n'Last_YnM_mean_2',\n'Last_YnM_mean_3',\n'Last_YnM_mean_4']\n\nRatio=['now_pre_ratio_1',\n'now_pre_ratio_2',\n'now_pre_ratio_3',\n'now_pre_ratio_4']\n\np_mean=[\n    'now_1_mean',\n    'now_2_mean',\n    'now_3_mean',\n    'now_4_mean',    \n'pre_1_mean',\n'pre_2_mean',\n'pre_3_mean',\n'pre_4_mean',\n'ppre_1_mean',\n'ppre_2_mean',\n'ppre_3_mean',\n'ppre_4_mean',\n'pppre_1_mean',\n'pppre_2_mean',\n'pppre_3_mean',\n'pppre_4_mean']\nfeature_cols.append('Month')\nfeature_cols.append('Year')\nfeature_cols.append('Day')\nfeature_cols=feature_cols+p_mean+p_median#+p_std+p_min+p_max+p_prod\nfeature_cols=feature_cols+L_YM+Ratio","metadata":{"execution":{"iopub.status.busy":"2021-07-31T23:46:56.782193Z","iopub.status.idle":"2021-07-31T23:46:56.782614Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"##################################\nfeat_cat=['label_playerId',\n 'label_primaryPositionName',\n 'label_teamId',\n 'label_status',\n 'battingOrder',\n          'Month',\n          'Year',\n          'Day'\n         ]","metadata":{"execution":{"iopub.status.busy":"2021-07-31T23:46:56.783439Z","iopub.status.idle":"2021-07-31T23:46:56.783865Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"#########################################\ntrain_A = train[feature_cols]\ntrain_X = train_A.drop([  \n    'now_1_mean',\n    'now_2_mean',\n    'now_3_mean',\n    'now_4_mean', \n    'now_1_median',\n    'now_2_median',\n    'now_3_median',\n    'now_4_median'],axis=1)\ntrain_y = train[['target1', 'target2', 'target3', 'target4']]\n_index = (train['date'] < 20210401)\ndel train\n# train_X=reduce_mem_usage(train_X)\n# train_y=reduce_mem_usage(train_y)\nx_train = train_X.loc[_index].reset_index(drop=True)\ny_train = train_y.loc[_index].reset_index(drop=True)\nx_valid = train_X.loc[~_index].reset_index(drop=True)\ny_valid = train_y.loc[~_index].reset_index(drop=True)","metadata":{"execution":{"iopub.status.busy":"2021-07-31T23:46:56.784931Z","iopub.status.idle":"2021-07-31T23:46:56.785349Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"#####################################\nfeature_cols.remove('now_1_mean')\nfeature_cols.remove('now_2_mean')\nfeature_cols.remove('now_3_mean')\nfeature_cols.remove('now_4_mean')\nfeature_cols.remove('now_1_median')\nfeature_cols.remove('now_2_median')\nfeature_cols.remove('now_3_median')\nfeature_cols.remove('now_4_median')\n\n","metadata":{"execution":{"iopub.status.busy":"2021-07-31T23:46:56.786171Z","iopub.status.idle":"2021-07-31T23:46:56.786597Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"\n#train['now_pre_ratio_1']","metadata":{"execution":{"iopub.status.busy":"2021-07-31T23:46:56.787523Z","iopub.status.idle":"2021-07-31T23:46:56.788124Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"#####################################################################\ndef fit_lgbm(x_train, y_train, x_valid, y_valid, params: dict=None, verbose=100):\n    oof_pred = np.zeros(len(y_valid), dtype=np.float32)\n    model = lgbm.LGBMRegressor(**params)\n    model.fit(x_train, y_train, \n        eval_set=[(x_valid, y_valid)],  \n        early_stopping_rounds=verbose, \n        verbose=verbose)\n    oof_pred = model.predict(x_valid)\n    score = mean_absolute_error(oof_pred, y_valid)\n    print('mae:', score)\n    return oof_pred, model, score\n\n\n#training lightgbm\n\n# params1 = {'objective':'mae',\n#            'reg_alpha': 0.034605059624253594,\n#            'reg_lambda':  0.11105489465182652, \n#            #'n_estimators': 3633, \n#            'learning_rate': 0.09921314408986122, \n#            'num_leaves': 760, \n#            'feature_fraction': 0.30447491362585494, \n#            #'bagging_fraction': 0.9884451442950513, \n#            #'bagging_freq': 8, \n#            #'min_child_samples': 51\n#           }\nparams1 = {#'categorical_feature':feat_cat,\n            'objective':'mae',\n            'num_leaves': 926,\n            'reg_alpha': 0.1907169216395267, \n            'reg_lambda': 0.6112721068803044,\n#            'reg_alpha': 0.14947461820098767,\n#            'reg_lambda': 0.10185644384043743, \n#            'n_estimators': 3633, \n#            'learning_rate': 0.08046301304430488, \n#            'num_leaves': 674, \n#            'feature_fraction': 0.9101240539122566, \n#            'bagging_fraction': 0.9884451442950513, \n#            'bagging_freq': 8, 'min_child_samples': 51\n}\n\n\nparams2 = {\n 'objective':'mae',\n    'num_leaves': 3\n#  'reg_alpha': 0.1,\n#  'reg_lambda': 0.1, \n#  'n_estimators': 80,\n#  'learning_rate': 0.1,\n#  'random_state': 42,\n#  \"num_leaves\": 22,\n    #'categorical_feature':feat_cat\n}\n\nparams4 = {'objective':'mae',\n#            'reg_alpha': 0.016468100279441976, \n#            'reg_lambda': 0.09128335764019105, \n#            'n_estimators': 9868, \n#            'learning_rate': 0.10528150510326864, \n            'num_leaves': 127, \n#            'feature_fraction': 0.5419185713426886, \n#            'bagging_fraction': 0.2637405128936662, \n#            'bagging_freq': 19, 'min_child_samples': 71, #'categorical_feature':feat_cat\n          }\n\n\nparams3 = {\n 'objective':'mae',\n#  'reg_alpha': 0.1,\n#  'reg_lambda': 0.1, \n#  'n_estimators': 10000,\n#  'learning_rate': 0.1,\n  