{"cells": [{"source": ["## What are we going to see in this kernel?\n", "* Since the memory of the dataset are too large and need to much time to run them. I try to reduce memory consumption of dataframes\n"], "cell_type": "markdown", "metadata": {"_uuid": "2bad73469a628dfd01c4edbede6b20ab606bf600", "_cell_guid": "d64a2848-8f28-4986-8361-9444fc5ef962"}}, {"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", "\n", "import numpy as np # linear algebra\n", "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n", "import seaborn as sns\n", "from matplotlib import pyplot\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 the files in the input directory\n", "\n", "from subprocess import check_output\n", "print(check_output([\"ls\", \"../input\"]).decode(\"utf8\"))"], "cell_type": "code", "execution_count": null, "outputs": [], "metadata": {"_cell_guid": "ee1f67d8-863c-41d0-aa78-47439243693a", "_kg_hide-output": true, "_uuid": "7bfc4aaa12cde37773c2f9a72d8a641b39548e71", "collapsed": true}}, {"source": ["df_train = pd.read_csv('../input/train.csv')\n", "df_members = pd.read_csv('../input/members.csv')\n", "df_transactions = pd.read_csv('../input/transactions.csv')\n", "#df_sample = pd.read_csv('../input/sample_submission_zero.csv')\n", "#df_user_logs_1 = pd.read_csv('../input/user_logs.csv'), chunksize = 500)\n", "#df = pd.concat(df_user_logs_1, ignore_index=True)\n", "\n", "# Any results you write to the current directory are saved as output."], "cell_type": "code", "execution_count": null, "outputs": [], "metadata": {"_cell_guid": "7ea31b23-c7da-419e-8cc1-d03da881cdde", "_uuid": "cb66ef7e8bce210ae82ce1673dcd553b26381b3a", "collapsed": true}}, {"source": ["# Memory Reduction\n", "\n", "**members.csv**\n"], "cell_type": "markdown", "metadata": {"_uuid": "620ed69fa723d97048a88924a840a34a71ed6f2a", "_cell_guid": "2ff26f5c-1c76-44a5-854e-4189560d42fd"}}, {"source": ["#--- Displays members column memory consumed  ---\n", "print(df_members.memory_usage().sum()/1023**2,\"MB\")"], "cell_type": "code", "execution_count": null, "outputs": [], "metadata": {"_cell_guid": "5ffa041a-83d4-4692-b869-808b9b711d67", "_kg_hide-output": true, "_uuid": "09c6106c5b5804d460baaf094e85c5e9a5dd7172", "collapsed": true}}, {"source": ["#--- List the columns with missing values ----\n", "df_members.isnull().values.any()"], "cell_type": "code", "execution_count": null, "outputs": [], "metadata": {"_cell_guid": "a959999c-29f5-49af-a62e-2baebb9da79e", "_kg_hide-output": true, "_uuid": "86e348c21f3b6fc12e13b197d0d92e0a4e636e43", "collapsed": true}}, {"source": ["df_members.columns[df_members.isnull().any()].tolist()"], "cell_type": "code", "execution_count": null, "outputs": [], "metadata": {"_cell_guid": "c1f61a39-12f8-45bb-b8cc-0bd3861f22fb", "_kg_hide-output": true, "_uuid": "21181d311976cc5e15d63ee09a824365908e84d0", "collapsed": true}}, {"source": ["#--- Check the datatypes of each columns in members.cvs ---\n", "df_members.dtypes"], "cell_type": "code", "execution_count": null, "outputs": [], "metadata": {"_cell_guid": "245158b4-2d9a-45ac-8a3b-7b412569035d", "_kg_hide-output": true, "_uuid": "022ed09bd7a07a3ee41f5c301dc961fb26200be0", "collapsed": true}}, {"source": ["df_members.head()"], "cell_type": "code", "execution_count": null, "outputs": [], "metadata": {"_cell_guid": "fc9ec570-bfa2-4bbb-9460-840aaf3e87e7", "_kg_hide-output": true, "_uuid": "dc411f790033d6b802746c53e52c3c5fb512c427", "collapsed": true}}, {"source": ["#--- members columns name ---#\n", "df_members.columns"], "cell_type": "code", "execution_count": null, "outputs": [], "metadata": {"_cell_guid": "80c1df18-85e3-4a28-9d25-83e00a9ab866", "_kg_hide-output": true, "_uuid": "a9f47ba760e21277cd218437d4a1923d112a570e", "collapsed": true}}, {"source": ["* Since 'registration_init_time' and 'expiration_date' columns are not datetime type. First, we will split them based on *year*, *month*, and *date* in order to convert it to more convinent type for us in the later data analysis."], "cell_type": "markdown", "metadata": {"_uuid": "17b04fee1ed0ea49f374d7f23c4367cfe585a849", "_cell_guid": "aed5e898-cf14-4aac-b8cb-2bdbea62e753"}}, {"source": ["df_members['registration_init_year'] = df_members['registration_init_time'].apply(lambda x: int(str(x)[:4]))\n", "df_members['registration_init_month'] = df_members['registration_init_time'].apply(lambda x: int(str(x)[4:6]))\n", "df_members['registration_init_date'] = df_members['registration_init_time'].apply(lambda x: int(str(x)[-2:]))"], "cell_type": "code", "execution_count": null, "outputs": [], "metadata": {"_cell_guid": "2b5de61b-185f-49f3-be79-e62d034b8122", "_kg_hide-output": true, "_uuid": "a80ff215397b1df828bb1e75ae23f59c6aac1ddc", "collapsed": true}}, {"source": ["df_members['expiration_date_year'] = df_members['expiration_date'].apply(lambda x: int(str(x)[:4]))\n", "df_members['expiration_date_month'] = df_members['expiration_date'].apply(lambda x: int(str(x)[4:6]))\n", "df_members['expiration_date_date'] = df_members['expiration_date'].apply(lambda x: int(str(x)[-2:]))"], "cell_type": "code", "execution_count": null, "outputs": [], "metadata": {"_cell_guid": "fb7920f3-2420-42fa-a167-1d26222e1e6e", "_kg_hide-output": true, "_uuid": "9255da5a52f5b7e2e9bace7d757ebcc935126e56", "collapsed": true}}, {"source": ["#--- Check the change of the df_members after we split two columns. ---#\n", "df_members.head()"], "cell_type": "code", "execution_count": null, "outputs": [], "metadata": {"_cell_guid": "31d7aab1-c971-406f-b87f-f4f7c27a5487", "_kg_hide-output": true, "_uuid": "7d5930a08393162b233a32949bd08193b5432251", "collapsed": true}}, {"source": ["#--- Let check the memory consumption of the df_members now ---#\n", "print(df_members.memory_usage().sum()/1023**2,\"MB\")"], "cell_type": "code", "execution_count": null, "outputs": [], "metadata": {"_cell_guid": "be43296f-5fd8-4d61-a2fa-ed5e4b77425e", "_kg_hide-output": true, "_uuid": "a0049a195a5ecea6a88846cd42334240cecc8d3a", "collapsed": true}}, {"source": ["* Woooo! It become larger than before. No panic, let us reduce the df_members memory consumption from now."], "cell_type": "markdown", "metadata": {"_uuid": "17e53a8541c56dc1e06a83fd763fd78e662d7396", "_cell_guid": "8dbf42fc-83f3-4393-ae8d-2cddb78de444"}}, {"source": ["#--- Now drop no needed date columns ---#\n", "df_members = df_members.drop('registration_init_time', 1)\n", "df_members = df_members.drop('expiration_date', 1)"], "cell_type": "code", "execution_count": null, "outputs": [], "metadata": {"_cell_guid": "9e8461a1-2da3-44b9-adcb-e781660696bd", "_kg_hide-output": true, "_uuid": "8ef9647074c69e0e3e4a0e97c054ce41565a7251", "collapsed": true}}, {"source": ["#--- df_members memory consumption after drop two no needed columns ---#\n", "print(df_members.memory_usage().sum()/1023**2,\"MB\")"], "cell_type": "code", "execution_count": null, "outputs": [], "metadata": {"_cell_guid": "f36e878a-9c2c-4f81-9bb8-a5bf91db0f4d", "_kg_hide-output": true, "_uuid": "6b958fa22fdbc457ef308c3b9505451cffeeac5d", "collapsed": true}}, {"source": ["df_members.columns"], "cell_type": "code", "execution_count": null, "outputs": [], "metadata": {"_cell_guid": "cd966a49-36e8-4952-b616-59eed0c83e1e", "_kg_hide-output": true, "_uuid": "52aa5d790b2de6a9ed6376540489e6866c30a950", "collapsed": true}}, {"source": ["#--- Check