Rich DataFrame
Create animated and pretty Pandas Dataframe or Pandas Series, as shown below:
Installation
pip install rich-dataframe
Usage
Minimal example
from sklearn.datasets import fetch_openml
from rich_dataframe import prettify
speed_dating = fetch_openml(name='SpeedDating', version=1)['frame']
table = prettify(speed_dating)
If you want to pass a non-dataframe object, rich_dataframe got it covered too!
from rich_dataframe import prettify
var = {'a': 1, 'b': 3}
prettify(var)
Parameters
- df: pd.DataFrame The data you want to prettify
- row_limit : int, optional
Number of rows to show, by default
20 - col_limit : int, optional
Number of columns to show, by default
10 - first_rows : bool, optional
Whether to show first n rows or last n rows, by default
True. If this is set toFalse, show last n rows. - first_cols : bool, optional
Whether to show first n columns or last n columns, by default
True. If this is set toFalse, show last n rows. - delay_time : int, optional
How fast is the animation, by default
5. Increase this to have slower animation. - clear_console: bool, optional Clear the console before printing the table, by default True. If this is set to false the previous console input/output is maintained
Metadata
Release files for rich-dataframe 0.2.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| rich-dataframe-0.2.0.tar.gz | 7.9 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| rich_dataframe-0.2.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 16.0 kB
Release files / rich-dataframe-0.2.0.tar.gz
| Download URL | rich-dataframe-0.2.0.tar.gz |
|---|---|
| Size | 7.9 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
0fa72373c191b8c14eeec11cb3db65c782215f87ff18745eab61e3b6673e1df3
|
|
BLAKE2b-256 checksum How to use checksums |
7a29a04df185991c8ca456767434fbe79cdd7be2c467e2a61cfaac6cfcb086c2
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
poetry/1.1.5 CPython/3.8.1 Linux/5.4.0-77-generic
|
Release files / rich_dataframe-0.2.0-py3-none-any.whl
| Download URL | rich_dataframe-0.2.0-py3-none-any.whl |
|---|---|
| Size | 8.1 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
257bea828316df1a878f6481fbd248a40597997b8213063e97b21c81430d7b55
|
|
BLAKE2b-256 checksum How to use checksums |
aec9a118b871f0e311f48e5eaa3fe5ec061d7fec9546520d9628001969ef9960
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
poetry/1.1.5 CPython/3.8.1 Linux/5.4.0-77-generic
|
Security for rich-dataframe 0.2.0
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.