male | MAchine | Machine Learning library

I'm trying to create an app that meets two random users in Django. my question is how to create an object Meeting out of 2 random users from my User model, I want something like a for loop so that every 2 users in my database have a meeting!

ps: I have only one day left to submit my work I will be so thankful if u help me

this is my code so far:

I have been trying to make a simple API, I need to send a request that will return a list of all individuals if they meet my criteria.

results = collection.find({'sex':'male', 'country':'usa', 'age':30})

This would give me all males in usa who are 30.

What I am looking for is something like

results = collection.find({'sex':'male', 'country':'usa', 'age':ANY})

Which should give me ALL males in usa regardless of age.

Is this possible?

I want to collect the names (Jenny, Tiffany, etc.) that are stored in every object. and these objects live in an array. I've used Array.prototype.every() and Array.prototype.forEach(), but I don't think they are the right methods.

I also want to note that majority of these codes are from Codaffection. I am practicing on developing in React.

If you would like to experiment with the code, click here.

In every object, there is an id, fullname, email and etc.

This is the code that adds, edits, generates unique ids for each employee, and gets all storage data.

Hi am trying to do a CRUD application am able to do the add user but i got stock with the edit user Actually for my edit user page i just copied the add user page there and then modified it

This is what my app has to do: normally when i enter the edit user page it has to show me the user's existing information then on my part i can now modify it if i wish and then it is stored in my mysql database but it doesn't return anything i actually console logged it to see if it returns anything but it doesn't

This code worked fine and it prints result in this format.

I need results in a nested dict format like this.

i need to check for duplicate values that might occur in a dictionary. I have a dictionary in the following layout. Any advise is welcome! thanks so much

the original dictionary

I'm trying to limit a calculation only when a field is blank. I have many other fields that are calculated simultaneously, I would like to limit the calculation to only the fields that have not been filled.

I don't know JS very well, so I hope to be able to find help here ... Thanks for any answers, I leave more info below.

Basically everything works fine. However, when the bodyfat field is empty, the calculation for BMR and TDEE Katch McArdle and Cunningham Formula is performed.

What I am trying to do is to calculate the McArdle and Cunningham Formula fields only when the Bodyfat field contains values.

I posted a similar question a week ago but I failed to identify the real problem. Therefore, the question was far from being correct.

Now, I clearly now what is going on but I cannot understand why it is happening. I also reviewed similar problems related with the same error but the solutions for these problems were not applicable to my case.

I am plotting the frequency distribution of a variable during the fieldwork progress of a survey. Therefore, it shows how the proportion of that variables has changed through time.

So, I have a variable (Startday) that tells which day the respondent took the survey, if he/she did not then it is NA. Then, I have the typical variables like sex or marital status.

This is the code to plot such graph

I have three large dataframes and I want to append some of the elements from one onto another based on several criteria. I looked up similar questions in Stack Overflow but they don't seem to work for my dataframe format (or I'm not skilled enough to adapt it properly).

What needs to happen is:

1. Filter by sex in maindf1
2. Search for the same ZCTA value in maindf1 in a rowname (first column) in maledflookup
3. Also search for the right age strata from a row in maindf1 in the column name of maledflookup
4. Add a new column of data to maindf1 row with matching ZCTA that has the census population value for that sex and age strata taken from maledflookup
5. Repeat with femaledflookup
6. End result is maindf1 having a censuspop value for every row that was matched by sex, ZCTA, and age strata

maindf1 is raw data where each row is an individual and columns are survey responses or collected data on individuals

The lookup table from the census website I had to use is in weird formatting so the easiest solution for me to fix one of the issues with it was to separate the lookup tables by sex first.

I had no luck in writing successful code as I'm not very experienced with coding in R yet. I tried some for & if loops and failed at adapting fuzzyjoin code for this task. I appreciate your help!

Example data: