Live Analytics Lab

Code, statistics & dashboards in your browser — no install.

Six free tools — full code notebooks, point-and-click statistics, and live dashboards. All in your browser, in seconds.

The full RStudio IDE in your browser — script editor, console, plots panel, and all the standard tidyverse packages preloaded.

Best for · Statistics · ggplot · dplyr · Regression · ANOVA

Launch RStudio

A real Jupyter notebook environment with NumPy, pandas, scikit-learn, and matplotlib already installed — open and start running cells.

Best for · Pandas · scikit-learn · Plotting · ML · Wrangling

Launch Jupyter

Colab

Google’s free Jupyter notebooks with on-demand GPU and TPU. Write Python, train deep-learning models with TensorFlow or PyTorch — sessions saved straight to your Drive.

Best for · Free GPU · Deep learning · PyTorch · TensorFlow

Open Colab

Notebooks, 200K+ public datasets, and live ML competitions in one place. Free Python & R environments with GPU access — and the world’s largest data-science community.

Best for · Datasets · Competitions · ML · Community

Open Kaggle

Free, open-source statistics with a clean point-and-click interface — t-tests, ANOVA, regression, mixed models, factor analysis. Built on R, no code required. Perfect SPSS replacement for academic research.

Best for · SPSS users · Thesis stats · ANOVA · Bayesian · No-code

Open jamovi

Looker Studio

Google’s free dashboard & reporting tool — connect Sheets, BigQuery, Search Console, and 800+ sources to build interactive reports.

Best for · Dashboards · Reports · KPIs · Sharing · Free

Open Looker Studio

How it works

From click to code in under a minute.

Click Launch

A clean R or Python environment opens in a new tab. Loading takes a few seconds — no setup, no sign-up.

Write & run code

Real RStudio or Jupyter, full functionality. Standard packages preinstalled — load datasets, run models, plot results.

Save before you close

Sessions are temporary. Download your scripts or notebooks locally before closing the tab — see the heads-up below.

Heads up

Sessions are temporary & private — your work disappears when the tab closes. Always download your .R / .ipynb files locally before you finish.

Try this first

A taste of what you can do.

Paste either snippet into a fresh session to see the environment in action.

R · RStudio

# A quick look at the iris dataset
summary(iris)
plot(iris$Sepal.Length, iris$Petal.Length,
     col = iris$Species, pch = 19,
     main = "Sepal vs Petal Length")

Python · Jupyter

# Load a sample dataset and plot it
import seaborn as sns
import matplotlib.pyplot as plt

iris = sns.load_dataset("iris")
sns.scatterplot(data=iris,
                x="sepal_length",
                y="petal_length",
                hue="species")
plt.show()

Browse our free analytics books

Hands-on guides for Business Analytics, R Programming, Power BI, and Decision Science — written to pair with the lab.