financial | dependency TypeScript/JavaScript financial library
kandi X-RAY | financial Summary
kandi X-RAY | financial Summary
A Zero-Dependency TypeScript / JavaScript financial utility library inspired by numpy-financial that can be used on Node.js, Deno and the browser. It does support the same functionality offered by numpy-financial but it only supports scalar JavaScript number values (NO numpy-like array values) and it does NOT support arbitrary-precision signed decimal numbers (such as decimal.js, big.js or bignumber.js). API DOCS : financialjs.netlify.app.
Support
Quality
Security
License
Reuse
Top functions reviewed by kandi - BETA
Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of financial
financial Key Features
financial Examples and Code Snippets
import React, { useEffect, useState } from "react";
import { Helmet } from "react-helmet";
export default function App() {
const [pageTitle, setPageTitle] = useState("My Financial Right Hand");
return (
<>
{p
<
foo
>
var selectedYearMonth = luxon.DateTime.now();
$(document).ready(function() {
// the Luxon date object for the selected year-m
const response = await Todo.findOneAndUpdate(
{ _id: "a1s2d3f4f4d3s2a1s2d3f4" },
{ title: "Get Groceries" },
{ new: true }
);
// response will have updated document
// We won't need this here. This is just to tell you how to get the
[{
"speaker": 0,
"transctips": "hi thank you for calling bright house financial my name is problem can I have"
}, {
"speaker": 1,
"transctips": "yeah hi my name is Richard Caillaux and I have a contract with bright house for a % HESITATION
const result={records:[{keys:["names","value","country","questions"],length:4,_fields:["123ilSE",["Longitude:5.1193","Latitude:52.3246","Agreeableness:0.147083333333333","Openness:0.211041666666667","Neuroticism:0.168833333333333","Extrave
const request = require("request");
const getData = function() {
return new Promise((resolve, reject) => {
let options = {
method: 'GET',
url : "https://en.wikipedia.org/w/api.php?format=json&origin=*&actio
import 'package:flutter/material.dart';
void main() {
runApp(MyApp());
}
class MyApp extends StatefulWidget {
@override
MyAppState createState() => MyAppState();
}
class MyAppState extends State {
var txtField = TextEditingCo
$(document).ready(function() {
var table = $('#example').DataTable( {
initComplete: function () {
this.api().columns().every( function () {
//for each column I add bootstrap selectpicker to the footer
var column = this;
var select = $('
\documentclass{article}
\usepackage{geometry}
\usepackage{longtable}
\begin{document}
% Please add the following required packages to your document preamble:
% \usepackage{longtable}
% Note: It may be necessary to compile the document
$(".letterInBar").click(function() {
let letter = $(this).html();
let matchText = function() {
return $(this).text() === letter;
}
$('html, body').animate({
scrollTop: $(".letter").filter(matchText).offset() ?
Community Discussions
Trending Discussions on financial
QUESTION
I'm using bert pre-trained model for question and answering. It's returning correct result but with lot of spaces between the text
The code is below :
...ANSWER
Answered 2021-Jun-15 at 17:14You can just use the tokenizer decode function:
QUESTION
I have a dataset with the name of Danish ministers and their position from 1990 to 2020 (data comes from dataset called WhoGovern; https://politicscentre.nuffield.ox.ac.uk/whogov-dataset/). The dataset consists of the ministers name
, the ministers position
, the prestige
of that position, and the year
in which the minister had that given position.
My problem is that some ministers are counted twice in the same year (i.e., the rows aren't unique in terms of name
and year
). See the example in the picture below, where "Bertel Haarder" was both Minister of Health and Minister of Interior Affairs in 2010 and 2021.
I want to create a dataset, where all the rows are unique combinations of name
and year
. However, I do not want to remove any information from the dataset. Instead, I want to use the information in the prestige
column to combine the duplicated rows into one. The observations with the highest prestige should be the main observations, where the other information should be added in a new column, e.g., position2
and prestige2
. In the example with Bertel Haarder the data should look like this:
(PS: Sorry for bad presenting of the tables, but didn't know how to create a nice looking table...)
Here's the dataset for creating a reproducible example with observations from 2010-2020:
...ANSWER
Answered 2021-Jun-08 at 14:04Reshape the data to wide format twice, once for position
and the other for prestige_1
, and join the two results.
QUESTION
Traceback (most recent call last):
File "", line 335, in
+ my_value_a
TypeError: can only concatenate str (not "NoneType") to str
...ANSWER
Answered 2021-Jun-15 at 11:26So if the key for os.getenv()
is invalid, it returns the default values that you pass as the second parameter. If you don't set this default value, it returns a None
. Possible Fixes:
QUESTION
I'm looking into using QuestDB for a large amount of financial trade data.
I have read and understood https://questdb.io/docs/guides/importing-data but my case is slightly different.
- I have trade data for multiple instruments.
- For each instrument, the microsecond-timestamped data spans several years.
- The data for each instrument is in a separate CSV file.
My main use case is to query for globally time-ordered sequences of trades for arbitrary subsets of instruments. For clarity, the results of a query would look like
...ANSWER
Answered 2021-Jun-13 at 22:11As of 6.0 you can simply append the CSVs to same table one by one given the table has designated timestamp and partitioned it will work.
If your CSVs are huge I think batching them in transactions with few million rows will be better than offloading billions at once.
Depending of how much data you have and your box memory you need to partition in a way that single partition fits memory several times. So you choose if you want daily or monthly partitions.
Once you decide with partitioning you can speed up the upload if you able to upload day by day batches (or month by month) from all CSVs.
You will not need to rebuild the table every time you add an instrument, table will be rewritten automatically partition by partition when you insert records out of order.
QUESTION
So, I'm a very amateur python programmer but hope all I'll explain makes sense.
I want to scrape a type of Financial document called "10-K". I'm just interested in a little part of the whole document. An example of the URL I try to scrape is: https://www.sec.gov/Archives/edgar/data/320193/0000320193-20-000096.txt
Now, if I download this document as a .txt, It "only" weights 12mb. So for my ignorance doesn't make much sense this takes 1-2 min to .read()
(even I got a decent PC).
The original code I was using:
...ANSWER
Answered 2021-Jun-13 at 18:07The time it takes to read a document over the internet is really not related to the speed of your computer, at least in most cases. The most important determinant is the speed of your internet connection. Another important determinant is the speed with which the remote server responds to your request, which will depend in part on how many other requests the remote server is currently trying to handle.
It's also possible that the slow-down is not due to either of the above causes, but rather to measures taken by the remote server to limit scraping or to avoid congestion. It's very common for servers to deliberately reduce responsiveness to clients which make frequent requests, or even to deny the requests entirely. Or to reduce the speed of data transmission to everyone, which is another way of controlling server load. In that case, there's not much you're going to be able to do to speed up reading the requests.
From my machine, it takes a bit under 30 seconds to download the 12MB document. Since I'm in Perú it's possible that the speed of the internet connection is a factor, but I suspect that it's not the only issue. However, the data transmission does start reasonably quickly.
If the problem were related to the speed of data transfer between your machine and the server, you could speed things up by using a streaming parser (a phrase you can search for). A streaming parser reads its input in small chunks and assembles them on the fly into tokens, which is basically what you are trying to do. But the streaming parser will deal transparently with the most difficult part, which is to avoid tokens being split between two chunks. However, the nature of the SEC document, which taken as a whole is not very pure HTML, might make it difficult to use standard tools.
Since the part of the document you want to analyse is well past the middle, at least in the example you presented, you won't be able to reduce the download time by much. But that might still be worthwhile.
The basic approach you describe is workable, but you'll need to change it a bit in order to cope with the search strings being split between chunks, as you noted. The basic idea is to append successive chunks until you find the string, rather than just looking at them one at a time.
I'd suggest first identifying the entire document and then deciding whether it's the document you want. That reduces the search issue to a single string, the document terminator (\n\n
; the newlines are added to reduce the possibility of false matches).
Here's a very crude implementation, which I suggest you take as an example rather than just copying it into your program. The function docs
yields successive complete documents from a url; the caller can use that to select the one they want. (In the sample code, the first matching document is used, although there are actually two matches in the complete file. If you want all matches, then you will have to read the entire input, in which case you won't have any speed-up at all, although you might still have some savings from not having to parse everything.)
QUESTION
I have a column in my table called Additional_comments. This column is a free text field where people pretty much write sentences, so it looks like this:
Additional_comments The client is in need of basic services, housing, and employment help; client is in need of financial help. Client is in the senior age-group.I want the sentence to appear like this - "The client is in need of basic services, housing, and employment help; client is in need of financial help. Client is in the senior age-group."
I would appreciate if anyone can help me with this query to figure out how I can add double quotes around the sentence. Thank you
...ANSWER
Answered 2021-Jun-10 at 20:10Just concatenate the quotes to your column
QUESTION
I applied case_when
to a text data of thousands of rows to detect strings with multiple conditions and replace them but got a wrong result because case_when
doesn't execute the remaining conditions once a condition is met. I have seen a solution in How to detect more than one regex in a case_when statement, but the solution does not have multiplicity of multiple conditions such as in my data.
Any alternative to case_when
will be is appreciated.
This is the dummy data:
...ANSWER
Answered 2021-Jan-22 at 06:51You may use case_when
with grepl
and a regex alternation:
QUESTION
ANSWER
Answered 2021-Jun-09 at 03:56I was able to resolve this issue by putting the paragraph contents inside a wordwrap function in php. Example: wordwrap('content string',100)
QUESTION
I need help to write a SQL logic in bigquery to replace a value in one column based on a condition as below
FINANCIAL YEAR --> JUL to JUN
How can I make it more dynamic so it rolls over next year
...ANSWER
Answered 2021-Jun-09 at 00:40If version = "ACT" an DATE is not current year i.e 07-2020 to 06-2021 then replace ACT with ACTA
You want a case
expression:
QUESTION
I have this dataset of product sales:
...ANSWER
Answered 2021-Jun-08 at 20:04Try this:
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install financial
Support
Reuse Trending Solutions
Find, review, and download reusable Libraries, Code Snippets, Cloud APIs from over 650 million Knowledge Items
Find more librariesStay Updated
Subscribe to our newsletter for trending solutions and developer bootcamps
Share this Page