{"cells":[{"metadata":{"trusted":true},"cell_type":"code","source":"!pip install ProgressBar","execution_count":null,"outputs":[]},{"metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true},"cell_type":"code","source":"\nimport numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\nimport glob \nfrom progressbar import ProgressBar","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"train_frag = glob.glob(\"../input/predict-volcanic-eruptions-ingv-oe/test/*\")\n\ntrain_means=[]\n\npbar = ProgressBar()\nfor i in pbar(train_frag):\n    train_means = np.append(train_means,pd.read_csv(i).mean().max())","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"'''\ntrain_frag = glob.glob(\"../input/predict-volcanic-eruptions-ingv-oe/train/*\")\n\ndata_tot =pd.read_csv(train_frag[0])\ndata_tot.columns = [['s1_0','s2_0','s3_0','s4_0','s5_0','s6_0','s7_0','s8_0','s9_0','s10_0']]\npbar = ProgressBar()\nj = 0\nfor i in pbar(train_frag[1:]):\n    j+=1\n    data = pd.read_csv(i)\n    data.columns = [['s1_{}'.format(j), 's2_{}'.format(j), 's3_{}'.format(j), 's4_{}'.format(j), 's5_{}'.format(j), 's6_{}'.format(j),\n       's7_{}'.format(j), 's8_{}'.format(j), 's9_{}'.format(j), 's10_{}'.format(j)]]\n    data_tot = pd.concat([data_tot,data],axis=1)\n'''","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"train = train_means.copy()\nsig_tr=[]\nfor i in range(0,len(train_frag)):\n    begin = train_frag[i].find('train/')+6\n    end = train_frag[i].find('.csv', begin)\n    sig_tr = np.append(sig_tr,train_frag[i][begin:end])","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"tomerge = pd.DataFrame({'mean': train , 'segment_id': sig_tr})\ntomerge['segment_id'] = tomerge['segment_id'].astype(int) ","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"train_df = pd.read_csv('../input/predict-volcanic-eruptions-ingv-oe/train.csv')","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"train_df = pd.merge(train_df,tomerge, on = ['segment_id'])","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"y = train_df['time_to_eruption']\nx = train_df['mean']","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn import  linear_model\n\nregr = linear_model.LinearRegression()\nregr.fit(np.array(x).reshape(-1,1), y)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"test_frag = glob.glob(\"../input/predict-volcanic-eruptions-ingv-oe/test/*\")\n\ntest_means=[]\n\npbar = ProgressBar()\nfor i in pbar(test_frag):\n    test_means = np.append(test_means,pd.read_csv(i).mean().max())","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"test = test_means.copy()\nsig_ts=[]\nfor i in range(0,len(test_frag)):\n    begin = test_frag[i].find('test/')+5\n    end = test_frag[i].find('.csv', begin)\n    sig_ts = np.append(sig_ts,test_frag[i][begin:end])","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"sample_submission=pd.read_csv('../input/predict-volcanic-eruptions-ingv-oe/sample_submission.csv')\ntomerge = pd.DataFrame({'mean': test , 'segment_id': sig_ts})\ntomerge['segment_id'] = tomerge['segment_id'].astype(int) \nsubmission = pd.merge(sample_submission,tomerge, on = ['segment_id'])","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"submission['time_to_eruption'] = regr.predict(np.array(submission['mean']).reshape(-1,1))","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"sample_submission = submission.drop(columns = ['mean'])\nsample_submission.to_csv('submission.csv',index=False)","execution_count":null,"outputs":[]}],"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":4,"nbformat_minor":4}