| Name | Version | Summary | date |
| dataglass |
0.8.1 |
dataglass is a Python library for data preprocessing, exploratory data analysis (EDA), and machine learning. It includes modules for handling missing values, detecting and resolving duplicates, managing outliers, feature encoding, type conversion, scaling, and pipeline integration. With its latest update, dataglass introduces intelligent automation which dynamically adapting preprocessing steps based on dataset characteristics, minimizing manual configuration and accelerating your workflow. |
2025-09-07 07:54:05 |
| robustpreprocessor |
1.0.0 |
RobustPreprocessor is designed to preprocess datasets effectively to ensure robust data preparation before further analysis or modeling. |
2024-11-22 09:57:57 |
| Missing-Value |
0.2.5 |
Python class for imputing missing values in data columns using various imputation strategies based on data types. |
2024-03-18 17:46:01 |
| Linear-Correlation |
0.2.5 |
Linear Correlation Analysis and Data Preprocessing Tools |
2024-03-18 17:16:00 |
| Encoding-One-Hot |
0.1.11 |
One hot encoding Categorical to Numerical |
2024-03-18 14:54:26 |
| adaptivebridge |
1.1.0 |
Revolutionizing ML adaptive modelling for handling missing features and data. The model can predict missing data in real-world scenarios. |
2024-01-29 13:21:58 |
| buildml |
1.0.9 |
Let's make building machine learning models the complex way, easy. |
2024-01-27 08:06:46 |
| mlwizard |
1.0.1 |
Let's make building machine learning models the complex way, easy. |
2024-01-08 03:22:36 |
| pydataanalysis |
0.0.4 |
Data Analysis and Visualization Functions |
2023-04-13 09:25:54 |
| PyChrom |
0.0.6 |
Module to provide tools to process and analyse chromatographic data from different sources such as UPLC, LCMS, GCMS, etc. |
2023-04-03 18:05:02 |
| pydatascience |
0.0.3 |
Data Science Functions |
2023-03-22 07:36:22 |