{"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":"import pandas as pd # data processing, CSV file I/O\nimport numpy as np\nimport base64\nfrom numpy.random import default_rng\nimport random\n\nrng= np.random.default_rng\n#defines the random number generator utilized to index values \n\nCusTrans = pd.read_csv(\"../input/h-and-m-personalized-fashion-recommendations/transactions_train.csv\")\nCusAge = pd.read_csv('../input/ages-20-25-30-35/Ages x5.csv')# Ages 20,25,30,35\narticle= pd.read_csv(\"../input/articles/clean Article.csv\")\n\nra = pd.merge(CusTrans,CusAge, on=['customer_id'], how='inner')\nres = pd.merge(ra,article, on=['article_id'], how='inner')\n\nlength_of_dataset= len(res)\n\nlist_index_vals=[]\n\nx_count=0\n\nfor i in range(len(res)):\n    list_index_vals.append(x_count)\n    x_count=x_count+1\n    \nprint(length_of_dataset)\n\nres.insert(loc=1,\n          column= \"Random Index Number\",\n          value=random.sample(list_index_vals,len(res))          \n          )\n\nprint(res)\n\nres.to_csv(\"new.csv\", index=False)","metadata":{"execution":{"iopub.status.busy":"2022-03-20T16:45:22.945537Z","iopub.execute_input":"2022-03-20T16:45:22.946927Z","iopub.status.idle":"2022-03-20T16:46:44.493488Z","shell.execute_reply.started":"2022-03-20T16:45:22.946813Z","shell.execute_reply":"2022-03-20T16:46:44.492459Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"","metadata":{},"execution_count":null,"outputs":[]}]}