How far could you drive your business with a
time series ecosystem 18x faster?

Test it and get all the details

See it for yourself, intuitive features designed to offer better performance.

Benchmarks

Be ready for unparalleled control and flexibility when working with data

Geek out the specs

Your data ingestion just 18X faster

We know data ingestion can be a pain

We, however, can take you to a smooth ecosystem, where all capabilities are easily integrated, allowing you to work with huge time series data faster than ever.

See how fast it is? Ready for you to handle data seamlessly and efficiently.

Check up to 1 Billion data points in a time series!

Want to quickly navigate through a Billion data points? No problem.

You can go into as much detail as you need. Create and play with intelligent features, and share it with whoever you want in just a few clicks.

Try it yourself, see how it works!

Want to learn all the specs?

Our state-of-the-art technology enables you to create and play with intelligent feautures.  Experience Shapelets

Join the Challenge

Don’t just take our word for it. Try this code example and see for yourself what Shapelets is capable of.  Join the challenge

Much more output in just a few lines of code

It only takes you a few lines of code to build your solution

We help you push the limits of your work

You can see this live example
checkbox

# import all the necessary libraries
from shapelets.apps import DataApp, Checkbox

# Create data app
app = DataApp(name=“checkbox”)

# Create a checkbox widget and place it in the data app
control = app.checkbox(title=“Option”, toggle=True)
app.place(control)

# Register the DataApp
app.register()

display image file

# Import all the necessary libraries
from shapelets.apps import DataApp

# Create a data app
app = DataApp(“display_image_file”)

# Path to the image
img_path = “/root/test/Resources/hello.jpg”

# Create an image widget
img = app.image(img=img_path, caption=“Test image”)

# Place image into the data app
app.place(img)

# Register data app
app.register()

button

# Import all the necessary libraries
from shapelets.apps import DataApp

# Create a data app
app = DataApp(“button”)

# Create a button and place it in the data app
button = app.button(“Press me”)
app.place(button)

line chart from_panda df

# import the necessary libraries
from shapelets.apps import DataApp
import pandas as pd

# Instantiate DataApp
app = DataApp(“linechart_from_pandas_df”)

# Create pd.DataFrame from list for the example – it can be use for anythoer type of data
data = {“series1”:[420, 300, 380, 390]}
df = pd.DataFrame(data=data, index=range(len(data[“series1”])))

# Create line chart widget and plot df
lc = app.line_chart(data=df, title=“My title”)

# Place line chart widget
app.place(lc)

# Register data app
app.register()

selector

# Import all the necessary libraries
from shapelets.apps import DataApp

# Instantiate data app
app = DataApp(name=“My Selector”, options=[“a”,“b”,“c”])

# Place selector in data app
app.place(selector)

# Register data app
app.register()

folium example code

# Create a data app
app = DataApp(“folium_example”)

# Create a folium map with a specific location – We are currently using the locatiopn of Portland Oregon
m = folium.Map(location=[45.5236, –122.6750])

# Create the folium map and place it in the data app
folium_chart = app.folium_chart(title=(“Folium Map”, folium=m)
app.place(folium_chart)

# Register the data app
app.register()

Do you want to know more?

We invite you to go deeper and discover the power of our platform for yourself.

Do you want to know more?

We invite you to go deeper and discover the power of our platform for yourself.

Are you ready?

Just a few steps, you will have your first data ready

INSTALLER
setup.py

Support

Need help from our experts? Maybe try a few examples?

Sometimes we need a little help to get the most out of our work. That’s why we offer you all the expert help you need, here.

Github

Join us!

Making the most of your data

Browse Shapelets examples in our repository, explore, engage, and raise issues.

shapelets platform architecture

Documentation

Last updates, all features

Get all the technical details 

For current version is necesary add at the top of your python DataApp script the login.

>>>import shapelets assh

>>>sh.login(user_name=”my_user_name”,password=”my_password”)

Report an isuue

Any questions?

Spotted an issue? Let us know

Found a bug or have a valuable suggestion? Report an issue and help us improve!

FAQ #1

Your content goes here. Edit or remove this text inline or in the module Content settings. You can also style every aspect of this content in the module Design settings and even apply custom CSS to this text in the module Advanced settings.

FAQ #1

Your content goes here. Edit or remove this text inline or in the module Content settings. You can also style every aspect of this content in the module Design settings and even apply custom CSS to this text in the module Advanced settings.

FAQ #1

Your content goes here. Edit or remove this text inline or in the module Content settings. You can also style every aspect of this content in the module Design settings and even apply custom CSS to this text in the module Advanced settings.

Repsol, Oil & Gas

A customer success story

Achieving Data Granularity and Accelerating Visualization Development
See how Repsol did it!

Repsol is one of the largest oil companies in the world, and they needed a software solution to:

  • Faster significant data ingestion from refinery plant sensors.
  • Build accurate models for stronger analytics.
  • Base their visualizations on real-time generated data, instead of static data.
  • Improve data granularity during the ingestion process

Faster significant data ingestion from refinery plant sensors.

Build accurate models for stronger analytics.

Base their visualizations on real-time generated data, instead of static data.

Improve data granularity during the ingestion process.

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  • Reduced back-and-forth in the visualization development process 50% 50%
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  • Simplify data science project development by 80%, minimizing interactions and tasks. 80% 80%
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Cut costs and boost budget

Repsol adopts a free data science tool powered by Shapelets.