Python package for amplifying operations on main Python data structures.
Project description
py_exp_calc
Python package for amplifying operations on main Python data structures.
First, this package can enhance operations on various data structures such as lists, numpy arrays, and dictionaries. It allows not only an increase in the available operations within these data structures but also conversion between them. Some of the main operations are:
Lists: Flattening, ensuring unique elements (uniq), adding tags to list elements and performing set operations such as intersection, union, and difference between lists.
Dictionaries: Enhanced operations for nested dictionaries, such as the dig method from Ruby, addition and removal of key-value pairs and expanding dictionaries by adding values in list format.
Numpy arrays: Matrix normalization and filtering.
Secondly, advanced data analysis operations have been added to the toolkit, including statistical analysis and clustering. To facilitate these operations, two command-line interfaces (CLIs) have been designed:
clusterize: Applies hierarchical clustering to a given matrix.
inference_analyzer: Executes inference analysis on a set of n observations divided into m categories.
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
File details
Details for the file py_exp_calc-1.1.0.tar.gz
.
File metadata
- Download URL: py_exp_calc-1.1.0.tar.gz
- Upload date:
- Size: 39.5 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.1 CPython/3.10.8
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 8b8614596457d7e3380c4904b29a7003966e24dbe80e1cf99cb6e669f709834a |
|
MD5 | 5adab1ba922f9c0159b8d2eafc9101d6 |
|
BLAKE2b-256 | f22f295d41cc4459ce7770f67ab81000d6ffe458298cac7d5b6295bc0cd0b2ed |
File details
Details for the file py_exp_calc-1.1.0-py3-none-any.whl
.
File metadata
- Download URL: py_exp_calc-1.1.0-py3-none-any.whl
- Upload date:
- Size: 17.9 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.1 CPython/3.10.8
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | b59d84b5aedcfbd2e9d5beb0cefde8c92a50666ff1f9dfe978ab14e12da0e0e2 |
|
MD5 | 5943ed90d32edf9a45fec62a68a90091 |
|
BLAKE2b-256 | 0702a8449c7b3d64a51c13ab4397a99984df443ff1ace859eb36d31b8de4cda7 |