tim | A tiny , secure JavaScript micro-templating script | Runtime Evironment library

I have a ListBox1 in UserForm1. When I send a multi-row array to a .List, everything works. But when I send only a one-row array, the values in the ListBox1 are arranged one below the other in first column. Independent of use Application.Transpose.

I tried to write a condition and a for loop, but it doesn't work. Run-time error 381 Could not set the List property. Invalid property array index. .AddItem cannot be used because there are more than 10 columns

Do you have any other solution?

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I'm trying to make a script that loops through files and vlookups the name into an excel sheet.

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When i call my funtion with a startingAngle=0 it produce a good shape with the correct size. Example:

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I am making a ninja game in which a ninja has to dodge obstacle by jumping(pressing spacebar), but the jump animation is too fast and the ninja is not able to jump beyond the obstacles. I want that it jumps a little slowly so as to make it jump beyond the obstacles, and goes till the 394 y value even if the key is released after pressing and then come down.

Note that I am a beginner.

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I am making a game in which a ninja has to dodge obstacles coming in front of him, the obstacles are chosen randomly by the computer using random.randint() in the method choose() in obstacle class. The problem is that the choose() method chooses a random number in every iteration of the main loop. I want that if the x position of the obstacle is 0 then only it should choose another random number.

Remember that I am a beginner

Here is my code:

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I would need some help. I can only use vanila css, html , javascript

I want to create Buttons that show/hide certain rows in a table I created with with HTML. If i give every row a class, how can I attach the show/hiding of certain tr to a button? I tried the other solutions on similar questions but couldnt figure it out.

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Pandas Series.value_counts() has a dropna parameter but DataFrame.value_counts() not. That is my problem. But I am sure there is a reason and an alternative solution for it.

The usecase is that I want to count pattern (value combinations of specific columns) in my DataFrame. For that usecase I want to count None/NaN, too.

This is the data with 8 rows.

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I've joined 2 tables and extract the top 2 vendors by country (code at the bottom of this post and link) with the help of Tim Biegeleisen on this link , now I would like to go 1 step further and group the top 2 vendors by year by country.

The original ORDERS table looks like this :

country_name date_local vendor_id gmv_local is_successful_order Taiwan 2012-10-02 2870 559.6 true Taiwan 2012-10-02 3812 573.5 true Singapore 2012-10-02 941 778.6 true Singapore 2014-10-02 13 120.6 true Bangkok 2014-10-02 227 563.6 true

This table is merged with the vendor table

id vendor_name country_name 2870 C House Taiwan 941 A House Singapore 227 9 House Bangkok

I would like to extract the year from the "date_local" column into timestamp format, where the items in the Year column will look like "2012-01-01T00:00:00" from the original date format of "2012-10-02"

Then I would like to list out the top 2 vendors of by year of each country in total revenue

The resulting table should look like this:

year country_name vendor_name total_gmv 2012-01-01T00:00:00 Singapore A House 1119.76 2012-01-01T00:00:00 Singapore B House 819.63 2012-01-01T00:00:00 Taiwan C House 119.6 2012-01-01T00:00:00 Taiwan D House 119.6 2012-01-01T00:00:00 Bangkok 9 House 119.6 2014-01-01T00:00:00 Singapore A House 2119.76 2014-01-01T00:00:00 Singapore B House 1819.63 2014-01-01T00:00:00 Taiwan C House 1019.6 2014-01-01T00:00:00 Taiwan D House 919.6 2014-01-01T00:00:00 Bangkok 9 House 189.6

printscreen of target results

I know I need to add one more partition of the Extract( year FROM date_local) as year and set it to the correct GETDATE() timestamp format to add the extra layer needed, but I don't know how to add it to the code

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For context of the code here. I have combined several of these 96 cell ranges into one larger range composed on n smaller ranges. Reason for doing this is to make it (more) scalable.

I have a range of data I want to break them up into n ranges/chunks and run my function on each (function below, shout out to @Tim Williams for the function) and combine the outputs all into a column. One solution I don't really like but I could do is to simply run the function on each n chunks/ranges and manually combine them, however, that's not really optimal for what I need. I am still pretty new to VBA, any ideas would be much appreciated!

The function I am using is as follows. Note my comment within the function:

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