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The easiest way to prepare data in Python
- from dataprep.datasets import load_dataset
- from dataprep.eda import create_report
- df = load_dataset("titanic")
- create_report(df).show()
- from dataprep.connector import connect
- dc = connect("twitter", _auth={"client_id":client_id, "client_secret":client_secret})
- df = await dc.query("twitter", q="covid-19", _count=1000)
- from dataprep.datasets import load_dataset
- from dataprep.clean import clean_address
- df = load_dataset("waste_hauler")
- clean_address(df, "LOCAL ADDRESS")
Think different.
"We were disappointed, if not surprised, to see that data wrangling still takes the lion’s share of time in a typical data professional’s day. Data preparation and cleansing takes valuable time away from real data science work and has a negative impact on overall job satisfaction."
2020 State of Data Science: Moving From Hype Toward Maturity, Anaconda
Designed for Notebook Users
DataPrep is designed for computational notebooks, the most popular environment among data scientists.
Integrate Seamlessly with the Python Ecosystem
DataPrep is built using Pandas/Dask DataFrame and can be seamlessly integrated with other Python libraries.
Embrace Open Source
DataPrep is free, open-source software released under the MIT license. Anyone can reuse DataPrep code for any purpose.
DataPrep.EDA
DataPrep.EDA is the fastest and the easiest EDA tool in Python. It allows data scientists to understand a Pandas/Dask DataFrame with a few lines of code in seconds.