the max and min value of each columns wich datatype is int64 by default ---#\n", "df_members.describe().astype(int)"], "cell_type": "code", "execution_count": null, "outputs": [], "metadata": {"_cell_guid": "4f36c3c8-38df-4666-96b5-b67543344890", "_kg_hide-output": true, "_uuid": "b7f8165434b1324cf2a3024211b1d34575e51f7f", "collapsed": true}}, {"source": ["As outputs shows above and the form shows below, I will assign the columns more appropriate datatype.\n", "![image.png](attachment:image.png)"], "cell_type": "markdown", "attachments": {"image.png": {"image/png": 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"}}, "metadata": {"_uuid": "6ec387e24f443c3bd1b6cacd7365c38ab579e67e", "_cell_guid": "da76ce37-56c4-4bd6-bca9-05d6eacbcb9f"}}, {"source": ["df_members['city'] = df_members['city'].astype(np.int8)\n", "df_members['bd'] = df_members['bd'].astype(np.int16)\n", "df_members['registered_via'] = df_members['registered_via'].astype(np.int8)\n", "df_members['registration_init_year'] = df_members['registration_init_year'].astype(np.int16)\n", "df_members['registration_init_month'] = df_members['registration_init_month'].astype(np.int8)\n", "df_members['registration_init_date'] = df_members['registration_init_date'].astype(np.int8)\n", "df_members['expiration_date_year'] = df_members['expiration_date_year'].astype(np.int16)\n", "df_members['expiration_date_month'] = df_members['expiration_date_month'].astype(np.int8)\n", "df_members['expiration_date_date'] = df_members['expiration_date_date'].astype(np.int8)"], "cell_type": "code", "execution_count": null, "outputs": [], "metadata": {"_cell_guid": "18838158-0ecc-49ce-83a9-356aa38dd75a", "_kg_hide-output": true, "_uuid": "b2714a469e76cf5a1cf7731384faae2b6cbfe41d", "collapsed": true}}, {"source": ["#--- df_members memory consumption after change them to appropriate datatype ---#\n", "print(df_members.memory_usage().sum()/1023**2,\"MB\")"], "cell_type": "code", "execution_count": null, "outputs": [], "metadata": {"_cell_guid": "9e156190-c4a7-432d-b4a8-d80b8804f1b6", "_kg_hide-output": true, "_uuid": "e6550dcfedbe28df9efe9357d083ba0f7236c953", "collapsed": true}}, {"source": ["* Done! Chane the df_members memory consumption to 137 MB from 273 MB."], "cell_type": "markdown", "metadata": {"_uuid": "9074c87285e36625545c5bea959bcbc5e0a04232", "_cell_guid": "2a974b9f-4cfd-4264-b1b9-f05bea86160f"}}, {"source": ["**train.csv**"], "cell_type": "markdown", "metadata": {"_uuid": "9b550ce9429bfb22b640f93c1db9cc04958a7c83", "_cell_guid": "d20796d9-1137-499f-90ef-2774ce148313"}}, {"source": ["df_train.head()"], "cell_type": "code", "execution_count": null, "outputs": [], "metadata": {"_cell_guid": "30cd3741-2e81-43d3-8acf-ea1a1606b17b", "_kg_hide-output": true, "_uuid": "a3a7518a0d9c68398d70cb2f1cfa417548aa7480", "collapsed": true}}, {"source": ["df_train.isnull().values.any()"], "cell_type": "code", "execution_count": null, "outputs": [], "metadata": {"_cell_guid": "c7e5f816-6b90-4588-9f10-3fefef27c4b6", "_kg_hide-output": true, "_uuid": "47482a35e07f465c4d920de70c2f6a9a621a0cb7", "collapsed": true}}, {"source": ["df_train.dtypes"], "cell_type": "code", "execution_count": null, "outputs": [], "metadata": {"_cell_guid": "0cec7035-10f8-43cf-9759-62674efd3666", "_kg_hide-output": true, "_uuid": "350e37b771559d38708ef00631504ed65eddeb6a", "collapsed": true}}, {"source": ["print(df_train.memory_usage(index=True).sum()/ 