The results of stats calls to IEX Cloud make no sense.
Docs are at https://iexcloud.io/docs/api/#stats-basic but they don't go into the details. Just saying a field exists seems to be enough for them.
Here is a result for today for Agilent from an API call:
{"companyName":"Agilent Technologies Inc.","marketcap":48702022828,"week52high":179.35,"week52low":104.59,"week52highSplitAdjustOnly":179.57,"week52lowSplitAdjustOnly":105.19,"week52change":0.4686617632157193,"sharesOutstanding":302722668,"float":0,"avg10Volume":1289493,"avg30Volume":1291085,"day200MovingAvg":152.69,"day50MovingAvg":156.41,"employees":16400,"ttmEPS":3.21,"ttmDividendRate":0.7744734957186514,"dividendYield":0.004813982444795198,"nextDividendDate":"","exDividendDate":"2021-10-04","nextEarningsDate":"2021-11-22","peRatio":49.19396245236364,"beta":0.9917301080890041,"maxChangePercent":6.000809392433486,"year5ChangePercent":2.617394432702253,"year2ChangePercent":1.1149775855495814,"year1ChangePercent":0.4686617632157193,"ytdChangePercent":0.3655365001761244,"month6ChangePercent":0.2405176122966075,"month3ChangePercent":0.011620302832134222,"month1ChangePercent":0.0709625882039675,"day30ChangePercent":0.05432859296153092,"day5ChangePercent":0.028578735374976016}
For example "year5ChangePercent" with value 2.617. Agilent is up roughly 400% in the last 5 years, from about $44 to $160. So how on earth did they come up with 2.617?
Related
I need to enter the below data in Redis:
Atlanta_96_Bronze Ana_Moser Ida_Alvares Ana_Paula Hilma_Caldeira Leila_Barros Virna_Dias Marcia_Fu Ericleia_Bodziak Ana_Flavia_Sanglard Fernanda_Venturini Fofao_Helia_Souza Sandra_Suruagy
Sidney_00_Bronze Elisangela_Oliveira Erika_Coimbra Fofao_Helia_Souza Janina_Conceicao Karin_Rodrigues Katia_Lopes Kely_Fraga Leila_Barros Raquel_Silva Ricarda_Lima Virna_Dias Walewska_Oliveira
Pequim_08_Gold Marianne_Steinbrecher Fofao_Helia_Souza Paula_Pequeno Walewska_Oliveira Thaisa_Menezes Valeska_Menezes Welissa_Gonzaga Fabiana_Oliveira Fabiana_Claudino Sheilla_Castro Jaqueline_Carvalho Carolina_Albuquerque
Londres_12_Gold Fabiana_Claudino Dani_Lins Paula_Pequeno Adenizia_Silva Thaisa_Menezes Jaqueline_Carvalho Fernanda_Ferreira Tandara_Caixeta Natalia_Pereira Sheilla_Castro Fabiana_Oliveira Fernanda_Garay
And then perform the following queries:
Which players won gold and silver medals?
Which players won two gold medals?
Which players only won medal in '96?
Which players were in the 96, 00 and 08 Olympics?
Which players were only in the 12 olympics?
But I never touched Redis, I came from a relational world, I need help.
Redis doesn't really seem like the right tool for the job as you've described it, as Redis is more of a cache than a database. There's no concept of running a "query" in Redis.
If you must use Redis, I would recommend storing the data in multiple sets to facilitate getting to the answers you need.
You might make a set for each type of medal, for example (a set of gold medalists, a set of silver medalists, and a set of bronze medalists). Then you could ask for the union of the gold and silver sets (Redis's SUNION operator) to get the answer to your first question.
You might also make a set for each year, so that you could retrieve information by year (for your last three questions).
In some cases, there may be no way around doing some coding to refine the results to give you exactly the answers you need.
My friends,
In the past couple of years I read a lot about AI with JS and some libraries like TensorFlow. I have great interest in the subject but never used it on a serious project. However, after struggling a lot with linear regression to solve an optimization problem I have, I think that finally I will get much better results, with greater performance, using AI. I work for 12 years with web development and lots of server side, but never worked with any AI library, so please, have a little patience with me if I say something stupid!