'random_state': 51,\n#  \"num_leaves\": 100,\n    #'categorical_feature':feat_cat\n}\n\n\noof1, model1, score1 = fit_lgbm(\n    x_train, y_train['target1'],\n    x_valid, y_valid['target1'],\n    params1\n)\n\noof2, model2, score2 = fit_lgbm(\n    x_train, y_train['target2'],\n    x_valid, y_valid['target2'],\n    params2\n)\n\noof3, model3, score3 = fit_lgbm(\n    x_train, y_train['target3'],\n    x_valid, y_valid['target3'],\n    params3\n)\n\noof4, model4, score4 = fit_lgbm(\n    x_train, y_train['target4'],\n    x_valid, y_valid['target4'],\n    params4\n)\n\nscore = (score1+score2+score3+score4) / 4\nprint(f'score: {score}')","metadata":{"execution":{"iopub.status.busy":"2021-07-31T23:46:56.789167Z","iopub.status.idle":"2021-07-31T23:46:56.789595Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"\n","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"###########################################################\nfeature_importance_1 = [(c, i) for i, c in enumerate(model1.feature_importances_)]\nfeature_importance_1.sort(key=lambda tup: tup[0],reverse=True)\nfeature_importance_1\n\nfor feature_idx in feature_importance_1:\n    print(feature_cols[feature_idx[1]],model1.feature_importances_[feature_idx[1]])","metadata":{"execution":{"iopub.status.busy":"2021-07-31T23:46:56.790767Z","iopub.status.idle":"2021-07-31T23:46:56.791182Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"feature_importance_2 = [(c, i) for i, c in enumerate(model2.feature_importances_)]\nfeature_importance_2.sort(key=lambda tup: tup[0],reverse=True)\nfeature_importance_2\n\nfor feature_idx in feature_importance_2:\n    print(feature_cols[feature_idx[1]],model2.feature_importances_[feature_idx[1]])\n    \n","metadata":{"execution":{"iopub.status.busy":"2021-07-31T23:46:56.792087Z","iopub.status.idle":"2021-07-31T23:46:56.792528Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"feature_importance = [(c, i) for i, c in enumerate(model3.feature_importances_)]\nfeature_importance.sort(key=lambda tup: tup[0],reverse=True)\nfeature_importance\n\nfor feature_idx in feature_importance:\n    print(feature_cols[feature_idx[1]],model3.feature_importances_[feature_idx[1]])\n    \nprint('########################################')\nfeature_importance = [(c, i) for i, c in enumerate(model4.feature_importances_)]\nfeature_importance.sort(key=lambda tup: tup[0],reverse=True)\nfeature_importance\n\nfor feature_idx in feature_importance:\n    print(feature_cols[feature_idx[1]],model4.feature_importances_[feature_idx[1]])\n    \n","metadata":{"execution":{"iopub.status.busy":"2021-07-31T23:46:56.793308Z","iopub.status.idle":"2021-07-31T23:46:56.793717Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"# x_train = train_X.loc[_index].reset_index(drop=True)\n# y_train = train_y.loc[_index].reset_index(drop=True)\n# x_valid = train_X.loc[~_index].reset_index(drop=True)\n# y_valid = train_y.loc[~_index].reset_index(drop=True)\nimport optuna\nimport multiprocessing\ndef objective(trial):\n    feat_cat=[]\n#     dtrain = lgbm.Dataset(x_train, label = y_train['target1'], categorical_feature = feat_cat, free_raw_data = False)\n#     dtest  = lgbm.Dataset(x_valid, label = y_valid['target1'], categorical_feature = feat_cat, free_raw_data = False)\n\n    param = {\n        ######################################################################################################\n         'objective': 'mae',\n#         'verbosity': -1,\n#         'boosting_type': 'gbdt',\n#         'max_depth': 6,#trial.suggest_int('max_depth', 5, 6),\n#         'num_leaves': 110,# trial.suggest_int('num_leaves', 35, 128),\n#         'early_stopping_round':100,\n#         'lambda_l1': '0.00024478379179012684',# trial.suggest_loguniform('lambda_l1', 1e-8, 10.0),\n#         'lambda_l2': '0.025186605425907192',#trial.suggest_loguniform('lambda_l2', 1e-8, 10.0),\n#         'feature_fraction': '0.7771121441198704',#trial.suggest_uniform('feature_fraction', 0, 1.0),\n#         'bagging_fraction': '0.21571689323484866',#trial.suggest_uniform('bagging_fraction', 0, 1.0),\n        \n        #############################################################################\n#         'bagging_freq': trial.suggest_int('bagging_freq', 1, 9),\n#         'min_data_in_leaf': trial.suggest_int('min_data_in_leaf', 10, 60),\n#         'min_child_samples': trial.suggest_int('min_child_samples', 5, 100),\n#         'sub_feature': trial.suggest_uniform('sub_feature', 0.0, 1.0),\n#         'sub_row': trial.suggest_uniform('sub_row', 0.0, 1.0)\n        #############################################################################################################\n        #'device': 'gpu',\n        #'num_threads': multiprocessing.cpu_count(),\n        #'num_leaves': 760,\n        'num_leaves': 926,#trial.suggest_int('num_leaves', 256, 1024), \n        #'learning_rate': 0.08046301304430488,\n        #'reg_alpha': 0.034605059624253594,\n        #trial.suggest_loguniform('reg_alpha', 1e-3, 10.0),\n        #'reg_lambda': 0.11105489465182652, #trial.suggest_loguniform('reg_lambda', 1e-3, 10.0), \n        #'n_estimators': trial.suggest_int('n_estimators', 2000, 5000)\n        'feature_fraction': trial.suggest_uniform('feature_fraction', 0, 1.0),\n        