1024**2,\" MB\")"], "cell_type": "code", "execution_count": null, "outputs": [], "metadata": {"_cell_guid": "335dc2ba-9328-4b9a-90f8-81836578055c", "_kg_hide-output": true, "_uuid": "60422460342b66c7a500b5aee2151526ed7e89ed", "collapsed": true}}, {"source": ["df_train['is_churn'] = df_train['is_churn'].astype(np.int8)\n", "print(df_train.memory_usage(index=True).sum()/ 1024**2,\" MB\")"], "cell_type": "code", "execution_count": null, "outputs": [], "metadata": {"_cell_guid": "823881bc-2e08-4628-b82c-0ae74d495911", "_kg_hide-output": true, "_uuid": "a154da494aa883000e30c079436ec2984a88d629", "collapsed": true}}, {"source": ["* The train.csv file has been reduced from 15MB to 8MB.\n", "\n", "* Then **transactions.csv**"], "cell_type": "markdown", "metadata": {"_uuid": "2207b664f5d1f1c7b8fe3e784d4cf49120d0bed3", "_cell_guid": "b55a62e7-5f69-4934-b6ae-9d0216e54edb"}}, {"source": ["df_transactions = pd.read_csv('../input/transactions.csv')"], "cell_type": "code", "execution_count": null, "outputs": [], "metadata": {"_cell_guid": "9ab9bb32-d18f-4e99-b480-8f663f9d19f5", "_uuid": "06148c7359adfb8967d60f0172e98168ebcf07f0", "collapsed": true}}, {"source": ["df_transactions.head()"], "cell_type": "code", "execution_count": null, "outputs": [], "metadata": {"_cell_guid": "15d60293-86ec-4579-befe-a4d4b9d25e90", "_kg_hide-output": false, "_uuid": "217c6a1865d931318d424207d8983b78b7252bf1", "collapsed": true}}, {"source": ["print(df_transactions.memory_usage(index=True).sum()/ 1024**2,\" MB\")"], "cell_type": "code", "execution_count": null, "outputs": [], "metadata": {"_cell_guid": "42e0497c-e30c-4cc8-8fc1-f01f97a736a7", "_kg_hide-output": true, "_uuid": "2e4c2a218b054a2eb5a14abe45cad2308b40e54d", "collapsed": true}}, {"source": ["* df_transactions consuming 1.4GB."], "cell_type": "markdown", "metadata": {"_uuid": "b087f7ee14b53bc672f6cead5822305aff23e132", "_cell_guid": "8c2352ff-8ae8-4ba4-9689-43ec8e8f89f0"}}, {"source": ["df_transactions.isnull().values.any()"], "cell_type": "code", "execution_count": null, "outputs": [], "metadata": {"_cell_guid": "8264499e-8ad1-4689-9ba7-0c1bcf33f4cc", "_kg_hide-output": true, "_uuid": "e5b8440921797db63cf5a50aebb2a43dfb1f2405", "collapsed": true}}, {"source": ["df_transactions.dtypes"], "cell_type": "code", "execution_count": null, "outputs": [], "metadata": {"_cell_guid": "1b647064-25ba-4443-8772-ce29506f2fe2", "_kg_hide-output": true, "_uuid": "83a1f38d8ad14235afdf6901edc537de1935a8d7", "collapsed": true}}, {"source": ["df_transactions['payment_method_id'] = df_transactions['payment_method_id'].astype(np.int8)\n", "df_transactions['payment_plan_days'] = df_transactions['payment_plan_days'].astype(np.int16)\n", "df_transactions['plan_list_price'] = df_transactions['plan_list_price'].astype(np.int16)\n", "df_transactions['actual_amount_paid'] = df_transactions['actual_amount_paid'].astype(np.int16)\n", "df_transactions['is_auto_renew'] = df_transactions['is_auto_renew'].astype(np.int8)\n", "df_transactions['is_cancel'] = df_transactions['is_cancel'].astype(np.int8)"], "cell_type": "code", "execution_count": null, "outputs": [], "metadata": {"_cell_guid": "f34ae68c-db03-452c-ab14-e1cd35e621d3", "_uuid": "388e243b04b337aa8089a025da00d7c7e4c2cfa6", "collapsed": true}}, {"source": ["* Here we have two date columns as well of type integer. We proceed as before."], "cell_type": "markdown", "metadata": {"_uuid": "9b30023648b6ae86b303181c2ed10b8a9b8b1bf6", "_cell_guid": "905ecefd-6279-4bfd-b274-0480566976ab"}}, {"source": ["df_transactions['transaction_date_year'] = df_transactions['transaction_date'].apply(lambda x: int(str(x)[:4]))\n", "df_transactions['transaction_date_month'] = df_transactions['transaction_date'].apply(lambda x: int(str(x)[4:6]))\n", "df_transactions['transaction_date_date'] = df_transactions['transaction_date'].apply(lambda x: int(str(x)[-2:]))\n", "\n", "df_transactions['membership_expire_date_year'] = df_transactions['membership_expire_date'].apply(lambda x: int(str(x)[:4]))\n", "df_transactions['membership_expire_date_month'] = df_transactions['membership_expire_date'].apply(lambda x: int(str(x)[4:6]))\n", "df_transactions['membership_expire_date_date'] = df_transactions['membership_expire_date'].apply(lambda x: int(str(x)[-2:]))"], "cell_type": "code", "execution_count": null, "outputs": [], "metadata": {"_cell_guid": "12f97d5a-a9b6-441e-ac02-3160edf376ee", "_uuid": "4b744e90cc1b31d9b55538e1f6858f49babe1b77", "collapsed": true}}, {"source": ["* Now we assign different datatypes as appropriate to the newly created columns."], "cell_type": "markdown", "metadata": {"_uuid": "030d312ef85d6971d065f8c9ef1baa8c2d098f3b", "_cell_guid": "fb984110-a86c-4731-a792-bd6c8559c706"}}, {"source": ["\n", "df_transactions['transaction_date_year'] = df_transactions['transaction_date_year'].astype(np.int16)\n", "df_transactions['transaction_date_month'] = df_transactions['transaction_date_month'].astype(np.int8)\n", "df_transactions['transaction_date_date'] = df_transactions['transaction_date_date'].astype(np.int8)\n", "\n", "df_transactions['membership_expire_date_year'] = df_transactions['membership_expire_date_year'].astype(np.int16)\n", "df_transactions['membership_expire_date_month'] = df_transactions['membership_expire_date_month'].astype(np.int8)\n", "df_transactions['membership_expire_date_date'] = df_transactions['membership_expire_date_date'].astype(np.int8)\n"], "cell_type": "code", "execution_count": null, "outputs": [], "metadata": {"_cell_guid": "88fe6058-6811-4fd4-aad6-12bc9e202e6e", "_uuid": "149b23ebb64519ddb2842ae94195e59ff97e4123", "collapsed": true}}, {"source": ["#--- Now drop no needed columns ---\n", "df_transactions = df_transactions.drop('transaction_date', 1)\n", "df_transactions = df_transactions.drop('membership_expire_date', 1)"], "cell_type": "code", "execution_count": null, "outputs": [], "metadata": {"_cell_guid": "844df928-7263-4fc5-82f9-1be4846256d8", "_uuid": "9b5ed5afa81c6f6053065925f6ab239a80feea23", "collapsed": true}}, {"source": ["df_transactions.head()"], "cell_type": "code", "execution_count": null, "outputs": [], "metadata": {"_cell_guid": "8bd12d5f-c1a6-40ac-9e35-a37d55c70072", "_uuid": "bb1ca3b0bccc63658148e3e53074424946c96cfb", "collapsed": true}}, {"source": ["print(df_transactions.memory_usage(index=True).sum()/ 1024**2,\" MB\")"], "cell_type": "code", "execution_count": null, "outputs": [], "metadata": {"_cell_guid": "1b0ae6be-f91b-42bd-b6be-da02ec0d19c4", "_kg_hide-output": true, "_uuid": "b016a55951e06098204194bd4ab45d420135e2dc", "collapsed": true}}], "metadata": {"kernelspec": {"language": "python", "name": "python3", "display_name": "Python 3"}, "language_info": {"nbconvert_exporter": "python", "name": "python", "mimetype": "text/x-python", "file_extension": ".py", "codemirror_mode": {"name": "ipython", "version": 3}, "pygments_lexer": "ipython3", "version": "3.6.3"}}, "nbformat_minor": 1, "nbformat": 4}