{"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":"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\n\nimport numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\nimport matplotlib.pyplot as plt\nimport seaborn as sns\nfrom tqdm.notebook import tqdm\n\n\n# Input data files are available in the read-only \"../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\n# for dirname, _, filenames in os.walk('/kaggle/input'):\n#     print(filenames)\n#     for filename in filenames:\n#         print(os.path.join(dirname, filename))\n\n# You can write up to 20GB to the current directory (/kaggle/working/) that gets preserved as output when you create a version using \"Save & Run All\" \n# You can also write temporary files to /kaggle/temp/, but they won't be saved outside of the current session","metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","execution":{"iopub.status.busy":"2023-02-25T13:25:48.436471Z","iopub.execute_input":"2023-02-25T13:25:48.437154Z","iopub.status.idle":"2023-02-25T13:25:49.164311Z","shell.execute_reply.started":"2023-02-25T13:25:48.437074Z","shell.execute_reply":"2023-02-25T13:25:49.163085Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"BASE_DIR = '../input/asl-signs/'\ntrain = pd.read_csv(f'{BASE_DIR}/train.csv')\nprint(\" train  {}\".format(train))","metadata":{"execution":{"iopub.status.busy":"2023-02-25T13:25:49.230280Z","iopub.execute_input":"2023-02-25T13:25:49.231339Z","iopub.status.idle":"2023-02-25T13:25:49.482472Z","shell.execute_reply.started":"2023-02-25T13:25:49.231293Z","shell.execute_reply":"2023-02-25T13:25:49.481100Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train.head()","metadata":{"execution":{"iopub.status.busy":"2023-02-25T13:25:50.074601Z","iopub.execute_input":"2023-02-25T13:25:50.074996Z","iopub.status.idle":"2023-02-25T13:25:50.098588Z","shell.execute_reply.started":"2023-02-25T13:25:50.074962Z","shell.execute_reply":"2023-02-25T13:25:50.097023Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train['sign'].value_counts().head(30).sort_values(ascending=False).plot.bar()","metadata":{"execution":{"iopub.status.busy":"2023-02-25T13:29:34.763826Z","iopub.execute_input":"2023-02-25T13:29:34.764238Z","iopub.status.idle":"2023-02-25T13:29:35.207850Z","shell.execute_reply.started":"2023-02-25T13:29:34.764202Z","shell.execute_reply":"2023-02-25T13:29:35.206875Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"","metadata":{},"execution_count":null,"outputs":[]}]}