Good day everyone!
I am pleased to introduce datamallet to you.
Datamallet is an open source collection of helpful functions and modules built by Data scientists for Data scientists, to help expedite the data science workflow.
Datamallet is built on top of Scikit-learn, plotly, pandas, numpy and scipy. It contains helpful scikit-learn transformers for preprocessing data, creating new features and automatic data visualization.
Installation
pip install datamallet
Since this is the plotly forum, I would like to show how the autoplot function within datamallet works.
Library imports
from datamallet.visualization import AutoPlot
import plotly.express as px
from datamallet.visualization import AutoPlot
Use inbuilt dataframe from plotly express (this can be replaced with your dataframe
tips = px.data.tips()
Instantiate an autoplot object
autoplot = AutoPlot(df=tips, include_scatter=True,include_pie=True,include_box=True,
include_sunburst=True,
include_violin=True,
include_treemap=True,
include_histogram=True,
include_correlation=True,
create_html=True,
filename='autoplot')
Call the show method, this creates an html file with all the plotly charts, as well as a list of plotly graph objects
list_of_charts = autoplot.show()
Look in your directory, and there should be an autoplot.html file (you can change the filename attribute to anything you want), this file would contain scatter plots, correlation plots, histograms, boxplots, violinplots, treemaps, sunburst charts, pie charts (more charts to come).
These charts are created by some heuristics which I have come across during my day to day job as a Data scientist. and more attributes can be specified in the Autoplot class.
As of version 0.10.2, (over 20 releases so far) datamallet supports the following chart types:
-Scatter plots.
-Correlation plots.
-Histogram.
-Box plots.
-Violin plots.
-Treemaps.
-Sun burst Charts.
-Pie Charts.
And a ton of scikit-learn compatible data transformers.
I am interested in having new collaborators and people interested in becoming core developers 
.
Important links
Github repo https://github.com/bodealamu/datamallet
Pypi page https://pypi.org/project/datamallet/
, Thanks 
for sharing.