From fbb63c2939e5000a43f6bbda54cd4125d639f5c4 Mon Sep 17 00:00:00 2001 From: elmartinj <36212821+elmartinj@users.noreply.github.com> Date: Fri, 29 Aug 2025 14:05:32 -0600 Subject: [PATCH 1/2] Update README.md update on hello world example to let user know they can access dataframe --- README.md | 19 ++++++++++++++++++- 1 file changed, 18 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index a28245c..dc00e13 100644 --- a/README.md +++ b/README.md @@ -159,6 +159,23 @@ result = tc.forecast(df=df, freq="MS") # - forecast_analysis: Interpretation of the forecast results # - user_query_response: Response to the user prompt, if any print(result.output) + +# You can also access the forecast results in the same shape of the +# provided input dataframe. +print(result.fcst_df) + +""" + unique_id ds Theta +0 AirPassengers 1961-01-01 440.969208 +1 AirPassengers 1961-02-01 429.249237 +2 AirPassengers 1961-03-01 490.693176 +... +21 AirPassengers 1962-10-01 472.164032 +22 AirPassengers 1962-11-01 411.458160 +23 AirPassengers 1962-12-01 462.795227 +""" + +``` ```
Click to expand the full forecast output @@ -206,7 +223,7 @@ performing model and generated forecasts considering seasonality and trend, aimi accuracy and reliability surpassing basic seasonal models.' """ ``` - +j
--- From e030707c683864ebf97b824ab1937982c84e6ee1 Mon Sep 17 00:00:00 2001 From: elmartinj <36212821+elmartinj@users.noreply.github.com> Date: Fri, 29 Aug 2025 14:17:57 -0600 Subject: [PATCH 2/2] Update README.md refinements on welcome page --- README.md | 11 +++++++---- 1 file changed, 7 insertions(+), 4 deletions(-) diff --git a/README.md b/README.md index dc00e13..2d6a281 100644 --- a/README.md +++ b/README.md @@ -107,9 +107,9 @@ TimeCopilot is available on PyPI as [`timecopilot`](https://pypi.org/project/tim and that's it! -!!! Important - - TimeCopilot requires Python 3.10+. Additionally, it currently does not support macOS running on Intel processors (x86_64). If you’re using this setup, you may encounter installation issues with some dependencies like PyTorch. If you need support for this architecture, please create a new issue. - - If on Windows, Python 3.10 is recommended due to some of the packages' current architecture. +**Important !!!** +- TimeCopilot requires Python 3.10+. Additionally, it currently does not support macOS running on Intel processors (x86_64). If you’re using this setup, you may encounter installation issues with some dependencies like PyTorch. If you need support for this architecture, please create a new issue. +- If on Windows, Python 3.10 is recommended due to some of the packages' current architecture. --- @@ -122,6 +122,9 @@ Here is an example to test TimeCopilot: import pandas as pd from timecopilot import TimeCopilot +# Use the following line if using a jupyter notebook environment!!!! +nest_asyncio.apply() + # Load the dataset # The DataFrame must include at least the following columns: # - unique_id: Unique identifier for each time series (string) @@ -223,7 +226,7 @@ performing model and generated forecasts considering seasonality and trend, aimi accuracy and reliability surpassing basic seasonal models.' """ ``` -j + ---