scat | SCAT : Signaling Collection and Analysis Tool

I scraped the link and address of each property on page 1 of a real estate website into a list. I then convert this list of lists listing_details into pandas dataframe by appending info of each property as a row (20 rows in total). My code is as follows:

I am trying to plot the following values using a moving average approach but I am having some issues getting the right facecolor.

In a Python/matplotlib program I am trying to alter the size of the marker in the animated plot to show the magnitude of an array with python.

In this code if the marker moves to x[i],y[i] the size of the marker should be s[i]. Which means the size of the marker at point x[i],y[i] should show the value of s[i] at that point. Any suggestion on how to animate such a plot would be appreciated.

Why are the y-values in my Seaborn barplot not summing correctly? The table below has the expected values, and you can see in the plot below that they do not match. Code is at the end. This is not a duplicate of Seaborn bar plot y axis has different values than expected because the issue there was related to datetime formatting.

Is there any other way to use a table name as a function parameter in PostgreSQL than with Execute?

The problem is the existing statement (taken from a report in openMaint) is long and has a lot of existing variables.

I want to be able to make a general function that can be used for any similar report where all I need to do is pass the different table parameters instead of making a new function for each report. However things will get exceedingly complicated using Execute. Does anyone have any alternatives for me?

I am trying to use the $names operator on my OutVals (outliers) to find the class these outliers are associated to and then put the outliers and their class name inside a data frame so I can see clearly from which class these outliers came from.

However, when trying to implement this, my class names return as "1", "2" etc... and not "Van", "Bus etc.. as it is in the dataset.

Have I missed something or am I approaching this completely wrong? The goal is to get the outliers in the data and place them inside a table which shows from which class the outliers came from

Any help would be appreciated

I have shown my data frame as well as my reproduceable code below

I have a matplotlib plot with a slider and am interested in setting the colors of the points plotted as the slider gets dragged one way or the other. I know you can set the colors of points with set_array() but so far have had luck passing set_array() only 1D arrays of floats. When I pass set_array() an array of strings corresponding to matplotlib colors, I receive the error and traceback below.

Here are some relevant code snippets, with dummy info. for ease of assessment. With the two commented-out lines in update(val), the error below appears. Un-commenting them, so that set_array() gets a float, fixes the issue, but then I lose ability to control the colors with any precision. (For instance, changing 'g' to 'c' makes no perceptible difference in the colors.)

I am trying to remove outliers from my dataset but I doesn't seem to be working. I have tested this technique on a vector of numbers and it worked. However, when trying to apply it to a dataset coming from a csv file. It doesn't seem to do anything. Am I doing something wrong or am I approaching outlier removal completely wrong?

• Original dataset had "Sample" number as the first column in the csv file and "Class" (van, car, etc..) as the final column and so I removed these columns from the dataset

After outlier removal (not sure if correct)

Testing on CSV File data

If I'm doing a scatter plot with the points coloured based on magnitude, can I specify the color levels like in contour & contourf?

For example I do this: