DAQUA

Daqua is a data quality measurement tool. We can connect to any data source which contains tabular data to perform data profiling and various indicator for data quality for data cleaning.

Getting Started

To use daqua, you need to install it by using pip.

pip install daqua

Prerequisites

You need to have numpy and pandas installed in your system for using daqua.

Getting started

# importing the package
import daqua

# Creating an object of the Daqua class
dq = daqua.Daqua()

# reading an excel file
dq.read_excel(path_to_excel)

# get the dataframe dictionary
## The structure is like {"sheet_name" : df}

dict_dfs = dq.getDataFrames()

# get meta data about the dataframe
meta = dq.getMetaData()


# get detailed metadata
detailed_meta = dq.getDetailedMeta()

# get the descriptive stat for numeric columns
descriptive_stat_dict = dq.getNumericDesc()

# get quantile stats
quant_dict = dq.getQuantileStat()

Deployment

link to pypi: https://pypi.org/project/daqua/

Contributing

Please read [CONTRIBUTING.md](link to contri page) for details on our code of conduct, and the process for submitting pull requests to us.

Authors

Satya Pati - Initial work - Github
Lalit Moharana - Initial work - Github
Soumya Ranjan Bisoi - Initial work - Github

See also the list of contributors who participated in this project.

License

This project is licensed under the MIT License - see the LICENSE.md file for details

lalit2001 / Daqua