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KLIB KETOPT SOFTWARE
"text": "TiddlyWiki created by Jeremy Ruston, (jeremy jermolene com)\n\nCopyright © Jeremy Ruston 2004-2007\nCopyright © UnaMesa Association 2007-2016\n\nRedistribution and use in source and binary forms, with or without modification,\nare permitted provided that the following conditions are met:\n\nRedistributions of source code must retain the above copyright notice, this\nlist of conditions and the following disclaimer.\n\nRedistributions in binary form must reproduce the above copyright notice, this\nlist of conditions and the following disclaimer in the documentation and/or other\nmaterials provided with the distribution.\n\nNeither the name of the UnaMesa Association nor the names of its contributors may be\nused to endorse or promote products derived from this software without specific\nprior written permission.\n\nTHIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS 'AS IS' AND ANY\nEXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES\nOF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. "text": "TiddlyWiki incorporates code from these fine OpenSource projects:\n\n* ]\n* ]\n* ]\n\nAnd media from these projects:\n\n* World flag icons from ]\n" If you find that data exploration takes a lot of time, you can use this library as it gives you all the functions that will help you to explore, clean and prepare your data. Ksort: sorting, shuffling, heap and k-small Klib is a Python library that provides amazing functionality for exploring your data in just a few lines of code.Kexpr: parsing mathematical expressions.$:/themes/tiddlywiki/vanilla/options/sidebarlayout.$:/plugins/tiddlywiki/highlight/license.$:/plugins/tiddlywiki/highlight/highlightblock.js.$:/plugins/tiddlywiki/highlight/highlight.js.$:/plugins/tiddlywiki/highlight/highlight.css.$:/config/PageControlButtons/Visibility/$:/core/ui/Buttons/permaview.$:/config/PageControlButtons/Visibility/$:/core/ui/Buttons/home.$:/config/PageControlButtons/Visibility/$:/core/ui/Buttons/control-panel.This TiddlyWiki contains the following tiddlers:
![klib ketopt klib ketopt](https://www.kaisbaking.com/wp-content/uploads/2020/11/Keto_Cheesecake_Brownies-768x512.jpg)
ColumnSelector () # selects num or cat columns, ideal for a Feature Union or Pipeline - klib. cat_pipe () # provides common operations for preprocessing of categorical data - klib.
![klib ketopt klib ketopt](http://voyagemia.com/wp-content/uploads/2020/06/AF594295-D5B9-4A76-AFE5-4F507DE07151.jpeg)
num_pipe () # provides common operations for preprocessing of numerical data - klib. feature_selection_pipe () # provides common operations for feature selection - klib. train_dev_test_split ( df ) # splits a dataset and a label into train, optionally dev and test sets - klib. loss of information # klib.preprocess - functions for data preprocessing (feature selection, scaling. pool_duplicate_subsets ( df ) # pools subset of cols based on duplicates with min.
![klib ketopt klib ketopt](https://images2.patro.cz/original/000/003/469/000003469557_0.jpg)
mv_col_handling ( df ) # drops features with high ratio of missing vals based on informational content - klib. drop_missing ( df ) # drops missing values, also called in data_cleaning() - klib. convert_datatypes ( df ) # converts existing to more efficient dtypes, also called inside data_cleaning() - klib. clean_column_names ( df ) # cleans and standardizes column names, also called inside data_cleaning() - klib. data_cleaning ( df ) # performs datacleaning (drop duplicates & empty rows/cols, adjust dtypes.) - klib. missingval_plot ( df ) # returns a figure containing information about missing values # klib.clean - functions for cleaning datasets - klib. dist_plot ( df ) # returns a distribution plot for every numeric feature - klib.
![klib ketopt klib ketopt](https://i.pinimg.com/originals/eb/a6/c7/eba6c7d373c9b6bc38e5f52b6919d120.jpg)
corr_plot ( df ) # returns a color-encoded heatmap, ideal for correlations - klib. corr_mat ( df ) # returns a color-encoded correlation matrix - klib. cat_plot ( df ) # returns a visualization of the number and frequency of categorical features - klib. DataFrame ( data ) # scribe - functions for visualizing datasets - klib.