datasetops-toolkit 0.1.2

A Python toolkit for simplifying dataset preparation and preprocessing

datasetops

A Python toolkit for simplifying dataset preparation and preprocessing.

Installation

pip install datasetops-toolkit

Usage

from datasetops import DatasetOps

ds = DatasetOps("data.csv")

ds.summary()
ds.missing_report()
ds.remove_duplicates()
ds.normalize()
ds.encode_categorical()
ds.save_csv("clean_data.csv")

Features

• Loading: load_csv, load_excel, load_json, reload_dataset
• Inspection: summary, head, tail, shape, column_names, column_types, describe_stats
• Missing Values: missing_report, missing_percentage, fill_missing_mean, fill_missing_median, fill_missing_mode, fill_missing_value, drop_missing_rows, drop_missing_columns
• Duplicates: duplicate_report, count_duplicates, remove_duplicates
• Column Operations: rename_column, drop_column, add_column, select_columns
• Row Operations: filter_rows, sort_rows, sample_rows
• Transformation: normalize, standardize, log_transform, encode_categorical, one_hot_encode
• Analysis: data_quality_report, correlation_matrix, detect_outliers, column_unique_values, value_counts, group_by, aggregate_stats, top_values
• Visualization: plot_histogram, plot_boxplot, plot_scatter, plot_correlation_heatmap
• Export: save_csv, save_excel, export_report