## How can I get the historical data of Number of transactions made by a wallet?

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## web development – What framework to use with excel for data frame in javascript like pandas?

I am trying to create a website that displays values from a .csv file that matches a certain criteria similar to how you can filter data from a dataframe in the pandas framework in python. I am not sure if there is anything similar in javascript. If not, what framework should I use to do this using python for web development?

## algorithms – What could be a good approach to compare environmental sensor data?

The premise in this case is the local proximity between the sensors. Furthermore let’s assume, that the data is provided by private Persons. One goal could be the detection of outliers, which are introduced intentionally or by mistake.

Any suggestions or papers?

## Squarespace returns no data using both curl and python

I am currently trying to build an integration between Quickbooks POS and squarespace. The official api documentation gives the following example:

``````curl "https://api.squarespace.com/1.0/commerce/products?cursor=abc"
-i
-H "Authorization: Bearer YOUR_API_KEY_OR_OAUTH_TOKEN"
-H "User-Agent: YOUR_CUSTOM_APP_DESCRIPTION"
``````

which returns with error 52 (no data) from. My attempts to do this with python also returns no data.

``````import requests
print("start")
"Authorization": "API KEY",
"User-Agent": "QBPOS integration"
}
square_api = requests.Session()
print(data)
print(data.text)
``````

and python-squarespace returns an error stating that squarespace thinks this request is bogus.
All of the response codes are <403>.
What could cause it to this, how can I fix this?

## encryption – Security of encrypted data and decrypting key

I am writing a python program in which I use encryption. The user can set the password and when it will be an input, the database will be decrypted. However, the function needs the decryption key to decrypt. So I thought about hiding that key somewhere(encryption and decryption key will be generated dynamically which means that the user on new device will have another decryption key.). I have no idea where I could hide it, so program could use it, but the user could not crack it.

## java – Red Hat Decision Manager – Como criar um data set no Decision Central do tipo bean?

Estou tentando criar um data set do tipo java bean no Decision Central para armazenar os dados da classe do meu projeto:

E nas configurações do meu projeto consta a classe:

Mas recebo a seguinte mensagem:

Esta é a minha classe java:

Alguém que já utilizou o Decision Manager da Red Hat pode me ajudar como posso resolver isso e oque estou fazendo de errado?

## Reseller Hosting in Europe that offers a Data Processing Agreement

Since a DPA with the Reseller Provider will be necessary to offer web hosting in Europe and comply with GDPR, I am looking for Europe based … | Read the rest of https://www.webhostingtalk.com/showthread.php?t=1818375&goto=newpost

## facttable – Distinguishing between fact and dimension tables in data warehouse

Is it true that facts in a fact table of a data warehouse always have a relation to time? I.e. is it true that a fact must always be assignable to a specific point in time?

If this is correct, can we conclude that dimension elements (except for maybe a time-dimension) do not need to be assignable to a specific point in time?

## data mining – PageRank vector

I computed the PageRank vector for the example given in https://en.wikipedia.org/wiki/PageRank (where the picture shows that node B ends up with a score of 38.4, node C with 34.3, node D with 3.9). I implemented the PageRank algorithm, but my numbers are slightly different: 39.8 for node B, and 36.1 for node C, 3.5 for node D, etc). I was wondering if anyone could simulate and obtain the same results they have. My question is what algorithm was used to obtain their numbers.

My algorithm is as follows. Starting with the uniform distribution $$r$$, I did power iteration using the equation $$r = Ar$$, where $$A = 0.85 M + 0.15 J$$, $$M$$ is the transition matrix of the Web graph given in the example, and $$J$$ is the matrix whose every entry is $$1/N$$ ($$N=11$$ is the number of nodes).

## database design – best data format and storage thinking for new app

I’ll start with familiar apology for what might be a long-ish question, and possibly for not being the best forum .. but not for lack of looking …

I wonder if I might get an opinion from some clever folk about how best to think about the data structure of a web app that I have prototyped.

It’s a reporting app where any user might generate say 5 – 50 reports within one project, and may have any number of projects over membership lifetime, but let’s guess at less than a hundred.

Each report has loosely 100 – 5000 line items, which are very simple, but grouped into a hierarchy that looks something like:
report > level > section > subsection > lineItem

The app itself is ‘relatively’ simple and allows the user to navigate around the report between various datagrids, editing certain line items or batch editing sections of line items etc.

I’m very familiar with php/mysql/laravel, so this is what I’ve used to prototype. However, in order to get this up and running, I have one JSON field in mySQL that basically holds the entire report. And the format is hierarchical, so {report: levels:(sections: lineItems: ()) ….}
(that’s probably not the best way of illustrating that, but you get the idea)

In the browser, the app simply grabs ALL this data, and then (using Vue) can zip around various custom grids doing whatver they need to do. I have a crude auto-saving thing that measures activity and then saves the whole darn lot back to the database (XHR in the background) to be overridden. Could be – say – 300kb a go.

The problem I have is that this works very well from a user-perspective, it’s obviously very zippy, no page reloads, and the client is very happy with the prototype. (okay, so not the worst problem to have)

However, I know very well that this isn’t great, and there must be a better (more accepted) methodology for structuring this.

But, if I go down a more ‘traditional’ route, and have a relational DB with a ‘line_items’ table, with each LI belonging to various things above it, this will quickly run to millions of lines … and there’s no massive relational benefit for linking the data from different reports, it’s all quite self-contained really. Also the DB will then be plucking thousands of lineItems from an enormous table full of every users’ data … just doesn’t feel right.

So I’ve thought about NoSQL, as it might appear that each report is much it’s own ‘document’. Howver, I don’t think this plays too well with Laravel, and I would still have other questions, such as: is it better to flatten this out into a great big list of lineItems, and store the ‘belonging’ of upper levels within, e.g. lineItem-{section: “foo”, subsection: “bar”, someData:”baz”}

One of the beneficial side-effects I have at the moment is that I don’t actually concern myself in any way with unique IDs or -in fact – any keys at all, I just grab the whole JSON object, the user manipulates it ‘as is’ and then it’s all saved back. This is quite handy because the data orginates from CSV, so it’s a straight conversion to JSON. However, it would obviously be a more efficient system to only save amended records ad-hoc.

I’ve gone on long enough, so sorry for rambling post. If anyone has the time for just a couple of thoughts or links or anything, I’d be very interested and grateful.