My problem is this: every user that visits our platform (website) we save the Hour, Day of the week, if the device requesting the page was a smartphone or computer... and such of the FIRST access the user made. If the user keeps visiting other pages, we dont care, we only save the data of the FIRST visit. And if the user anytime does something that we consider a conversion, we assign that conversion to the record of the first access that user made. So we have almost 3 millions of lines like this:
SESSION HOUR DAY_WEEK DEVICE CONVERSION
9847 7 MONDAY SMARTPHONE NO
2233 13 TUESDAY COMPUTER YES
5543 19 SUNDAY COMPUTER YES
3721 8 FRIDAY SMARTPHONE NO
1849 12 SUNDAY COMPUTER NO
6382 0 MONDAY SMARTPHONE YES
What I would like to do is this: next time a user visits our platform, we wanna know the probability of that user making a conversion. If a user access now, our website, depending on their device, day of week, hour... we wanna know the probability of that user making a future conversion. With that, we can show very specific messages to the user while he is using our platform and a different price model according to that probability.
CURRENTLY we are using a liner regression, and it predicts if the user will make a conversion with an accuracy of around 30%. It's pretty low but so far, it's the best we got it, and this linear regression generates almost 18% increase in conversions when we use it to show specific messages/prices to that specific user compaired to when we dont use it. SO, with a 30% accuracy our linear regression already provides 18% better conversions (and with that, higher revenues and so on).
In case you are curious, our linear regression model works like this: we generate a linear equation to every first user access on our system with variables that our system tries to find in order to minimize error sqr(expected value - value). Using the data above, our model would generate these equations below (SUNDAY = 0, MONDAY = 1...COMPUTER = 0, SMARTPHONE = 1... CONVERSION YES = 1 and NO = 0)
A*7 + B*1 + C*1 = 0
A*13 + B*2 + C*0 = 1
A*19 + B*0 + C*0 = 1
A*8 + B*6 + C*1 = 0
A*12 + B*0 + C*1 = 0
A*0 + B*1 + C*0 = 1
So, our system find the best A, B and C that generates the minimizes error. How can we do that with AI? If possible, it would be nice if we could use TensorFlow or anything with JS! I know there are several AI models, and I have no idea which one would best fit what we need!
I am very new to this and would like to know how to start gathering statistics on my followers as I am currently growing my follower base. I am subscribed to several statistic tracking apps but none are really good.
I wish to track things such as:
Follower count by Location
Frequency distribution of followers and tags
Follower growth rate by Hour, Day, week, etc..
Follower Loss
Is this at all possible using APIs? Can anyone tell me how to get started?
There is no direct API call to get follower growth by hour and week, you have to get all followers every hour and store it in database and analyze for growth or loss every hour compared to previous hour and save it on the server.
You cannot get location of followers from API, you can may be estimate the location by checking for location in bio or analyzing all user posts and finding most posted location (this is expensive on API side and will have to make a lot of API calls to get analyze)
Yes, all this is possible to do using API, but it is a lot of work on backend, so if some service does this, it will cost you money cause they cannot do it for free, my guess is that you have checked all free or cheap services and they cannot do all this analysis for cheap.
You can get a broad breakdown of follower count in Google Sheets. This doesn't require API access so you won't get all of the data you are looking for, such as GEO. But, if you would like to see your follower increase by the hour, do this -
Open up a new Google Sheet
Go to Tools > Script Editor
Name your script 'IGFollowers'
In the code box, copy and paste this code below, but make sure to write this replace 'AccountName' with your username
var sheetName = "IGFollowers";
var instagramAccountName = "AccountName";
function insertFollowerCount() {
var ss = SpreadsheetApp.getActiveSpreadsheet();
var sheet = ss.getSheetByName("IGFollowers");
sheet.appendRow([Utilities.formatDate(new Date(), "PST", "yyyy-MM-dd"),
Utilities.formatDate(new Date(), "PST", "hh:mm"),
getInstagramFollowerCount(this.instagramAccountName)]);
};
function getInstagramFollowerCount(username) {
var url = "https://www.instagram.com/" + username + "/?__a=1";
var response = UrlFetchApp.fetch(url).getContentText();
return JSON.parse(response).user.followed_by.count;
}
Go to Run > InsertFollowerCount
NOTE: You may need to do a bit of formatting with the main Google Sheet, but this will get you some very long columns showing an increase in followers by the hour.
I need to get the available options for a certain question in Watson conversation api?
For example I have a conversation app and in some cases Y need to give the users a list to select an option from it.
So I am searching for a way to get the available reply options for a certain question.
I can't answer to the NPM part, but you can get a list of the top 10 possible answers by setting alternate_intents to true. For example.