'bagging_freq': trial.suggest_int('bagging_freq', 1, 20),\n        'bagging_fraction': trial.suggest_uniform('bagging_fraction', 0, 1.0),\n        #'learning_rate': trial.suggest_loguniform('learning_rate', 1e-3, 0.1),\n        #'min_data_in_leaf': 35,# trial.suggest_int('min_data_in_leaf', 0, 60),\n        #'min_child_samples': trial.suggest_int('min_child_samples', 5, 100) no problem\n        'reg_alpha': 0.1907169216395267, \n        'reg_lambda': 0.6112721068803044,\n        \n#         'reg_alpha': trial.suggest_loguniform('reg_alpha', 1e-3, 10.0),\n#         'reg_lambda': trial.suggest_loguniform('reg_lambda', 1e-3, 10.0), \n    }\n\n    # Add a callback for pruning\n\n    oof_pred = np.zeros(len(y_valid['target1']), dtype=np.float32)\n    model = lgbm.LGBMRegressor(**param)\n    model.fit(x_train, y_train['target1'], \n        eval_set=[(x_valid, y_valid['target1'])],  \n        early_stopping_rounds=100, \n        verbose=False)\n    oof_pred = model.predict(x_valid)\n    accuracy = mean_absolute_error(y_valid['target1'], oof_pred)\n    \n\n    return accuracy\n\nif __name__ == \"__main__\":\n    study = optuna.create_study(direction = 'minimize', pruner = optuna.pruners.MedianPruner(n_warmup_steps = 10))\n    study.optimize(objective, n_trials = 200)\n\n    print(\"Number of finished trials: {}\".format(len(study.trials)))\n\n    print(\"Best trial:\")\n    trial = study.best_trial\n\n    print(\"  Value: {}\".format(trial.value))\n\n    print(\"  Params: \")\n    for key, value in trial.params.items():\n        print(\"    {}: {}\".format(key, value))","metadata":{"execution":{"iopub.status.busy":"2021-07-31T23:46:56.794728Z","iopub.status.idle":"2021-07-31T23:46:56.795124Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"# # x_train = train_X.loc[_index].reset_index(drop=True)\n# # y_train = train_y.loc[_index].reset_index(drop=True)\n# # x_valid = train_X.loc[~_index].reset_index(drop=True)\n# # y_valid = train_y.loc[~_index].reset_index(drop=True)\n# import optuna\n# import multiprocessing\n# def objective(trial):\n#     feat_cat=[]\n# #     dtrain = lgbm.Dataset(x_train, label = y_train['target1'], categorical_feature = feat_cat, free_raw_data = False)\n# #     dtest  = lgbm.Dataset(x_valid, label = y_valid['target1'], categorical_feature = feat_cat, free_raw_data = False)\n\n#     param = {\n#         ######################################################################################################\n#          'objective': 'mae',\n# #         'verbosity': -1,\n# #         'boosting_type': 'gbdt',\n# #         'max_depth': 6,#trial.suggest_int('max_depth', 5, 6),\n# #         'num_leaves': 110,# trial.suggest_int('num_leaves', 35, 128),\n# #         'early_stopping_round':100,\n# #         'lambda_l1': '0.00024478379179012684',# trial.suggest_loguniform('lambda_l1', 1e-8, 10.0),\n# #         'lambda_l2': '0.025186605425907192',#trial.suggest_loguniform('lambda_l2', 1e-8, 10.0),\n# #         'feature_fraction': '0.7771121441198704',#trial.suggest_uniform('feature_fraction', 0, 1.0),\n# #         'bagging_fraction': '0.21571689323484866',#trial.suggest_uniform('bagging_fraction', 0, 1.0),\n        \n#         #############################################################################\n# #         'bagging_freq': trial.suggest_int('bagging_freq', 1, 9),\n# #         'min_data_in_leaf': trial.suggest_int('min_data_in_leaf', 10, 60),\n# #         'min_child_samples': trial.suggest_int('min_child_samples', 5, 100),\n# #         'sub_feature': trial.suggest_uniform('sub_feature', 0.0, 1.0),\n# #         'sub_row': trial.suggest_uniform('sub_row', 0.0, 1.0)\n#         #############################################################################################################\n#         #'device': 'gpu',\n#         #'num_threads': multiprocessing.cpu_count(),\n#         #'num_leaves': 760,\n#         'num_leaves': trial.suggest_int('num_leaves', 0, 555),#3\n#         #'learning_rate': 0.08046301304430488,\n#         #'reg_alpha': 0.034605059624253594,# trial.suggest_loguniform('reg_alpha', 1e-3, 10.0),\n#         #'reg_lambda': 0.11105489465182652, #trial.suggest_loguniform('reg_lambda', 1e-3, 10.0), \n#         #'n_estimators': trial.suggest_int('n_estimators', 2000, 5000)\n#         #'feature_fraction': 0.30447491362585494,# trial.suggest_uniform('feature_fraction', 0, 1.0),\n#         #'bagging_freq': trial.suggest_int('bagging_freq', 1, 20),\n#         #'bagging_fraction': trial.suggest_uniform('bagging_fraction', 0, 1.0),\n#         #'learning_rate': trial.suggest_loguniform('learning_rate', 1e-3, 0.1),\n#         #'min_data_in_leaf': 35,# trial.suggest_int('min_data_in_leaf', 0, 60),\n#         #'min_child_samples': trial.suggest_int('min_child_samples', 5, 100) no problem\n#     }\n\n#     # Add a callback for pruning\n\n#     oof_pred = np.zeros(len(y_valid['target2']), dtype=np.float32)\n#     model = lgbm.LGBMRegressor(**param)\n#     model.fit(x_train, y_train['target2'], \n#         eval_set=[(x_valid, y_valid['target2'])],  \n#         early_stopping_rounds=100, \n#         verbose=False)\n#     oof_pred = model.predict(x_valid)\n#     accuracy = mean_absolute_error(y_valid['target2'], oof_pred)\n    \n\n#     return