tsfeatures | Calculates various features from time series data | Time Series Database library
kandi X-RAY | tsfeatures Summary
kandi X-RAY | tsfeatures Summary
Calculates various features from time series data. Python implementation of the R package tsfeatures.
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tsfeatures Key Features
tsfeatures Examples and Code Snippets
Lines of Code : 9License : Permissive (MIT)
Copyfrom tsfeatures import acf_features
tsfeatures(panel, freq=7, features=[acf_features])
def number_zeros(x, freq):
number = (x == 0).sum()
return {'number_zeros': number}
tsfeatures(panel, freq=7, features=[acf_features, number_zeros])
from tsfeatures import tsfeatures
tsfeatures(panel, freq=7)
FREQS = {'H': 24, 'D': 1,
'M': 12, 'Q': 4,
'W':1, 'Y': 1}
tsfeatures(panel, dict_freqs={'D': 7, 'W': 52})
from tsfeatures.tsfeatures_r import tsfeatures_r
tsfeatures_r(panel, freq=7, features=["acf_features"])
Community Discussions
Trending Discussions on tsfeatures
QUESTION
After doing devtools::check(cran=TRUE) I got this warning. I saw others say we cannot use ":::" on CRAN. So, how to fix this problem? Thank you for helping!
...ANSWER
Answered 2020-Jul-22 at 08:35Here you could find the answer. https://github.com/drsimonj/twidlr/issues/16
Summing up there are many options:
- Contact package authors and ask them to export the relevant function.
- Copy the function source code and cite the author appropriately. Use roxygen2 @references or manually \references in mas file. In my opinion reference at the level of function is satisfactory if this function is one of many in your package.
- Another trick is using getFromNamespace()
fun <- utils::getFromNamespace("fun", "pkg"). When you building a package the order and place of functions is not relevant.
QUESTION
I have some time series data that I want to lapply or map over some functions. For example, I want to apply the two functions in funcs to the data.
Code:
...ANSWER
Answered 2020-May-09 at 19:18You’re using map from the ‘purrr’ package incorrectly.
You need to pass the mapper function either as a function, or as a formula. You are attempting to pass a formula containing a function.
To fix this, write either
QUESTION
I am trying to apply a series of functions to my data, however I am going wrong a little bit.
The functions can create more than one column so I use bind_rows to add them to the original data.
What I am trying to do is to take the two functions in functions and map them over a list to create new columns in each list, I would like to use mutate or summarise.
ANSWER
Answered 2019-Oct-19 at 20:13The data frames in your example list Data only contain two rows, which is too small for the tsfeatures function. Another issue is when you do .x["Value"] the output is a data frame, but the documentation of the tsfeatures function said the first argument should be a a list of univariate time series object or a vector. Therefore, I assume the code you should use is .x[["Value"]], which results in a vector.
I tried you example as follows by combining all data frame in Data to a single data frame.
QUESTION
I am trying to compute some function and then spread my data based on the results.
Code & Data:
-- Preprocessing:
...ANSWER
Answered 2019-Aug-08 at 10:51Instead of using spread, we can just subset max_level_shift(daily.returns) by positions, as we know max will be in the first position and time in the 2nd position.
QUESTION
tsfeatures() says that approx() fails due to needing at least two non-NA values to interpolate. I can't find any NAs in my time series or the time series index, and I can construct a toy example with no NA values, ordered and unique indices, and still reproduce the error.
There appear to be a number of previous questions concerning R's tsfeatures() function, but I can't find one that explains why I'm receiving the error:
ANSWER
Answered 2019-Jul-11 at 09:29The error is due to the fact that tsfeatures() automatically scales the time series by default. When you pass a constant series, scaling reduces the series to NaNs. This is now prevented in the current github version -- fixed here.
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