{
"context":{
"conversation_id":"cbbea7b5-6971-4437-99e0-a82927607079",
"system":{
"dialog_stack":["root"
],
"dialog_turn_counter":1,
"dialog_request_counter":1
}
},
"alternate_intents":true,
"input":{
"text":"Is it hot outside?"
}
}
This will return at most the top ten answers. If there is a limited number of intents it will only show them.
Part of your JSON response will have something like this:
"intents":[{
"intent":"temperature",
"confidence":0.9822100598134365
},
{
"intent":"conditions",
"confidence":0.017789940186563623
}
This won't get you the output text though from the node. So you will need to have your answer store elsewhere to cross reference.
Also be aware that just because it is in the list, doesn't mean it's a valid answer to give the end user. The confidence level needs to be taken into account.
The confidence level also does not work like a normal confidence. You need to determine your upper and lower bounds. I detail this briefly here.
Unlike earlier versions of WEA, the confidence is relative to the
number of intents you have. So the quickest way to find the lowest
confidence is to send a really ambiguous word.
These are the results I get for determining temperature or conditions.
treehouse = conditions / 0.5940327076534431
goldfish = conditions / 0.5940327076534431
music = conditions / 0.5940327076534431
See a pattern?🙂 So the low confidence level I will set at 0.6. Next
is to determine the higher confidence range. You can do this by mixing
intents within the same question text. It may take a few goes to get a
reasonable result.
These are results from trying this (C = Conditions, T = Temperature).
hot rain = T/0.7710267712183176, C/0.22897322878168241
windy desert = C/0.8597747113239446, T/0.14022528867605547
ice wind = C/0.5940327076534431, T/0.405967292346557
I purposely left out high confidence ones. In this I am going to go
with 0.8 as the high confidence level.
I am building a web app, which uses Yahoo Weather API to provide weather information, based on a ZIP code, provided by the users.
I know that in order to obtain this data for certain number of days I have to add it as a parameter in my request, like so:
http://weather.yahooapis.com/forecastrss?p=33035&u=c&d=3
Which gives this result:
<channel>
....
<yweather:location city="Homestead" region="FL" country="US"/>
<yweather:units temperature="C" distance="km" pressure="mb" speed="km/h"/>
<yweather:wind chill="19" direction="90" speed="11.27"/>
<yweather:atmosphere humidity="78" visibility="16.09" pressure="1021" rising="1"/>
<yweather:astronomy sunrise="7:12 am" sunset="7:36 pm"/>
...
<item>
...
<yweather:forecast day="Wed" date="2 Apr 2014" low="19" high="28" text="Mostly Sunny" code="34"/>
<yweather:forecast day="Thu" date="3 Apr 2014" low="21" high="29" text="Partly Cloudy" code="30"/>
<yweather:forecast day="Fri" date="4 Apr 2014" low="20" high="28" text="Partly Cloudy" code="30"/>
<guid isPermaLink="false">USFL0208_2014_04_04_7_00_EDT</guid>
</item>
</channel>
However I need to be able to get the humidity level for EVERY day in the forecast and not just the current one. I've tried to find solution here and also read the Yahoo API documentation, but it's really a short one.
I've also tried http://www.myweather2.com/ and http://developer.worldweatheronline.com/, but they have the same issue with humidity - it's shown only for the current day and stripped from the whole forecast.
I'll keep trying with other free Weather APIs, but if you can help here I'd be very grateful.
I've spent some time researching for better APIs than the Yahoo! Weather API and I found something, that works for me, so I've decided to share the info, in case anyone else bump into this some day.
Version 2 of the Forecast API looks like a nice solution, because it provides detailed information, more specifically the humidity index for each day in the forecast, which was what I was looking for in the first place.
There are also number of libraries for this API (languages include PHP, Node.js, Python, Perl and others).
It works with longitude & latitude as in this example
https://api.forecast.io/forecast/APIKEY/LATITUDE,LONGITUDE,TIME
and of course one needs to register for an API key.
The TIME parameter is optional, the temperature uses Fahrenheit metrics by default, but this can be changed with additional ?units=ca parameter.
One disadvantage is that you get only a 1,000 free calls per day, which probably won't be suitable for big applications.
If you know a better answer to the original question, I'll be very happy to hear it. Until then I'll use this solution, without going into much details:
// The default result from a Forecast API call is in JSON,
// so decode it to an object for easier access
$fcObj = json_decode($jsonResult);
if(!empty($fcObj->daily->data[0]->humidity)) {
// get humidity value in %
$humidty = $fcObj->daily->data[0]->humidity * 100;
}