accuracy\n\n# if __name__ == \"__main__\":\n#     study = optuna.create_study(direction = 'minimize', pruner = optuna.pruners.MedianPruner(n_warmup_steps = 10))\n#     study.optimize(objective, n_trials = 300)\n\n#     print(\"Number of finished trials: {}\".format(len(study.trials)))\n\n#     print(\"Best trial:\")\n#     trial = study.best_trial\n\n#     print(\"  Value: {}\".format(trial.value))\n\n#     print(\"  Params: \")\n#     for key, value in trial.params.items():\n#         print(\"    {}: {}\".format(key, value))","metadata":{"execution":{"iopub.status.busy":"2021-07-31T23:46:56.796268Z","iopub.status.idle":"2021-07-31T23:46:56.796693Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"# # x_train = train_X.loc[_index].reset_index(drop=True)\n# # y_train = train_y.loc[_index].reset_index(drop=True)\n# # x_valid = train_X.loc[~_index].reset_index(drop=True)\n# # y_valid = train_y.loc[~_index].reset_index(drop=True)\n# import optuna\n# import multiprocessing\n# def objective(trial):\n#     feat_cat=[]\n# #     dtrain = lgbm.Dataset(x_train, label = y_train['target1'], categorical_feature = feat_cat, free_raw_data = False)\n# #     dtest  = lgbm.Dataset(x_valid, label = y_valid['target1'], categorical_feature = feat_cat, free_raw_data = False)\n\n#     param = {\n#         ######################################################################################################\n#          'objective': 'mae',\n# #         'verbosity': -1,\n# #         'boosting_type': 'gbdt',\n# #         'max_depth': 6,#trial.suggest_int('max_depth', 5, 6),\n# #         'num_leaves': 110,# trial.suggest_int('num_leaves', 35, 128),\n# #         'early_stopping_round':100,\n# #         'lambda_l1': '0.00024478379179012684',# trial.suggest_loguniform('lambda_l1', 1e-8, 10.0),\n# #         'lambda_l2': '0.025186605425907192',#trial.suggest_loguniform('lambda_l2', 1e-8, 10.0),\n# #         'feature_fraction': '0.7771121441198704',#trial.suggest_uniform('feature_fraction', 0, 1.0),\n# #         'bagging_fraction': '0.21571689323484866',#trial.suggest_uniform('bagging_fraction', 0, 1.0),\n        \n#         #############################################################################\n# #         'bagging_freq': trial.suggest_int('bagging_freq', 1, 9),\n# #         'min_data_in_leaf': trial.suggest_int('min_data_in_leaf', 10, 60),\n# #         'min_child_samples': trial.suggest_int('min_child_samples', 5, 100),\n# #         'sub_feature': trial.suggest_uniform('sub_feature', 0.0, 1.0),\n# #         'sub_row': trial.suggest_uniform('sub_row', 0.0, 1.0)\n#         #############################################################################################################\n#         #'device': 'gpu',\n#         #'num_threads': multiprocessing.cpu_count(),\n#         #'num_leaves': 760,\n#         'num_leaves': trial.suggest_int('num_leaves', 0, 1024),#127\n#         #'learning_rate': 0.08046301304430488,\n#         #'reg_alpha': 0.034605059624253594,# trial.suggest_loguniform('reg_alpha', 1e-3, 10.0),\n#         #'reg_lambda': 0.11105489465182652, #trial.suggest_loguniform('reg_lambda', 1e-3, 10.0), \n#         #'n_estimators': trial.suggest_int('n_estimators', 2000, 5000)\n#         #'feature_fraction': 0.30447491362585494,# trial.suggest_uniform('feature_fraction', 0, 1.0),\n#         #'bagging_freq': trial.suggest_int('bagging_freq', 1, 20),\n#         #'bagging_fraction': trial.suggest_uniform('bagging_fraction', 0, 1.0),\n#         #'learning_rate': trial.suggest_loguniform('learning_rate', 1e-3, 0.1),\n#         #'min_data_in_leaf': 35,# trial.suggest_int('min_data_in_leaf', 0, 60),\n#         #'min_child_samples': trial.suggest_int('min_child_samples', 5, 100) no problem\n#     }\n\n#     # Add a callback for pruning\n\n#     oof_pred = np.zeros(len(y_valid['target3']), dtype=np.float32)\n#     model = lgbm.LGBMRegressor(**param)\n#     model.fit(x_train, y_train['target3'], \n#         eval_set=[(x_valid, y_valid['target3'])],  \n#         early_stopping_rounds=100, \n#         verbose=False)\n#     oof_pred = model.predict(x_valid)\n#     accuracy = mean_absolute_error(y_valid['target3'], oof_pred)\n    \n\n#     return accuracy\n\n# if __name__ == \"__main__\":\n#     study = optuna.create_study(direction = 'minimize', pruner = optuna.pruners.MedianPruner(n_warmup_steps = 10))\n#     study.optimize(objective, n_trials = 300)\n\n#     print(\"Number of finished trials: {}\".format(len(study.trials)))\n\n#     print(\"Best trial:\")\n#     trial = study.best_trial\n\n#     print(\"  Value: {}\".format(trial.value))\n\n#     print(\"  Params: \")\n#     for key, value in trial.params.items():\n#         print(\"    {}: {}\".format(key, value))","metadata":{"execution":{"iopub.status.busy":"2021-07-31T23:46:56.797678Z","iopub.status.idle":"2021-07-31T23:46:56.79817Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"# # x_train = train_X.loc[_index].reset_index(drop=True)\n# # y_train = train_y.loc[_index].reset_index(drop=True)\n# # x_valid = train_X.loc[~_index].reset_index(drop=True)\n# # y_valid = train_y.loc[~_index].reset_index(drop=True)\n# import optuna\n# import multiprocessing\n# def objective(trial):\n#     feat_cat=[]\n# #     dtrain = lgbm.Dataset(x_train, label = y_train['target1'], categorical_feature = feat_cat, free_raw_data = False)\n# #     dtest  = lgbm.Dataset(x_valid, label = y_valid['target1'], categorical_feature = feat_cat, free_raw_data = False)\n\n#     param = {\n#         ######################################################################################################\n#          'objective': 'mae',\n# #         'verbosity': -1,\n# #         'boosting_type': 'gbdt',\n# #         'max_depth': 6,#trial.suggest_int('max_depth', 5, 6),\n# #         'num_leaves': 110,# trial.suggest_int('num_leaves', 35, 128),\n# #         'early_stopping_round':100,\n# #         'lambda_l1': '0.00024478379179012684',# trial.suggest_loguniform('lambda_l1', 1e-8, 10.0),\n# #         'lambda_l2': '0.025186605425907192',#trial.suggest_loguniform('lambda_l2', 1e-8, 10.0),\n# #         'feature_fraction': '0.7771121441198704',#trial.suggest_uniform('feature_fraction', 0, 1.0),\n# #         'bagging_fraction': '0.21571689323484866',#trial.suggest_uniform('bagging_fraction', 0, 1.0),\n        \n#         #############################################################################\n# #         'bagging_freq': trial.suggest_int('bagging_freq', 1, 9),\n# #         'min_data_in_leaf': trial.suggest_int('min_data_in_leaf', 10, 60),\n# #         'min_child_samples': trial.suggest_int('min_child_samples', 5, 100),\n# #         'sub_feature': trial.suggest_uniform('sub_feature', 0.0, 1.0),\n# #         'sub_row': trial.suggest_uniform('sub_row', 0.0, 1.0)\n#         #############################################################################################################\n#         #'device': 'gpu',\n#         #'num_threads': multiprocessing.cpu_count(),\n#         #'num_leaves': 760,\n#         'num_leaves': trial.suggest_int('num_leaves', 0, 1024),#51\n#         #'learning_rate': 0.08046301304430488,\n#         #'reg_alpha': 0.034605059624253594,# trial.suggest_loguniform('reg_alpha', 1e-3, 10.0),\n#         #'reg_lambda': 0.11105489465182652, #trial.suggest_loguniform('reg_lambda', 1e-3, 10.0), \n#         #'n_estimators': trial.suggest_int('n_estimators', 2000, 5000)\n#         #'feature_fraction': 0.30447491362585494,# trial.suggest_uniform('feature_fraction', 0, 1.0),\n#         #'bagging_freq': trial.suggest_int('bagging_freq', 1, 20),\n#         #'bagging_fraction': trial.suggest_uniform('bagging_fraction', 0, 1.0),\n#         #'learning_rate': trial.suggest_loguniform('learning_rate', 1e-3, 0.1),\n#         #'min_data_in_leaf': 35,# trial.suggest_int('min_data_in_leaf', 0, 60),\n#         #'min_child_samples': trial.suggest_int('min_child_samples', 5, 100) no problem\n#     }\n\n#     # Add a callback for pruning\n\n#     oof_pred = np.zeros(len(y_valid['target4']), dtype=np.float32)\n#     model = lgbm.LGBMRegressor(**param)\n#     model.fit(x_train, y_train['target4'], \n#         eval_set=[(x_valid, y_valid['target4'])],  \n#         early_stopping_rounds=100, \n#         verbose=False)\n#     oof_pred = model.predict(x_valid)\n#     accuracy = mean_absolute_error(y_valid['target4'], oof_pred)\n    \n\n#     return accuracy\n\n# if __name__ == \"__main__\":\n#     study = optuna.create_study(direction = 'minimize', pruner = optuna.pruners.MedianPruner(n_warmup_steps = 10))\n#     study.optimize(objective, n_trials = 100)\n\n#     print(\"Number of finished trials: {}\".format(len(study.trials)))\n\n#     print(\"Best trial:\")\n#     trial = study.best_trial\n\n#     print(\"  Value: {}\".format(trial.value))\n\n#     print(\"  Params: \")\n#     for key, value in trial.params.items():\n#         print(\"    {}: {}\".format(key, value))","metadata":{"execution":{"iopub.status.busy":"2021-07-31T23:46:56.799052Z","iopub.status.idle":"2021-07-31T23:46:56.799463Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"###########################################################\nimport pandas as pd\nimport numpy as np\nfrom datetime import timedelta\nfrom tqdm import tqdm\n\nimport gc\nfrom functools import reduce\nfrom sklearn.model_selection import StratifiedKFold\n\nROOT_DIR = \"../input/mlb-player-digital-engagement-forecasting\"\n\n#=======================#\ndef flatten(df, col):\n    du = (df.pivot(index=\"playerId\", columns=\"EvalDate\", \n               values=col).add_prefix(f\"{col}_\").\n      rename_axis(None, axis=1).reset_index())\n    return du\n#============================#\ndef reducer(left, right):\n    return left.merge(right, on=\"playerId\")\n#========================\n\nTGTCOLS = [\"target1\",\"target2\",\"target3\",\"target4\"]\ndef train_lag(df, lag=1):\n    dp = df[[\"playerId\",\"EvalDate\"]+TGTCOLS].copy()\n    dp[\"EvalDate\"]  =dp[\"EvalDate\"] + timedelta(days=lag) \n    df = df.merge(dp, on=[\"playerId\", \"EvalDate\"], suffixes=[\"\",f\"_{lag}\"], how=\"left\")\n    return df\n#=================================\ndef test_lag(sub):\n    sub[\"playerId\"] = sub[\"date_playerId\"].apply(lambda s: int(  s.split(\"_\")[1]  ) )\n    assert sub.date.nunique() == 1\n    dte = sub[\"date\"].unique()[0]\n    \n    eval_dt = pd.to_datetime(dte, format=\"%Y%m%d\")\n    dtes = [eval_dt + timedelta(days=-k) for k in LAGS]\n    mp_dtes = {eval_dt + timedelta(days=-k):k for k in LAGS}\n    \n    sl = LAST.loc[LAST.EvalDate.between(dtes[-1], dtes[0]), [\"EvalDate\",\"playerId\"]+TGTCOLS].copy()\n    sl[\"EvalDate\"] = sl[\"EvalDate\"].map(mp_dtes)\n    du = [flatten(sl, col) for col in TGTCOLS]\n    du = reduce(reducer, du)\n    return du, eval_dt\n    #\n#===============\n\ntr = pd.read_csv(\"../input/mlb-data/target.csv\")\nprint(tr.shape)\ngc.collect()\n\ntr[\"EvalDate\"] = pd.to_datetime(tr[\"EvalDate\"])\ntr[\"EvalDate\"] = tr[\"EvalDate\"] + timedelta(days=-1)\ntr[\"EvalYear\"] = tr[\"EvalDate\"].dt.year\n\nMED_DF = tr.groupby([\"playerId\",\"EvalYear\"])[TGTCOLS].median().reset_index()\nMEDCOLS = [\"tgt1_med\",\"tgt2_med\", \"tgt3_med\", \"tgt4_med\"]\nMED_DF.columns = [\"playerId\",\"EvalYear\"] + MEDCOLS\n\nLAGS = list(range(1,21))\nFECOLS = [f\"{col}_{lag}\" for lag in reversed(LAGS) for col in TGTCOLS]\n\nfor lag in tqdm(LAGS):\n    tr = train_lag(tr, lag=lag)\n    gc.collect()\n#===========\ntr = tr.sort_values(by=[\"playerId\", \"EvalDate\"])\nprint(tr.shape)\ntr = tr.dropna()\nprint(tr.shape)\ntr = tr.merge(MED_DF, on=[\"playerId\",\"EvalYear\"])\ngc.collect()\n\ntr=reduce_mem_usage(tr)\n\nX = tr[FECOLS+MEDCOLS].values\ny = tr[TGTCOLS].values\ncl = tr[\"playerId\"].values\n\nNFOLDS = 6\n\nskf = StratifiedKFold(n_splits=NFOLDS)\nfolds = skf.split(X, cl)\nfolds = list(folds)\n\nX\n\nimport tensorflow as tf\nimport tensorflow.keras.layers as L\nimport tensorflow.keras.models as M\nfrom sklearn.metrics import mean_absolute_error, mean_squared_error\nfrom tensorflow.keras.callbacks import ModelCheckpoint, ReduceLROnPlateau, EarlyStopping\n\ntf.random.set_seed(777)\n\ndef make_model(n_in):\n    inp = L.Input(name=\"inputs\", shape=(n_in,))\n    x = L.Dense(50, activation=\"relu\", name=\"d1\")(inp)\n    x = L.Dense(50, activation=\"relu\", name=\"d2\")(x)\n    preds = L.Dense(4, activation=\"linear\", name=\"preds\")(x)\n    \n    model = M.Model(inp, preds, name=\"ANN\")\n    model.compile(loss=\"mean_absolute_error\", optimizer=\"adam\")\n    return model\n\nnet = make_model(X.shape[1])\nprint(net.summary())\n\noof = np.zeros(y.shape)\nnets = []\nfor idx in range(NFOLDS):\n    print(\"FOLD:\", idx)\n    tr_idx, val_idx = folds[idx]\n    ckpt = ModelCheckpoint(f\"w{idx}.h5\", monitor='val_loss', verbose=1, save_best_only=True,mode='min')\n    reduce_lr = ReduceLROnPlateau(monitor='val_loss', factor=0.2,patience=3, min_lr=0.0005)\n    es = EarlyStopping(monitor='val_loss', patience=6)\n    reg = make_model(X.shape[1])\n    reg.fit(X[tr_idx], y[tr_idx], epochs=10, batch_size=35_000, validation_data=(X[val_idx], y[val_idx]),\n            verbose=1, callbacks=[ckpt, reduce_lr, es])\n    reg.load_weights(f\"w{idx}.h5\")\n    oof[val_idx] = reg.predict(X[val_idx], batch_size=50_000, verbose=1)\n    nets.append(reg)\n    gc.collect()\n    \n\n\nmae = mean_absolute_error(y, oof)\nmse = mean_squared_error(y, oof, squared=False)\nprint(\"mae:\", mae)\nprint(\"mse:\", mse)\n\n# Historical information to use in prediction time\nbound_dt = pd.to_datetime(\"2021-01-01\")\nLAST = tr.loc[tr.EvalDate>bound_dt].copy()\n\nLAST_MED_DF = MED_DF.loc[MED_DF.EvalYear==2021].copy()\nLAST_MED_DF.drop(\"EvalYear\", axis=1, inplace=True)\ndel tr\n\n#\"\"\"\nimport mlb\nFE = []; SUB = [];","metadata":{"execution":{"iopub.status.busy":"2021-07-31T23:46:56.800429Z","iopub.status.idle":"2021-07-31T23:46:56.800849Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"###########################################################\nplayers_cols = ['playerId', 'primaryPositionName']\nrosters_cols = ['playerId', 'teamId', 'status']\nscores_cols = ['playerId', 'battingOrder', 'gamesPlayedBatting', 'flyOuts',\n       'groundOuts', 'runsScored', 'doubles', 'triples', 'homeRuns',\n       'strikeOuts', 'baseOnBalls', 'intentionalWalks', 'hits', 'hitByPitch',\n       'atBats', 'caughtStealing', 'stolenBases', 'groundIntoDoublePlay',\n       'groundIntoTriplePlay', 'plateAppearances', 'totalBases', 'rbi',\n       'leftOnBase', 'sacBunts', 'sacFlies', 'catchersInterference',\n       'pickoffs', 'gamesPlayedPitching', 'gamesStartedPitching',\n       'completeGamesPitching', 'shutoutsPitching', 'winsPitching',\n       'lossesPitching', 'flyOutsPitching', 'airOutsPitching',\n       'groundOutsPitching', 'runsPitching', 'doublesPitching',\n       'triplesPitching', 'homeRunsPitching', 'strikeOutsPitching',\n       'baseOnBallsPitching', 'intentionalWalksPitching', 'hitsPitching',\n       'hitByPitchPitching', 'atBatsPitching', 'caughtStealingPitching',\n       'stolenBasesPitching', 'inningsPitched', 'saveOpportunities',\n       'earnedRuns', 'battersFaced', 'outsPitching', 'pitchesThrown', 'balls',\n       'strikes', 'hitBatsmen', 'balks', 'wildPitches', 'pickoffsPitching',\n       'rbiPitching', 'gamesFinishedPitching', 'inheritedRunners',\n       'inheritedRunnersScored', 'catchersInterferencePitching',\n       'sacBuntsPitching', 'sacFliesPitching', 'saves', 'holds', 'blownSaves',\n       'assists', 'putOuts', 'errors', 'chances']\n\nnull = np.nan\ntrue = True\nfalse = False","metadata":{"execution":{"iopub.status.busy":"2021-07-31T23:46:56.801638Z","iopub.status.idle":"2021-07-31T23:46:56.802027Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"##############################################\nimport