{"cells":[{"metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true},"cell_type":"code","source":"# This Python 3 environment comes with many helpful analytics libraries installed\n# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python\n# For example, here's several helpful packages to load in \n\nimport numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n\n# Input data files are available in the \"../input/\" directory.\n# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n\nimport os\nimport librosa\ndirectory = '/kaggle/input/freesound-audio-tagging/audio_train/'\ntime_series = []\nsampling_rate = []\ntempos = []\nall_beat_frames = []\nall_beat_times = []\n\nfor dirname, _, filenames in os.walk(directory):\n    print(len(filenames))\n    print(len(dirname))\n\n\n    for filename in filenames:\n        print(len(filenames))\n\n        y, sr = librosa.load(directory + filename)\n        tempo, beat_frames = librosa.beat.beat_track(y=y, sr=sr)\n        \n        # SHANE IS GAY\n        #print('Estimated tempo: {:.2f} beats per minute'.format(tempo))\n        beat_times = librosa.frames_to_time(beat_frames, sr=sr)\n        time_series.append(y)\n        sampling_rate.append(sr)\n        tempos.append(tempo)\n        all_beat_frames.append(beat_frames)\n        all_beat_times.append(beat_times)\n# Any results you write to the current directory are saved as output.\n\ndf = pd.DataFrame([time_series,sampling_rate,tempos,all_beat_frames,all_beat_times],columns=['time_series', 'sampling_rate', 'tempo','beat_frames','beat_times'])\n\n","execution_count":null,"outputs":[]},{"metadata":{"_uuid":"d629ff2d2480ee46fbb7e2d37f6b5fab8052498a","_cell_guid":"79c7e3d0-c299-4dcb-8224-4455121ee9b0","trusted":true},"cell_type":"code","source":"print('Ayyyyyyy CORONA')","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"","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":1}