Simple tool for data transformation
Project description
data-steps
This projects provides a minmal framework to organize data transformations in pandas.
It is intended to be used in both notebooks and code files.
The main idea is to provide a simple decorator syntax that is easy to maintains when data transfromation steps get changed or added throughout the project. A prime example is data cleaning where only later in the project some required cleaning steps become apparent
Usage
Wrap your data in an instance
from data_steps import DataSteps
my_data = DataSteps(my_pandas_df)
#register transformation steps
@my_data.step()
def data_transformation(data):
#transfromation steps
...
return transformed data
#access original data
my_data.original
#access data after all transformation steps
my_data.transformed
#get an overview of the registered steps
my_data.steps
#only execute some steps to help debugging transformations
my_data.partial_transform(0)
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
data-steps-0.0.1.tar.gz
(3.2 kB
view details)
File details
Details for the file data-steps-0.0.1.tar.gz
.
File metadata
- Download URL: data-steps-0.0.1.tar.gz
- Upload date:
- Size: 3.2 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.3.0 pkginfo/1.7.0 requests/2.25.1 setuptools/52.0.0 requests-toolbelt/0.9.1 tqdm/4.56.0 CPython/3.9.1
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 0534dc4660578caa1ff5fc3959c3d70bbc2f905b972fa07424598e440fd51dea |
|
MD5 | 31d54ae8b2892efc5f5de183b401955b |
|
BLAKE2b-256 | 984ba1603f401015db5c50752d9e80608c75297db1148aab8a45b08e6a6b0c12 |