I like to interpolate a time series, so that the timestamp is exact 0.1 Hz. So the first step maybe would be something like library(tidyverse) library(zoo) options(digits.secs = 3, pillar.sigfig ...

I would like to find (in python) the local minimum and maximum values in OHLC data, under the condition that the distance between these values is at least +-5%. Temporal Condition Note that for an...

I have a count time series data which I'm able to use to determine the parameters of the underlying stochastic process. For example say I have a SARIMA (p,d,q)(P,D,Q)[S] seasonal ARIMA model. How ...

I am trying to do out of sample forecasting using python statsmodels. I do not want to just forecast the next x number of values from the end of the training set but I want to forecast one value at...

Are there any lossless compression methods that can be applied to floating point time-series data, and will significantly outperform, say, writing the data as binary into a file and running it thro...

I have few weeks data with units sold given xs[weeks] = [1,2,3,4] ys['Units Sold'] = [1043,6582,5452,7571] from the given series, we can see that although there is a drop from xs[2] to xs[3] but o...

I have a timestamp column where the timestamp is in the following format 2016-06-16T21:35:17.098+01:00 I want to extract date and time from it. I have done the following: import datetime as dt ...

I have a Pandas DataFrame containing the date that a stream gage started measuring flow and the date that the station was decommissioned. I want to generate a plot showing these dates graphically. ...

My question is different ways to connect mongodb with grafana Link for reference ?

I have identified one pandas command timeseries.loc[z, x] = y to be responsible for most of the time spent in an iteration. And now I am looking for better approaches to accelerate it. The loop...

I am analyzing the following data: Raw data (seperated with spaces): 1 1 1.1 1 0.9 1 1 1.1 1 0.9 1 1.1 1 1 0.9 1 1 1.1 1 1 1 1 1.1 0.9 1 1.1 1 1 0.9 1 1.1 1 1 1.1 1 0.8 0.9 1 1.2 0.9 1 1 1.1 1.2 1...

im trying to temporal fusion transformer from pytorch_forecasting module but im getting the error in trainer.fit method:model must be a LightningModule or torch._dynamo.OptimizedModule, got Tempora...

There seems to be no function that simply calculates the moving average on numpy/scipy, leading to convoluted solutions. My question is two-fold: What's the easiest way to (correctly) implement ...

I want to parse the time from a column of a sub second precision timeseries .csv file but it returns NaT for some timestamps. A quirk of the dataset is, that every non-full second will be represent...

Suppose I wish to re-index, with linear interpolation, a time series to a pre-defined index, where none of the index values are shared between old and new index. For example # index is all precise...

I have been working on a project for estimating the traffic flow using time series data combine with weather data. I am using a window of 30 values for my time series and I am using 20 weather rela...

I'm working on a multivariate (100+ variables) multi-step (t1 to t30) forecasting problem where the time series frequency is every 1 minute. The problem requires to forecast one of the 100+ variabl...

I've got a pandas DataFrame that looks like this: sum 1948 NaN 1949 NaN 1950 5 1951 3 1952 NaN 1953 4 1954 8 1955 NaN and I would like to cut off the NaNs at the beginning and at the end ONLY (...

Have been working with time series in Python, and using sm.tsa.seasonal_decompose. In the docs they introduce the function like this: We added a naive seasonal decomposition tool in the same vei...

How do I use strptime or any other functions to parse time stamps with milliseconds in R? time <- "2010-01-15 13:55:23.975" print(time) # [1] "2010-01-15 13:55:23.975" strpti...

I have data in an hourly values. SNo Date Hour X 1 2006-12-17 00:00:00 1.8824667 2 2006-12-17 01:00:00 3.3494000 3 2006-12-17 02:00:00 1.5872667 4 2006-12-17 03:00:00 1.6622000 5 2006-12-17 04:00:...

ERROR: Could not find a version that satisfies the requirement httpstan<4.5,>=4.4 (from pystan>=2.14->fbprophet) (from versions: 0.1.0, 0.1.1, 0.2.3, 0.2.5, 0.3.0, 0.3.1, 0.4.0, 0.5.0, ...

I am looking for efficient ways to remove outliers in my data. I have tried several solutions that I found here on Stack Overflow and elsewhere but none of them worked for me (4 high values of 2163...

I would like calculate the Hurst exponent with R. Is there a library or built in function that can do this? any suggestion will be appreciated (even weblinks to references). update: thanks to the c...

I have some problems executing an additive model right. I have the following data frame: And when I run this code: import statsmodels as sm import statsmodels.api as sm decomposition = sm.tsa.seas...