We have 4 cameras “camA”, “camB”, “camC”, “camD” installed at every junction along a road and in this sequence. The flow of traffic is such “camA” is at the beginning, and “camD” is at the end. Whenever a vehicle passes a junction or makes a turn at the junction, the camera is positioned to record down the license plate number.
Tag: time-series
Where does xarrays time.hour start and end?
I am not sure where xarray starts and ends the hour. For example: When I get a value for 1 o’clock, are those values form 00:00-01:00 or from 00:30-01:30 or from 01:00-02:00? In my specific case I have datas form several year token every minute and I need to know what exact timeslice the mean is when its plotted at
Lineplot – plot a single legend for uneven number of subplots
I’m working on the following graph where I’d like to plot is single legend that applies to all, essentially this would be a small box where blue color line is AB=0 and green line is AB = 1. Moreover, I’m using plt.subplot(… since it is possible that might have to deal with uneven number of columns to plot. I tried
Manipulate the Dataframe to start from the nearest varying Midnight timestamp
My goal: I have a dataset that gets generated every day at random hours leading to the first row to start at a random time. I want to make this dataset start from the nearest midnight date. For example, if the date on the first row is 2022-05-09 15:00:00, I would have to slice the data to make it start
Plotting time series directly with Pandas
In the above dataframe, all I want to create a line plot so that we have info on trends per year for each of the columns. I’ve read about pivot-table on related posts, but when I implement that, it says there are no numbers to aggregate. I don’t want to aggregate something. I just need the y-axis in terms of
How to calculate a Process Duration from a TimeSeries Dataset with Pandas
I have a huge dataset of various sensor data sorted chronologically (by timestamp) and by sensor type. I want to calculate the duration of a process in seconds by subtracting the first entry of a sensor from the last entry. This is to be done with python and pandas. Attached is an example for better understanding: enter image description here
Pandas – stack time columns with time and date
I have date and time data now I want to reduce this dataframe to two columns with Timestamp (date+time) in a column and value in another column current df – desired df – Here is original list from which I’m creating my dataframe – Answer Use melt to flatten your dataframe and set Time as a name of the variable
Setting Time with interval of 1 minute
I have a dataset which comprises of minutely data for 2 stocks over 3 months. I have to create date in the first column and time (with interval of 1 minute) in the next column for 3 months. I am attaching the snap of 1 such data set. Kindly help me to solve this problem. Data Format Answer -Create 3
How to include future values in a time series prediction of a RNN in Keras
I currently have a RNN model for time series predictions. It uses 3 input features “value”, “temperature” and “hour of the day” of the last 96 time steps to predict the next 96 time steps of the feature “value”. Here you can see a schema of it: and here you have the current code: Here you have some test data
Problem with plotting peaks using find_peaks from SciPy to detect drastic up/down turns or global outliers
Let’s say I have following dataframe contains value over time or date: I inspired from this answer to detect peaks and valleys via below code: This is the output: The problems: I can’t figure out how I can configure find_peaks() documentation to reach meaningful/drastic peaks & valley with respect to threshold as global outliers. I also checked this post but