1. Load data from a ZIP

GAMU: Presentation of `webR` functionalities

How could our app look like

Tomas Pompa

October 2025

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1. Load data from a ZIP

In this section, we will work with a custom dataset uploaded as a ZIP file. After uploading the ZIP file, we will:

Visualize the data in a scatter plot to understand its structure.
Fit a linear regression model to investigate the relationships between variables.
Plot the fitted regression lines alongside the original data points for comparison.

1.1 Upload and extract the ZIP

Start by uploading your ZIP file containing the datasets. The ZIP can contain multiple folders; for example, typical folders are Before and After. Once uploaded, the files will be extracted into the webR virtual filesystem and listed below.

Select a ZIP file with your data:

    No ZIP data uploaded yet.

Files in Before folder:

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Files in After folder:

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1.2 Select the CSV file

Now, select a CSV file from one of the extracted folders. Enter the folder name and the CSV filename you want to analyze, then click Load CSV file.

CSV folder:
CSV file:

    CSV file not uploaded yet.

1.3 Plot the data

Visualize the data points in a scatter plot. Enter a title for the graph below and click Plot the data:

Title for the graph:

    Press Plot the data button to see the graph ...

1.4 Fit linear regression model

Fit a linear model with interaction terms using the lm() function in R. Click the button below to compute the regression coefficients:

    Press "Fit linear model" button to fit the model ...

1.5 Plot the fitted lines

Finally, visualize the fitted regression lines along with the data points. You can enter a title for the plot: