Spiced | A simple tile-based game engine backed by ChaiScript | Game Engine library

MenuItems.filter((item) => "Drinks") return always true

What you should be doing is comparing the category to drinks.

MenuItems.filter((item) => item.category === "Drinks")

Wrap your figure elements inside of a div and set that to display as flex. See below:

To solve your specific issue, you can generate dummy variables to run your desired clustering.

One way to do it is using the dummy_columns() function from the fastDummies package.

Updated

As @dcarlson recommended, you can run mice on the entire dataframe, then you can use complete to get the whole output dataframe. Then, you can join the new data with your original dataframe.

Depending on your restrictions, you can try to separate the Visual Studio tests into its own job within the pipeline so that you can run those on a windows-server-2019 agent, while still building the app using the Ubuntu agent in a separate job. One job running your original build steps on Ubuntu (what was working originally), then a second job to run the Visual Studio tasks (windows-server-2019).

Because initial value of selectedDish is null. So filter will return an empty array. And dish will be undefined.

You should check value of this.props.dish before return instead this.props

You can't use index i as it is representing an object in pizza array. It is fine for index === 0 but whent the index exceeds 0 then it will access the elements in sizes array beyond its length.

Let say i is 1 then

• i --> 1
• i + 1 --> 2
• i + 1 --> 3

and sizes array doesn't have any element with index 3. It has only index upto 2(zero-based)

"sizes": [{ "Small": 0 }, { "Medium": 100 }, { "Large": 200 }]

You need to take another index variable let say j and increment it.

You can create an HTML template in JavaScript and use it over to generate your multiple

Using Template Literals you can easily use with the loops

I think you misunderstand what a CoroutineScope is. It determines the lifecycle of coroutines that it runs, but not of the objects created in the process of running those coroutines.

viewModelScope is a CoroutineScope that automatically cancels any coroutines it is running when the associated ViewModel is torn down. The coroutine doesn't know what you're doing with it. Cancelling a coroutine merely stops it from running to completion, like returning from a function early. In your code, you set your listeners and haven't stored references to them besides in the views they are set to, so their lives are tied to their respective view's lives.

If you were going to use a coroutine in your fragment to set up something for your UI, you would use the Fragment's lifecycleScope, not the ViewModel's viewModelScope. Like if you were fetching something to show in your UI, you would want that coroutine to be cancelled when the Fragment is destroyed, not the ViewModel which might be outliving the Fragment.

Your use of a coroutine in your example code looks pointless, because I don't see any blocking or asynchronous suspend functions being called. You mentioned setting up site markers is taking like 200ms. I'm not familiar with Google Maps since I haven't used it in the past several years, so I'm not sure which part is time-consuming. Usually, UI elements do not allow you to interact with them on background threads, so you might be out of luck. But maybe the time-consuming part is allowed to be done on background threads. You'll have to read the documentation. Using a coroutine for this won't make it take less time, but can prevent the UI from stuttering/freezing.

If you were going to do some long computation with a coroutine, you would need to switch dispatchers to do the blocking work and interact with the UI elements back on the main dispatcher. Simply putting something in a coroutine doesn't make it take less time, but it provides a convenient way to do something on another thread and then continue on the main thread after the result is ready. For example: