Dataprep: Data Preparation in Python
Dataprep lets you prepare your data using a single library with a few lines of code.
Currently, you can use
- Collect data from common data sources (through
- Do your exploratory data analysis (through
- ...more modules are coming
pip install -U dataprep
Examples & Usages
The following examples can give you an impression of what dataprep can do:
There are common tasks during the exploratory data analysis stage, like a quick look at the columnar distribution, or understanding the correlations between columns.
The EDA module categorizes these EDA tasks into functions helping you finish EDA tasks with a single function call.
- Want to understand the distributions for each DataFrame column? Use
- Want to understand the correlation between columns? Use
- Or, if you want to understand the impact of the missing values for each column, use
You can drill down to get more information by given
plot_missing a column name.: E.g. for
for numerical column using
for categorical column using
Don't forget to checkout the examples folder for detailed demonstration!
Connector provides a simple way to collect data from different websites, offering several benefits:
- A unified API: you can fetch data using one or two lines of code to get data from many websites.
- Auto Pagination: it automatically does the pagination for you so that you can specify the desired count of the returned results without even considering the count-per-request restriction from the API.
- Smart API request strategy: it can issue API requests in parallel while respecting the rate limit policy.
In the following examples, you can download the Yelp business search result into a pandas DataFrame, using only two lines of code, without taking deep looking into the Yelp documentation! More examples can be found here: Examples
There are many ways to contribute to Dataprep.
- Submit bugs and help us verify fixes as they are checked in.
- Review the source code changes.
- Engage with other Dataprep users and developers on StackOverflow.
- Help each other in the Dataprep Community Discord and Mail list & Forum.
- Contribute bug fixes.
- Providing use cases and writing down your user experience.
Please take a look at our wiki for development documentations!
Some functionalities of DataPrep are inspired by the following packages.
Release history Release notifications | RSS feed
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
|Filename, size||File type||Python version||Upload date||Hashes|
|Filename, size dataprep-0.2.14-py3-none-any.whl (155.0 kB)||File type Wheel||Python version py3||Upload date||Hashes View|
|Filename, size dataprep-0.2.14.tar.gz (121.8 kB)||File type Source||Python version None||Upload date||Hashes View|
Hashes for dataprep-0.2.14-py3-none-any.whl