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I'm doing work for school and my professor specifically asks for a dynamic array created without using a vector. The work I'm doing is a game that is played on an island and I need to use the dynamic array to create the island.

The island is a class that consists of an array of cells (which is another class). When I'm trying to insert the cells into the island array it throws a segmentation fault.

The problem is in this function:

I am trying to understand how specific script (fade function) works in PICO8:

I'm learing flutter and I tried to recreate this from fireship.io.

I copied the code and I get this Error:

I am trying to get only the price of the coin but instead, I am getting the whole HTML because of the body. I cannot find any documentation or usage for the request package so I needed to ask here.

I am trying to find the class="price" which only shows the price.

Is there a way to search based on class or the XPath of the URL or a way to cut everything out except for the class="price" section?

Would appreciate a help with selenium.

Trying to fill in google form for several entries, so that I need to input the feirst row a df, than click "Submit" a new form and run again for the second form and to the n-th row.

Got stuck with NoSuchFrameException: Unable to locate frame with index error after the first entry. Read on Selenium docs that one can locate a window's frame in console and it gives me nothing (F12 --> find frame (any combination tried) --> no matches). No such thing in google form (or my search is wrong hands down)

Haven't got anything on the issue so tried frame(0) - no luck.

Any tips would be appreciated. The whole code is below

I have a .flr animation of a minion. Is it possible to change colors of his body, pants, eyes, etc dynamicaly and separately in flutter app?

PS Minion is just an example i found on rive.app .There will be another character with lots of different parts.

PPS Maybe there is a better way to make a simple animated character in flutter? For now, i have a stack with positioned colorfilterd images, but i guess it should be easier with rive.

I am using a stack widget to display animations inside a screen. I am using only 70% of the screen and the rest I have kept it unused. I want to display something else there. When I am wrapping my stack widget inside a column it is giving the error: Bottom Overflowed by Infinite Pixels.

I tried adding a custom height using Container and SizedBox. Also tried using SingleChildScrollView. Still the same error.

Code:

I'm using stripe payment gateway in my app everything works fine when i enter card details after that it redirect to the OTP page after enter otp and submit it throws this error

This problem occurs only in live mode, in test mode debit card won't ask for OTP

I need help with the specific code I will paste below. I am using the Ames Housing data set collected by Dean De Cock. I am using a Python notebook and editing thru Anaconda's Jupyter Lab 2.1.5. The code below is supposed to replace all np.nan or "None" values. For some reason, after repeatedly calling a hand-made function inside a for loop, the columns of the resulting data frame get swapped around.

Note: I am aware I could do this with an "imputer." I plan to select numeric and object type features, impute them separately then put them back together. As a side-note, is there any way I can do that while having the details I output manually using text displayed or otherwise verified?

In the cell in question, the flow is:

1. Get and assign the number of data points in the data frame df_train.
2. Get and assign a series that lists the count of null values in df_train. The syntax is sr_null_counts = df_train.isnull().sum().
3. Create an empty list to which names of features that have 5% of their values equal to null are appended. They will be dropped later, outside the for loop. I thought at first that this was the problem since the command to drop the columns of df_train in-place used to be within the for-loop.
4. Repeatedly call a hand-made function to impute columns with null values not exceeding 5% of the row count for df_train.

I used a function that has a for-loop and nested try-except statements to:

1. Accept a series and, optionally, the series' name when it was a column in a dataframe. It assigns a copy of the passed series to a local variable.
2. In the exact order, (a) try to replace all null (NaN or None) values with the mean of the passed series. (b) If that fails, try to replace all null values with the median of the series. (c) If even that fails, replace all null values with the mode of the series.
3. Return the edited copy of the series with all null values replaced. It should also print out strings that tell me what feature was modified and what summary statistic was used to replace/impute the missing values.

The final line is to drop all the columns marked as having more than 5% missing values.

Here is the full code:

The full data-set was loaded thru df_housing = pd.read_csv(sep = '\t', filepath_or_buffer = "AmesHousing.tsv").