{"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":"markdown","source":"# Simple EDA\n\nIn this Kaggle notebook is presented a simple EDA of the [G-Research Crypto Forecast Competition](https://www.kaggle.com/c/g-research-crypto-forecasting/overview).\n\nAny comments and votes are very welcome! ;)\n","metadata":{}},{"cell_type":"markdown","source":" <a id=\"1\"></a>\n# <p style=\"background-color:#627D78;font-family:newtimeroman;color:#D5CABD;font-size:150%;text-align:center;border-radius:20px 60px;\">How to copy this notebook?</p>\n\nTo copy this notebook to start making your own modifications you just neet to click the button \"Copy & Edit\" that is in the upper right corner of the page. After doing that, you could make any change to it.\n\nEach block of code is named \"cell\". And to run a cel you need to put the cursor on it and hit \"ctrl+Intro\" in the keyboard. \n\n\nThe next cell has some python modules that we will use (module = a bunch of useful functions).  If you need to use those modules, you need to erase the \"#\".\n\nLet first run th","metadata":{}},{"cell_type":"code","source":"import pandas as pd \nimport numpy as np\n\n# import matplotlib.pyplot as plt\n%matplotlib inline","metadata":{"execution":{"iopub.status.busy":"2021-11-29T13:38:53.399186Z","iopub.execute_input":"2021-11-29T13:38:53.399601Z","iopub.status.idle":"2021-11-29T13:38:53.426608Z","shell.execute_reply.started":"2021-11-29T13:38:53.399491Z","shell.execute_reply":"2021-11-29T13:38:53.426013Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":" <a id=\"1\"></a>\n# <p style=\"background-color:#627D78;font-family:newtimeroman;color:#D5CABD;font-size:150%;text-align:center;border-radius:20px 60px;\">Reading Data </p>\n\nWe will only work with the \"train.csv\" data. So the next cell reads the data and save it under the name \"train\". One could read in the same way the other files; to do that one just needs to eliminate the character \"#\" of the beggining of the line and run again the cel.\n\nThis could take like 30 seconds to run.","metadata":{}},{"cell_type":"code","source":"train = pd.read_csv('../input/g-research-crypto-forecasting/train.csv') \n# test = pd.read_csv('../input/g-research-crypto-forecasting/example_test.csv') \n# sub = pd.read_csv('../input/g-research-crypto-forecasting/example_sample_submission.csv') \n# asset_details = pd.read_csv('../input/g-research-crypto-forecasting/asset_details.csv')  ","metadata":{"execution":{"iopub.status.busy":"2021-11-29T13:39:48.936615Z","iopub.execute_input":"2021-11-29T13:39:48.9369Z","iopub.status.idle":"2021-11-29T13:40:46.530306Z","shell.execute_reply.started":"2021-11-29T13:39:48.936872Z","shell.execute_reply":"2021-11-29T13:40:46.529656Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"<a id=\"1\"></a>\n# <p style=\"background-color:#627D78;font-family:newtimeroman;color:#D5CABD;font-size:150%;text-align:center;border-radius:20px 60px;\">Data Exploration</p>\n\nThe simples data exploration that we could perform is to print the first 10 lines of the \"train\" data.","metadata":{}},{"cell_type":"code","source":"train.head(10)","metadata":{"execution":{"iopub.status.busy":"2021-11-29T13:40:46.531816Z","iopub.execute_input":"2021-11-29T13:40:46.532606Z","iopub.status.idle":"2021-11-29T13:40:46.564427Z","shell.execute_reply.started":"2021-11-29T13:40:46.532562Z","shell.execute_reply":"2021-11-29T13:40:46.563604Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"In the next cells we explore other characteristics of the data","metadata":{}},{"cell_type":"code","source":"# The type of each colum\ntrain.info()","metadata":{"execution":{"iopub.status.busy":"2021-11-29T13:47:00.197567Z","iopub.execute_input":"2021-11-29T13:47:00.198269Z","iopub.status.idle":"2021-11-29T13:47:00.221215Z","shell.execute_reply.started":"2021-11-29T13:47:00.198232Z","shell.execute_reply":"2021-11-29T13:47:00.220621Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"# The dimension of the data (number of rows and colums)\ntrain.shape","metadata":{"execution":{"iopub.status.busy":"2021-11-10T05:41:41.334877Z","iopub.status.idle":"2021-11-10T05:41:41.335205Z","shell.execute_reply.started":"2021-11-10T05:41:41.335031Z","shell.execute_reply":"2021-11-10T05:41:41.335047Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"# Number fo NA values (NA = Not Answer mining that is a missing value )\ntrain.isna().sum()","metadata":{"execution":{"iopub.status.busy":"2021-11-29T13:50:38.942334Z","iopub.execute_input":"2021-11-29T13:50:38.943803Z","iopub.status.idle":"2021-11-29T13:50:40.055915Z","shell.execute_reply.started":"2021-11-29T13:50:38.943722Z","shell.execute_reply":"2021-11-29T13:50:40.054988Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"# Basic statistics \ntrain.describe()","metadata":{"execution":{"iopub.status.busy":"2021-11-29T13:52:08.608704Z","iopub.execute_input":"2021-11-29T13:52:08.609475Z","iopub.status.idle":"2021-11-29T13:52:17.115924Z","shell.execute_reply.started":"2021-11-29T13:52:08.609426Z","shell.execute_reply":"2021-11-29T13:52:17.114913Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"This notebook is still in progres, so any comment is more than welcome.\n\nThe same goes for up-votes (to up-vote a notebook you need to click the button with the triangle that appears in the upper left of the original notebook next to the \"Copy & Edit\" button). \n\nBest regards,\nA","metadata":{}}]}