{"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 \nimport numpy as np \nimport matplotlib.pyplot as plt \n%matplotlib inline\nimport seaborn as sns","metadata":{"execution":{"iopub.status.busy":"2023-08-18T17:34:12.145100Z","iopub.execute_input":"2023-08-18T17:34:12.145500Z","iopub.status.idle":"2023-08-18T17:34:12.152613Z","shell.execute_reply.started":"2023-08-18T17:34:12.145469Z","shell.execute_reply":"2023-08-18T17:34:12.151555Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"df = pd.read_csv('/kaggle/input/titanic-extended/train.csv')\ndf.head()","metadata":{"execution":{"iopub.status.busy":"2023-08-18T17:34:12.158714Z","iopub.execute_input":"2023-08-18T17:34:12.159121Z","iopub.status.idle":"2023-08-18T17:34:12.202449Z","shell.execute_reply.started":"2023-08-18T17:34:12.159090Z","shell.execute_reply":"2023-08-18T17:34:12.201518Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"df.shape\ndf.isnull().sum()","metadata":{"execution":{"iopub.status.busy":"2023-08-18T17:34:12.204102Z","iopub.execute_input":"2023-08-18T17:34:12.204611Z","iopub.status.idle":"2023-08-18T17:34:12.217236Z","shell.execute_reply.started":"2023-08-18T17:34:12.204581Z","shell.execute_reply":"2023-08-18T17:34:12.215956Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"sns.countplot(x ='SibSp', data=df);","metadata":{"execution":{"iopub.status.busy":"2023-08-18T17:39:32.424876Z","iopub.execute_input":"2023-08-18T17:39:32.425413Z","iopub.status.idle":"2023-08-18T17:39:32.793259Z","shell.execute_reply.started":"2023-08-18T17:39:32.425375Z","shell.execute_reply":"2023-08-18T17:39:32.792060Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"","metadata":{},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"**next cell explanation**\nThe resulting heatmap visually represents the correlation between different numeric variables in the DataFrame. Correlation values close to 1 indicate a strong positive correlation, values close to -1 indicate a strong negative correlation, and values close to 0 indicate little to no correlation between the variables.","metadata":{}},{"cell_type":"code","source":"plt.figure(figsize=(9,7))\nsns.heatmap(df.corr(), annot=True, square=True, fmt='.1f', cbar=False);","metadata":{"execution":{"iopub.status.busy":"2023-08-18T17:40:53.538379Z","iopub.execute_input":"2023-08-18T17:40:53.538853Z","iopub.status.idle":"2023-08-18T17:40:54.288161Z","shell.execute_reply.started":"2023-08-18T17:40:53.538818Z","shell.execute_reply":"2023-08-18T17:40:54.287221Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"!pip install autoviz","metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","execution":{"iopub.status.busy":"2023-08-18T17:19:23.097854Z","iopub.execute_input":"2023-08-18T17:19:23.098651Z","iopub.status.idle":"2023-08-18T17:20:01.662418Z","shell.execute_reply.started":"2023-08-18T17:19:23.098613Z","shell.execute_reply":"2023-08-18T17:20:01.661175Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"from autoviz.AutoViz_Class import AutoViz_Class\n\n","metadata":{"execution":{"iopub.status.busy":"2023-08-18T17:20:01.664428Z","iopub.execute_input":"2023-08-18T17:20:01.664792Z","iopub.status.idle":"2023-08-18T17:20:07.505626Z","shell.execute_reply.started":"2023-08-18T17:20:01.664761Z","shell.execute_reply":"2023-08-18T17:20:07.504557Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"AV = AutoViz_Class()","metadata":{"execution":{"iopub.status.busy":"2023-08-18T17:20:07.506897Z","iopub.execute_input":"2023-08-18T17:20:07.507874Z","iopub.status.idle":"2023-08-18T17:20:07.513666Z","shell.execute_reply.started":"2023-08-18T17:20:07.507839Z","shell.execute_reply":"2023-08-18T17:20:07.512714Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"","metadata":{"trusted":true},"execution_count":null,"outputs":[]}]}