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Here's one idea to help visualize the difference you are trying to show. Firstly, the country names on the x axis are likely to remain illegible however you try to label them. It might therefore be better to have the rank of the countries on the x axis.

Drawing a polygon around the points might make the point visually, but doesn't make much sense in statistical terms. What might be better here is to plot a regression with a separate line for each group. Since we are dealing with count data, we can use Poisson regression, and since we have a numeric rank on the x axis, it is possible to have lines going across your plot to show the regression.

Your problem seems simple enough to be solved by str.contains.

We can do groupby with rank create the category then pivot

The benefits of Eigen's vectorization are outweighed because you evaluate your expressions into temporary vectors. Allocating, deallocating, filling and reading these vectors has cost that seems significant. This is especially so because the expressions themselves are relatively simple (just a few scalar operations).

What usually helps here is aggregating into fewer expressions. For example line 3 and 4 can be collapsed into one: vidxt.array() = 2*3.14159265358979 * (vidxt.array() - quadrant.array()*0.5); (BTW: Note that that math.h contains a constant M_PI with pi in double precision).

Beyond that, Eigen expressions can be combined and reused. Something like this:

Pandas read_json method needs valid JSON str, path object or file-like object, but you put string. https://pandas.pydata.org/docs/reference/api/pandas.read_json.html

Try this:

The address you are using is not the router address as you assumed, but the address of the pair itself.

You can also easily check that via the graphql api. https://testnet-exchange-graph.elrond.com/graphql

With the following query:

It is overplotted for each row in your data. Set check_overlap = TRUE inside geom_text(), or use annotate instead. Or create a separate data frame for this layer with one row per label.

Thank you Indranil. Posting your suggestion as an answer to help other community members.

It's not recommended to use verify = False in your organization's environments because it will disable the SSL verification.

Sometimes, when you are behind a company proxy, it replaces the certificate chain with the ones of Proxy. Adding the certificates in cacert.pem used by certifi should solve the issue.

1. Find the path where cacert.pem is located:

   Install certifi, if you don't have. Command: pip install certifi

[This is a partial answer only, unfortunately.]

This is a Windows problem. I tried reproducing your results on macOS, and found a different, interesting behavior. I modified your code to distinguish between the C fwrite and the C++ std::fwrite, and I added code to write using the lower-level Posix write.

This is the C++ code: