low | low level data type and utils in Golang | REST library

I am trying to check if the value in 'diff' column is greater than 0 if it is, then the value in 'worth' should be False else it should be True

I am using the below code to compute and check but it always gives me True. Can anyone point here what is the mistake. I am attaching pic of output as well

I have bitcoin historical data. I split the "DATE" Colum as "year month days and hour" because I wanted to sort data based on hours["AS it is hourly base data"]. the data goes up to 2021-12 ie Decmber["the dates goes from 1 to 30 every month"]. I want to sort this data further as:- "2019-Jan, 2020-Jan 20201-Jan" then "2019-Feb,2020-Feb, 2021-Feb" and soon on

can this be done by saying I have split the "DATE" column? if YES please any suggestion on how this can be achieved

The original "DATE" colum was as follows :- 2019-01-01T00:00:00Z

When a divide-and-conquer recursive function doesn't yield runtimes low enough, which other improvements could be done?

Let's say, for example, this power function taken from here:

I have a dataframe output from the python script which gives following output

i Want to remove all rows where time is equal to 15:30:00. tried different things but unable to do. Help please.

I have a dataset with the name of Danish ministers and their position from 1990 to 2020 (data comes from dataset called WhoGovern; https://politicscentre.nuffield.ox.ac.uk/whogov-dataset/). The dataset consists of the ministers name, the ministers position, the prestige of that position, and the year in which the minister had that given position.

My problem is that some ministers are counted twice in the same year (i.e., the rows aren't unique in terms of name and year). See the example in the picture below, where "Bertel Haarder" was both Minister of Health and Minister of Interior Affairs in 2010 and 2021.

I want to create a dataset, where all the rows are unique combinations of name and year. However, I do not want to remove any information from the dataset. Instead, I want to use the information in the prestige column to combine the duplicated rows into one. The observations with the highest prestige should be the main observations, where the other information should be added in a new column, e.g., position2 and prestige2. In the example with Bertel Haarder the data should look like this:

(PS: Sorry for bad presenting of the tables, but didn't know how to create a nice looking table...)

Here's the dataset for creating a reproducible example with observations from 2010-2020:

Good day, everyone.

I want to have two separate TensorFlow models (f and g) and train both of them on the loss of f(g(x)). However, I want to use them separately, like g(x) or f(e), where e is an embedded vector but received not from g.

For example, the classical way to create the model with embedding looks like this:

Following script is a combination of RSI and Higher High and Lower Low script. The issue is that the HH LL labels are aligned for the price not on the RSI Line. How to align the labels to the RSI line? It is basically showing the Higher Highs and Lower Lows of RSI. The labels need to stick on to the respective RSI line.

I know there are some other questions (with answers) to this topic. But no of these was helpful for me.

I have a postfix server (postfix 3.4.14 on debian 10) with following configuration (only the interesting section):

I would like to find minimum distance of each voxel to a boundary element in a binary image in which the z voxel size is different from the xy voxel size. This is to say that a single voxel represents a 225x110x110 (zyx) nm volume.

Normally, I would do something with scipy.ndimage.morphology.distance_transform_edt (https://docs.scipy.org/doc/scipy-0.14.0/reference/generated/scipy.ndimage.morphology.distance_transform_edt.html) but this gives the assume that isotropic sizes of the voxel: