Skip to content

docs: Audit and clean data methods #638

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
wants to merge 7 commits into
base: main
Choose a base branch
from

Conversation

MMenchero
Copy link
Contributor

Description

Includes a new tutorial showing the new audit and clean data methods from TimeGPT.

Copy link

Check out this pull request on  ReviewNB

See visual diffs & provide feedback on Jupyter Notebooks.


Powered by ReviewNB

Copy link
Contributor

github-actions bot commented Apr 22, 2025

Experiment Results

Experiment 1: air-passengers

Description:

variable experiment
h 12
season_length 12
freq MS
level None
n_windows 1

Results:

metric timegpt-1 timegpt-1-long-horizon SeasonalNaive Naive
mae 12.6793 11.0623 47.8333 76
mape 0.027 0.0232 0.0999 0.1425
mse 213.936 199.132 2571.33 10604.2
total_time 0.789 0.5711 0.0044 0.0034

Plot:

Experiment 2: air-passengers

Description:

variable experiment
h 24
season_length 12
freq MS
level None
n_windows 1

Results:

metric timegpt-1 timegpt-1-long-horizon SeasonalNaive Naive
mae 58.1031 58.4587 71.25 115.25
mape 0.1257 0.1267 0.1552 0.2358
mse 4040.21 4110.79 5928.17 18859.2
total_time 0.5549 0.482 0.0039 0.0034

Plot:

Experiment 3: electricity-multiple-series

Description:

variable experiment
h 24
season_length 24
freq H
level None
n_windows 1

Results:

metric timegpt-1 timegpt-1-long-horizon SeasonalNaive Naive
mae 178.296 268.121 269.23 1331.02
mape 0.0234 0.0311 0.0304 0.1692
mse 121588 219457 213677 4.68961e+06
total_time 1.6119 2.6587 0.0047 0.0042

Plot:

Experiment 4: electricity-multiple-series

Description:

variable experiment
h 168
season_length 24
freq H
level None
n_windows 1

Results:

metric timegpt-1 timegpt-1-long-horizon SeasonalNaive Naive
mae 465.454 346.978 398.956 1119.26
mape 0.062 0.0436 0.0512 0.1583
mse 834903 403769 656723 3.17316e+06
total_time 1.4017 1.8919 0.0049 0.0044

Plot:

Experiment 5: electricity-multiple-series

Description:

variable experiment
h 336
season_length 24
freq H
level None
n_windows 1

Results:

metric timegpt-1 timegpt-1-long-horizon SeasonalNaive Naive
mae 558.702 459.769 602.926 1340.95
mape 0.0697 0.0565 0.0787 0.17
mse 1.22728e+06 739162 1.61572e+06 6.04619e+06
total_time 0.5429 1.2165 0.005 0.0044

Plot:

@MMenchero
Copy link
Contributor Author

This been seating here for a few days, but tagging reviewers for validation.

@@ -0,0 +1,807 @@
{
Copy link
Member

@ngupta23 ngupta23 Apr 25, 2025

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

The details of the checks are shown below. Do we need to elaborate on it here? Maybe keep this section small.


Reply via ReviewNB

@@ -0,0 +1,807 @@
{
Copy link
Member

@ngupta23 ngupta23 Apr 25, 2025

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Can we use pretty print for the dictionary (it might be easier to read)?


Reply via ReviewNB

@@ -0,0 +1,807 @@
{
Copy link
Member

@ngupta23 ngupta23 Apr 25, 2025

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Does it not show the error for the missing values D002 here?


Reply via ReviewNB

@@ -0,0 +1,807 @@
{
Copy link
Member

@ngupta23 ngupta23 Apr 25, 2025

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Nice example here.


Reply via ReviewNB

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

Successfully merging this pull request may close these issues.

2 participants