copy\n\nenv = mlb.make_env() # initialize the environment\niter_test = env.iter_test() # iterator which loops over each date in test set\ntrain_A['Year']=train_A['Year']+1 # to get 1 year before data\nfor (test_df, sample_prediction_df) in iter_test: # make predictions here\n    \n\n    #for (test_df, sample_prediction_df) in iter_test: # make predictions here\n    \n    sub = copy.deepcopy(sample_prediction_df.reset_index())\n    sample_prediction_df = copy.deepcopy(sample_prediction_df.reset_index(drop=True))\n    \n    # LGBM summit\n    # creat dataset\n    sample_prediction_df['playerId'] = sample_prediction_df['date_playerId']\\\n                                        .map(lambda x: int(x.split('_')[1]))\n    # Dealing with missing values\n    if test_df['rosters'].iloc[0] == test_df['rosters'].iloc[0]:\n        test_rosters = pd.DataFrame(eval(test_df['rosters'].iloc[0]))\n    else:\n        test_rosters = pd.DataFrame({'playerId': sample_prediction_df['playerId']})\n        for col in rosters.columns:\n            if col == 'playerId': continue\n            test_rosters[col] = np.nan\n            \n    if test_df['playerBoxScores'].iloc[0] == test_df['playerBoxScores'].iloc[0]:\n        test_scores = pd.DataFrame(eval(test_df['playerBoxScores'].iloc[0]))\n    else:\n        test_scores = pd.DataFrame({'playerId': sample_prediction_df['playerId']})\n        for col in scores.columns:\n            if col == 'playerId': continue\n            test_scores[col] = np.nan\n    test_scores = test_scores.groupby('playerId').sum().reset_index()\n    test = sample_prediction_df[['playerId']].copy()\n    test = test.merge(players[players_cols], on='playerId', how='left')\n    test = test.merge(test_rosters[rosters_cols], on='playerId', how='left')\n    test = test.merge(test_scores[scores_cols], on='playerId', how='left')\n    test = test.merge(player_target_stats, how='inner', left_on=[\"playerId\"],right_on=[\"playerId\"])\n    \n\n    test['label_playerId'] = test['playerId'].map(player2num)\n    test['label_primaryPositionName'] = test['primaryPositionName'].map(position2num)\n    test['label_teamId'] = test['teamId'].map(teamid2num)\n    test['label_status'] = test['status'].map(status2num)\n   \n    test['Year']=int(test_rosters['gameDate'][0][2:4])\n    test['Month']=int(test_rosters['gameDate'][0][5:7])\n    test['Day']=int(test_rosters['gameDate'][0][8:10])\n    test=pd.merge(test,train_A[['label_playerId','Month','Year','Day','now_1_mean','now_2_mean',\n    'now_3_mean',\n    'now_4_mean', \n    'now_1_median',\n    'now_2_median',\n    'now_3_median',\n    'now_4_median',\n    'pre_1_mean',\n    'pre_2_mean', \n     'pre_3_mean',\n     'pre_4_mean',\n     'ppre_1_mean',\n     'ppre_2_mean',\n     'ppre_3_mean',\n     'ppre_4_mean',\n     'pppre_1_mean',\n     'pppre_2_mean',\n     'pppre_3_mean',\n     'pppre_4_mean',\n     'pre_1_median',\n     'pre_2_median',\n     'pre_3_median',\n     'pre_4_median',\n     'ppre_1_median',\n     'ppre_2_median',\n     'ppre_3_median',\n     'ppre_4_median',\n     'pppre_1_median',\n     'pppre_2_median',\n     'pppre_3_median',\n     'pppre_4_median']],on=[\"label_playerId\",\"Year\",\"Month\",'Day'],how='inner',suffixes=('', '_after'))\n\n    test=test.drop([\n     'pppre_1_mean',\n     'pppre_2_mean',\n     'pppre_3_mean',\n     'pppre_4_mean', \n     'pppre_1_median',\n     'pppre_2_median',\n     'pppre_3_median',\n     'pppre_4_median'],axis=1)\n\n    C_list=['now_1_mean',\n    'now_2_mean',\n    'now_3_mean',\n    'now_4_mean', \n    'now_1_median',\n    'now_2_median',\n    'now_3_median',\n    'now_4_median',\n     'pre_1_mean',\n     'pre_2_mean',\n     'pre_3_mean',\n     'pre_4_mean',\n     'pre_1_median',\n     'pre_2_median',\n     'pre_3_median',\n     'pre_4_median',\n     'ppre_1_mean',\n     'ppre_2_mean',\n     'ppre_3_mean',\n     'ppre_4_mean',\n     'ppre_1_median',\n     'ppre_2_median',\n     'ppre_3_median',\n     'ppre_4_median',\n     'pppre_1_mean',\n     'pppre_2_mean',\n     'pppre_3_mean',\n     'pppre_4_mean',\n     'pppre_1_median',\n     'pppre_2_median',\n     'pppre_3_median',\n     'pppre_4_median']\n    #df.rename(columns={'oldName1': 'newName1', 'oldName2': 'newName2'}, inplace=True)\n    for idx in range(len(C_list)-9,-1,-1):\n        a=C_list[idx]\n        b=C_list[idx+8]\n        c={a:b}\n    \n        test.rename(columns=c,inplace=True)\n\n        \n        \n        \n    ########################################################################################################################\n    \n    test['Last_YpM_mean_1']=0\n    test['Last_YpM_mean_2']=0\n    test['Last_YpM_mean_3']=0\n    test['Last_YpM_mean_4']=0        \n    test['Last_YnM_mean_1']=0\n    test['Last_YnM_mean_2']=0\n    test['Last_YnM_mean_3']=0\n    test['Last_YnM_mean_4']=0\n\n\n\n    for num,Id in enumerate(test['playerId'].unique()):\n        year = test['Year'].mean()\n        month = test['Month'].mean()\n        Yp = year -1\n        Yn = year -1\n        Mp = month -1\n        Mn = month +1\n\n        if month==1:\n            Yp=year-2\n            Mp=12\n        elif month==12:\n            Yn=year\n            Mn=1\n\n        tr_pId = test['playerId']==Id\n        