es-stats | ElasticSearch cluster metrics - Graphite | Analytics library

Imagine you have a data set in three dimensions, x, y and z, and you want to show their relation. You could do this for example using a scatter plot in x and y and adding information about z with the help of a colormap:

But such a plot can be hard to read or even missleading, so I would like to use a 2d-histogram in x and y instead and weigh each data point by their z value:

However, as can be seen by the plot above, the magnitude of bin values can now be much higher than the maximum in z, which makes sense of course, as the bin values are usually the sums several z values.

So weighing by their z value is not enough, I also need to "normalize" each bin value by the number of data points within it. But as can be seen on the right plot above, for some reason, this doesn't seem to work. The color value range remains unchanged.

What am I doing wrong and is there a better approach to do this?

Code for reproduction (loosely based on this example):

I am currently to create a composite GitHub Actions that build a container from Java project with JIB and publish it automatically to a GitHub Packages and Maven Central.

But I got this error when I try to run it:

Using: Python in Google Collab Thanks in Advance: I have run this code on other data I have scraped FBREF, so I am unsure why it's happening now. The only difference is the way I scraped it. The first time I scraped it: url_link = 'https://fbref.com/en/comps/Big5/gca/players/Big-5-European-Leagues-Stats'

The second time I scraped it:

url = 'https://fbref.com/en/comps/22/stats/Major-League-Soccer-Stats'

html_content = requests.get(url).text.replace('', '')

df = pd.read_html(html_content)

I then convert the data from object to float so I can do a calculation, after I have pulled it into my dataframe:

dfstandard['90s'] = dfstandard['90s'].astype(float) dfstandard['Gls'] = dfstandard['Gls'].astype(float)

I look and it shows they are both floats:

10 90s 743 non-null float64

11 Gls 743 non-null float64

But when I run the code that as worked previously:

dfstandard['Gls'] = dfstandard['Gls'] / dfstandard['90s']

I get the error message "TypeError: '<' not supported between instances of 'str' and 'int'"

I am fairly new to scraping, I'm stuck and don't know what to do next.

The full error message is below:

I've been having a warning in the Ads App Content of Google Play saying that "We found ad SDKs in your app". After publishing many versions trying to resolve that, I discovered that the cause is these lines in my app-level build Gradle file:

I need to create an endpoint that returns the census data by state with the listing of cities, I currently get this using two endpoints.

Current response:

Custom query one: censusByState

I am testing a bulk insert in a mobgoDB database, in the @BeforeEach method I instantiate the database, in the@AfterEach I delete all documents created in the puzzles-today collection.

But the last one always fails, have random result, sometimes the test passes sometimes it displays this 367 or 366 or 364 or 364.

I added @RepeatedTest(4) To make sure it doesn't vary.

I'm trying to get a custom meta data field from wc_order. I have to clarify that I'm not a pro in php and I have tried many ways to get field, with:

• get_meta()
• get_meta_data()
• get_post_meta( $order_id )
• and so on...

But none of them have worked. I have this order object:

I need to create a method that reads a html file then display the number of word occurrence.

for example: String [] words = {"happy", "nice", "good"};

The word happy was used 7 times. The word nice was used 1 times. The word happy was used 2 times.

This is what I did:

I'am trying to use woocommerce_get_order_item_totals filter hook to add some extra information into the order totals (on orders and email notifications).