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I have a list that includes the paths of the files (in my case movies), which is called collectMovies and has followed data structure:

I am trying to calculate a NPV of several cashflows with continuous compounding. However when trying to refer to the optional parameter (which signals that the NPV will be continuous compounding), i get #VALUE! instead of a valid NPV

My VBA code is as follows:

I need to customize cash on delivery (COD) in WooCommerce based on user role and product category.

Requirements:

• By default COD is hidden
• COD is visible when a product in cart, belongs to a certain category (category 1)
• Users who have the role "x" must always see COD, even if they don't have category 1 products in the cart.

This is my code attempt to meet the above requirements:

I have a DataFrame with cash, inflows and outflows. I need to create a feature survival that is the maximum number of periods the cash is enough to pay the projection of outflows (excluding the inflows from the computation).

Let's take an example from the table below.

(Again, the inflows do not count in this exercise).
In t=1, from the starting cash = 100, I can add the outflows: -20, -50, -10, -10 e still having a positive cash (100-20-50-10-10 = 10 > 0) while with the outflow in t=5 the cash would be negative. So, as long as I can "survive" 4 periods in t=1 the survival = 4.
In t=2 the survival = 3 and so on.

As it is a big DataFrame, how can I do it efficiently with Pandas?

I'm developing an app which has to fetch new orders from the Firestore database, I used componentDidMount to refresh the screen every 10 seconds and launch the fetchNewOrders function, if new orders are available, the function should push that object into the state array newOrder, and display the orders in the FlatList below. When I start the code it returns the error TypeError: undefined is not an object (evaluating 'item.id'), I also wrote the example of an array I'm fetching from the database.

Screen

Trying to install Midone - Vuejs 3 Admin Dashboard Template + HTML Version + XD Design File ( HTML Version ) from https://themeforest.net/item/midone-vuejs-admin-dashboard-template/28123408 in new Laravel 8 / inertiajs/vuejs3 app / inertia-vue3 app

I read instructions how to install Midone under Laravel 8 / app at https://themeforest.net/item/midone-vuejs-admin-dashboard-template/28123408/comments?page=14

In the webpack.mix.js file mentioned line :

I'm making a simple bit of JSX that returns different text based on the value of a variable passed in from the back end. Although the card is displayed correctly up to and including the {irr}, the code block with the ifs is simply not executing. There are no errors in the build process or browser, and none of the console.log statements are logged either.

I've done this successfully a few times before, even copy-pasting some of the code from another (working) part of the project as the basis of this bit, and it's pretty simple so I'm not sure where to start trying to figure out what I've done wrong here.

Any ideas?

I was tasked to create an ATM mock program and my problem is overwriting the money and PIN variables with the information that the user will enter.

Here it is:

I have some data in Excel that's already laid out in groups (it's a Statement of Cash Flows from some accounting software) that I'm reading into Pandas with the read_excel() method. I want to create an index on the first 4 columns, but I can't figure out how to maintain the hierarchy of accounts. Here's what the hierarchy looks like:

When I try to either create a multi-index from the first 4 columns or if I do a ffill() on them, Pandas (effectively) does this...

The highlighted cells are incorrect for what I need and they should be blank/NaN to maintain the hierarchy. When the subcategory B2 on Level 2 starts, any categories from levels 3 and 4 should not be filled.

Here's what I'm trying to achieve:

Ultimately, these are Statements of Cash Flows from multiple years that have slightly different charts of accounts, so my hope was to import them into Pandas DataFrames and merge them so the accounts all line up across the whole time period... this is just the first step in the process. I could code this into a dictionary manually, but am wondering if it's possible more simply within Pandas?