tr_M = test['Month']==month\n        tr_Y = test['Year']==year\n        c = tr_pId & tr_M & tr_Y\n        try:\n            test.loc[test[c].index,'Last_YpM_mean_1']=mean_IdYM.loc[(Id,Yp,Mp)].target1\n        except:\n            test.loc[test[c].index,'Last_YpM_mean_1']=np.nan\n        try:\n            test.loc[test[c].index,'Last_YpM_mean_2']=mean_IdYM.loc[(Id,Yp,Mp)].target2\n        except:\n            test.loc[test[c].index,'Last_YpM_mean_2']=np.nan\n        try:\n            test.loc[test[c].index,'Last_YpM_mean_3']=mean_IdYM.loc[(Id,Yp,Mp)].target3\n        except:\n            test.loc[test[c].index,'Last_YpM_mean_3']=np.nan\n        try:\n            test.loc[test[c].index,'Last_YpM_mean_4']=mean_IdYM.loc[(Id,Yp,Mp)].target4\n        except:\n            test.loc[test[c].index,'Last_YpM_mean_4']=np.nan            \n\n\n        try:\n            test.loc[test[c].index,'Last_YnM_mean_1']=mean_IdYM.loc[(Id,Yn,Mn)].target1\n        except:\n            test.loc[test[c].index,'Last_YnM_mean_1']=np.nan\n        try:\n            test.loc[test[c].index,'Last_YnM_mean_2']=mean_IdYM.loc[(Id,Yn,Mn)].target2\n        except:\n            test.loc[test[c].index,'Last_YnM_mean_2']=np.nan\n        try:\n            test.loc[test[c].index,'Last_YnM_mean_3']=mean_IdYM.loc[(Id,Yn,Mn)].target3\n        except:\n            test.loc[test[c].index,'Last_YnM_mean_3']=np.nan\n        try:\n            test.loc[test[c].index,'Last_YnM_mean_4']=mean_IdYM.loc[(Id,Yn,Mn)].target4\n        except:\n            test.loc[test[c].index,'Last_YnM_mean_4']=np.nan\n\n\n    test['now_pre_ratio_1']=0\n    test['now_pre_ratio_2']=0\n    test['now_pre_ratio_3']=0\n    test['now_pre_ratio_4']=0\n    Year_21=train_A[\"Year\"]==22\n    for num,Id in enumerate(test['label_playerId'].unique()):\n        \n        ID=train_A[\"label_playerId\"]==Id\n        c = Year_21 & ID\n        df=train_A[c]\n        test.loc[test[test['label_playerId']==Id].index,'now_pre_ratio_1']=df.iloc[0].now_pre_ratio_1\n        test.loc[test[test['label_playerId']==Id].index,'now_pre_ratio_2']=df.iloc[0].now_pre_ratio_2\n        test.loc[test[test['label_playerId']==Id].index,'now_pre_ratio_3']=df.iloc[0].now_pre_ratio_3\n        test.loc[test[test['label_playerId']==Id].index,'now_pre_ratio_4']=df.iloc[0].now_pre_ratio_4\n                \n                    \n            \n    \n        \n\n\n    \n    \n    ##########################################################################################################\n    \n    test_X = test[feature_cols]\n\n\n#     # predict\n    pred1 = model1.predict(test_X)\n    pred2 = model2.predict(test_X)\n    pred3 = model3.predict(test_X)\n    pred4 = model4.predict(test_X)\n    \n    # merge submission\n    sample_prediction_df['target1'] = np.clip(pred1, 0, 100)\n    sample_prediction_df['target2'] = np.clip(pred2, 0, 100)\n    sample_prediction_df['target3'] = np.clip(pred3, 0, 100)\n    sample_prediction_df['target4'] = np.clip(pred4, 0, 100)\n    sample_prediction_df = sample_prediction_df.fillna(0.)\n    del sample_prediction_df['playerId']\n    # TF summit\n    # Features computation at Evaluation Date\n    sub_fe, eval_dt = test_lag(sub)\n    sub_fe = sub_fe.merge(LAST_MED_DF, on=\"playerId\", how=\"left\")\n    sub_fe = sub_fe.fillna(0.)\n    \n    _preds = 0.\n    for reg in nets:\n        _preds += reg.predict(sub_fe[FECOLS + MEDCOLS]) / NFOLDS\n    sub_fe[TGTCOLS] = np.clip(_preds, 0, 100)\n    sub.drop([\"date\"]+TGTCOLS, axis=1, inplace=True)\n    sub = sub.merge(sub_fe[[\"playerId\"]+TGTCOLS], on=\"playerId\", how=\"left\")\n    sub.drop(\"playerId\", axis=1, inplace=True)\n    sub = sub.fillna(0.)\n    #Blending\n    blend = pd.concat(\n        [sub[['date_playerId']],\n        (0.01*sub.drop('date_playerId', axis=1) + 0.99*sample_prediction_df.drop('date_playerId', axis=1))],\n        \n        axis=1\n    )\n    env.predict(blend)\n    # Update Available information\n    sub_fe[\"EvalDate\"] = eval_dt\n    #sub_fe.drop(MEDCOLS, axis=1, inplace=True)\n    LAST = LAST.append(sub_fe)\n    LAST = LAST.drop_duplicates(subset=[\"EvalDate\",\"playerId\"], keep=\"last\")\ntrain_A['Year']=train_A['Year']-1","metadata":{"execution":{"iopub.status.busy":"2021-07-31T23:46:56.803092Z","iopub.status.idle":"2021-07-31T23:46:56.803509Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"pd.concat(\n    [sub[['date_playerId']],\n    (sub.drop('date_playerId', axis=1) + sample_prediction_df.drop('date_playerId', axis=1)) / 2],\n    axis=1\n)","metadata":{"execution":{"iopub.status.busy":"2021-07-31T23:46:56.804313Z","iopub.status.idle":"2021-07-31T23:46:56.804733Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"sample_prediction_df","metadata":{"execution":{"iopub.status.busy":"2021-07-31T23:46:56.805589Z","iopub.status.idle":"2021-07-31T23:46:56.805987Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"del w0.h5\n\ndel w1.h5\n\ndel w2.h5\n\ndel w3.h5\n\ndel w4.h5\n\ndel w5.h5","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"\n\n    \n    \n    \n    \n    ","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"","metadata":{},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"","metadata":{},"execution_count":null,"outputs":[]}]}