Skip to content

Instantly share code, notes, and snippets.

@balzer82
Last active June 20, 2022 14:38
Show Gist options
  • Save balzer82/5cec6ad7adc1b550e7ee to your computer and use it in GitHub Desktop.
Save balzer82/5cec6ad7adc1b550e7ee to your computer and use it in GitHub Desktop.
TimeSeries Decomposition in Python with statsmodels and Pandas
Display the source blob
Display the rendered blob
Raw
Loading
Sorry, something went wrong. Reload?
Sorry, we cannot display this file.
Sorry, this file is invalid so it cannot be displayed.
@fclesio
Copy link

fclesio commented Oct 10, 2019

@Cyberguille

Just use that before the plot and you will be fine:

pylab.rcParams['figure.figsize'] = (14, 9)

@XiaoLaoDi
Copy link

when we get the decomposition components, how to predict the future steps?

@DavidD32-svg
Copy link

Thanks for your comments,

I also want to know how can i use this data in ARIMA or FOURIER.

@jcarless
Copy link

jcarless commented Oct 5, 2020

@Cyberguille

Just use that before the plot and you will be fine:

pylab.rcParams['figure.figsize'] = (14, 9)

Worked for me, thanks!

@pratikask
Copy link

Hi..am trying to use your method in my project and am using many issues. Can anyone help me decompose my time series??

@Ibitayoabiodun
Copy link

Just use that before the plot and you will be fine:

pylab.rcParams['figure.figsize'] = (14, 9)

Works perfectly!

@simonyelisey
Copy link

@pratikask if you still need a help I can help you

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment