{"cells":[{"metadata":{},"cell_type":"markdown","source":"Valentine’s Day occurs every February 14. Across the United States and in other places around the world, candy, flowers and gifts are exchanged between loved ones, all in the name of St. Valentine. But who is this mysterious saint and where did these traditions come from? Find out about the history of Valentine’s Day, from the ancient Roman ritual of Lupercalia that welcomed spring to the card-giving customs of Victorian England.\n\nThe Catholic Church recognizes at least three different saints named Valentine or Valentinus, all of whom were martyred. One legend contends that Valentine was a priest who served during the third century in Rome. When Emperor Claudius II decided that single men made better soldiers than those with wives and families, he outlawed marriage for young men. Valentine, realizing the injustice of the decree, defied Claudius and continued to perform marriages for young lovers in secret. When Valentine’s actions were discovered, Claudius ordered that he be put to death. Still others insist that it was Saint Valentine of Terni, a bishop, who was the true namesake of the holiday. He, too, was beheaded by Claudius II outside Rome.\nhttps://www.history.com/topics/valentines-day/history-of-valentines-day-2"},{"metadata":{"_kg_hide-input":true,"trusted":true},"cell_type":"code","source":"#codes from Rodrigo Lima  @rodrigolima82\nfrom IPython.display import Image\nImage(url = 'https://encrypted-tbn0.gstatic.com/images?q=tbn%3AANd9GcQirxiYssgJwAlgp0uAl_6SST0o8z9LEbZJE5Be73n2oKLGvhHE',width=400,height=400)","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"freepik.com"},{"metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true,"_kg_hide-output":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)\nimport matplotlib.pyplot as plt\nimport seaborn as sns\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\nfor dirname, _, filenames in os.walk('/kaggle/input'):\n    for filename in filenames:\n        print(os.path.join(dirname, filename))\n\n# Any results you write to the current directory are saved as output.","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"<iframe width=\"640\" height=\"360\" src=\"https://www.youtube.com/embed/WtYdcZmpRyM\" frameborder=\"0\" allow=\"accelerometer; autoplay; encrypted-media; gyroscope; picture-in-picture\" allowfullscreen></iframe>"},{"metadata":{},"cell_type":"markdown","source":"#Strictly Ballroom: Love Is In The Air..."},{"metadata":{"trusted":true,"_kg_hide-input":true},"cell_type":"code","source":"#codes from Rodrigo Lima  @rodrigolima82\nfrom IPython.display import Image\nImage(url = 'data:image/jpeg;base64,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',width=400,height=400)","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"goodhousekeeping.com"},{"metadata":{"_uuid":"d629ff2d2480ee46fbb7e2d37f6b5fab8052498a","_cell_guid":"79c7e3d0-c299-4dcb-8224-4455121ee9b0","trusted":true},"cell_type":"code","source":"valentine = pd.read_csv('/kaggle/input/flower-classification-with-tpus/sample_submission.csv')","execution_count":null,"outputs":[]},{"metadata":{"trusted":true,"_kg_hide-input":true},"cell_type":"code","source":"#codes from Rodrigo Lima  @rodrigolima82\nfrom IPython.display import Image\nImage(url = 'https://encrypted-tbn0.gstatic.com/images?q=tbn%3AANd9GcTSolJIceBIeIS42xiPe6Po-rw1XO1u8w2rWp3aAfQBnUPxjnt2',width=400,height=400)","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"peoplesflowers.com"},{"metadata":{"trusted":true},"cell_type":"code","source":"valentine.head()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true,"_kg_hide-input":true},"cell_type":"code","source":"#codes from Rodrigo Lima  @rodrigolima82\nfrom IPython.display import Image\nImage(url = 'https://encrypted-tbn0.gstatic.com/images?q=tbn%3AANd9GcQx7RS6gA3Wl1jaE7VjLbZX4dgiDCYaIh42oSldu8Ja0sLdn41_',width=400,height=400)","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"fransflowers.ca"},{"metadata":{"trusted":true},"cell_type":"code","source":"valentine.dtypes","execution_count":null,"outputs":[]},{"metadata":{"_kg_hide-input":true,"trusted":true},"cell_type":"code","source":"#codes from Rodrigo Lima  @rodrigolima82\nfrom IPython.display import Image\nImage(url = 'https://encrypted-tbn0.gstatic.com/images?q=tbn%3AANd9GcRfslCHYiwhKUjlnv-Cb641VitqGpXMbMVS_kyF7ff_xMPF0Zef',width=400,height=400)","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"mymodernmet.comm"},{"metadata":{"trusted":true},"cell_type":"code","source":"sns.distplot(valentine[\"label\"].apply(lambda x: x**4))\nplt.show()","execution_count":null,"outputs":[]},{"metadata":{"_kg_hide-input":true,"trusted":true},"cell_type":"code","source":"#codes from Rodrigo Lima  @rodrigolima82\nfrom IPython.display import Image\nImage(url = 'https://encrypted-tbn0.gstatic.com/images?q=tbn%3AANd9GcQIeKxpjPeCtvBoU7BD3oxt0ZdwtmynAqlpR15w2bHTA2oyJhZU',width=400,height=400)","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"pexels.com"},{"metadata":{"_kg_hide-input":true,"trusted":true},"cell_type":"code","source":"#codes from Rodrigo Lima  @rodrigolima82\nfrom IPython.display import Image\nImage(url = 'https://encrypted-tbn0.gstatic.com/images?q=tbn%3AANd9GcS3GcDREFYjch6dPzqzIWxYnTLoaqg5AbKAyGqu3nOUpnY4Ao31',width=400,height=400)","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"conservativememes.com"},{"metadata":{"_kg_hide-input":true,"trusted":true},"cell_type":"code","source":"#codes from Rodrigo Lima  @rodrigolima82\nfrom IPython.display import Image\nImage(url = 'https://encrypted-tbn0.gstatic.com/images?q=tbn%3AANd9GcRzQ_MNufbpbvng9zJSLxnYHC0u25hp3l3JMI8tf4eIAa_wH22b',width=400,height=400)","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"quoteshumor.com"},{"metadata":{"trusted":true},"cell_type":"code","source":"submission = pd.read_csv('/kaggle/input/flower-classification-with-tpus/sample_submission.csv', delimiter=',')\nsubmission.to_csv('submission.csv', index = False)","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"Kaggle Notebook Runner: Marília Prata @mpwolke"}],"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}