Load from Epidata API

(source: cdc.gov)
(source: cdc.gov)
(source: cdc.gov et al)
(source: delphi.midas.cs.cmu.edu)
(source: google.com)
(source: private Google API)
(source: healthtweets.org)
(source: dumps.wikimedia.org)
(source: private CDC dataset)
(source: nidss.cdc.gov.tw)
(source: nidss.cdc.gov.tw)
(source: delphi.midas.cs.cmu.edu)
(source: delphi.midas.cs.cmu.edu)
(source: delphi.midas.cs.cmu.edu)
(region to filter data by)
(fetch the most up-to-date/stable data)
(fetch data "as-of" a specific week)
(fetch data lagged by a number of weeks)
(this option has no additional parameters)

Load from CSV File

(treat rows as columns and vice versa)
(extract column names, then discard first row)
(otherwise assume daily starting on 2000-01-01)
(format: YYYY-MM-DD; ex: 2015-05-02)
(format: YYYYWW; ex: 201522)
(format: YYYY, WW; ex: 2015, 22)
(format: YYYY.YYY; ex: 2015.456)
(format: YYYY, MM; ex: 2015, 05)
(all columns are zero-indexed)

(for when multiple overlapping time series are in the same file; ex: FluView Regional data)

Add Custom Line

(short string)

(format is YYYY-MM-DD or YYYYWW)
(any floating point number)

(format is YYYY-MM-DD or YYYYWW)
(any floating point number)

Tip: you can make a vertical line by using the same date at both endpoints!

Create a new Dataset

Select Inputs
In the tree to the left, select (by checking) the datasets to start with. How many you select depends on the function you want to apply.

Open the developer console
In chrome, the keyboard shortcut is Ctrl+Shift+J

Call the function createDataset
The function accepts two parameters: a name for the output dataset, and a function to apply to the selected dataset(s).

Available Functions ("Kernels")
Kernels.sum, Kernels.product, Kernels.average
Selected Datasets: 1 or more
Kernel Parameters: none
Action: Calculates the sum, product, or average of the selected datasets.

Selected Datasets: 2
Kernel Parameters: none
Action: Calculates the product, divided by 100, of the selected datasets. (Intended for 'wILI' and '%positive' datasets.)

Selected Datasets: 1
Kernel Parameters: scale
Action: Scales the selected dataset by the provided scale parameter.

Selected Datasets: 2
Kernel Parameters: inverse (optional)
Action: Calculates the quotient of the selected datasets. (Flips numerator and denominator if inverse is true.)

Compute ILI+: createDataset('ILI+', Kernels.iliplus())
Scale GFT by 1/1000: createDataset('GFT/1000', Kernels.scale(0.001))
Take the average: createDataset('avg', Kernels.average())

Run regression

Regression target selection: