quant | Quantitative Analysis Research see more at https | Machine Learning library

by teddykoker Python Version: Current License: No License

X-Ray Key Features Code Snippets(1)Community Discussions(10)Vulnerabilities Install Support

kandi X-RAY | quant Summary

quant is a Python library typically used in Artificial Intelligence, Machine Learning applications. quant has no bugs, it has no vulnerabilities and it has low support. However quant build file is not available. You can download it from GitHub.

backtester: side-project WIP of simple event-driven backtester. survivorship-free: Survivorship Bias-Free S&P 500 stock data from my blog post. Jupyter Notebooks for most of my blog posts are available in my blog repo.

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Quality

Security

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Support

quant has a low active ecosystem.

It has 80 star(s) with 45 fork(s). There are 2 watchers for this library.

It had no major release in the last 6 months.

There are 1 open issues and 0 have been closed. On average issues are closed in 417 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of quant is current.

Quality

quant has 0 bugs and 0 code smells.

Security

quant has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

quant code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

quant does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

quant releases are not available. You will need to build from source code and install.

quant has no build file. You will be need to create the build yourself to build the component from source.

It has 366 lines of code, 30 functions and 8 files.

It has low code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed quant and discovered the below as its top functions. This is intended to give you an instant insight into quant implemented functionality, and help decide if they suit your requirements.

Query Quandl data
Convert the given ticker to the appropriate format
Convert a ticker
Returns a pandas DataFrame containing the constituent constituents
Return a pandas DataFrame of Yahoo Finance

Get all kandi verified functions for this library.

quant Key Features

No Key Features are available at this moment for quant.

quant Examples and Code Snippets

Fake quant with minVars per channel .

python

Lines of Code : 9

License : Non-SPDX (Apache License 2.0)

Copy

def _FakeQuantWithMinMaxVarsPerChannelGradient(op, grad):
  """Gradient for FakeQuantWithMinMaxVarsPerChannel op."""
  return fake_quant_with_min_max_vars_per_channel_gradient(
      grad,
      op.inputs[0],
      op.inputs[1],
      op.inputs[2],

Community Discussions

Trending Discussions on quant

SQL/DB2 getting single row of results per employee with a UNION

Creating loop over columns to calculate regression and then compare best combination of variables

Flagging NaN values based on a condition and year

How to sort (rearrange) DataFrame by descending last row value, and rearrange columns respectively

How can I create a parallel analysis scree in R?

ONNX Runtime Inference | session.run() multiprocessing

Problem minimising a function using L-BFGS-B method in R?

Descriptive Statistic in R with more than one X

Error applying facet_wrap() in geom_sf() incomplete polygon in ggplot R

How do I use lapply or sapply for boostraping or KM calculations on three different DFs when functions are nested?

QUESTION

SQL/DB2 getting single row of results per employee with a UNION

Asked 2022-Mar-28 at 17:57

I'm currently using a UNION on 2 select statements and while I'm getting the correct data, it's not exactly what I actually need when it comes time to use it in a front-end view

I'm currently using this query:

...

ANSWER

Answered 2022-Mar-28 at 17:57

Try adding an outer query:

Source https://stackoverflow.com/questions/71651405

QUESTION

Creating loop over columns to calculate regression and then compare best combination of variables

Asked 2022-Mar-24 at 19:14

I am trying to run a loop which takes different columns of a dataset as the dependent variable and remaining variables as the independent variables and run the lm command. Here's my code

...

ANSWER

Answered 2022-Mar-24 at 17:53

We could change the line of fit with

Source https://stackoverflow.com/questions/71605227

QUESTION

Flagging NaN values based on a condition and year

Asked 2022-Mar-18 at 17:23

I am trying to get this requirement of flagging NaN values based on condition and particular year, below is my code:

...

ANSWER

Answered 2022-Mar-18 at 17:13

You could build a boolean condition that checks if "Quant" is greater than "upper" and the month is "03" or "04", and mask "Quant" column:

Source https://stackoverflow.com/questions/71530740

QUESTION

How to sort (rearrange) DataFrame by descending last row value, and rearrange columns respectively

Asked 2022-Feb-18 at 09:47

I am working my quant. I have a set of data which is date-indexed, and the output heatmap is not sorted in any way. What I want is to sort the values of the last day (today if the case) numbers descending, and rearrange the columns respectively.

raw data:

...

ANSWER

Answered 2022-Feb-18 at 09:47

You can use pandas.DataFrame.sort_values method and set axis=1 in the argument. and sort the dataframe according to the values of the last row.

Source https://stackoverflow.com/questions/71170980

QUESTION

How can I create a parallel analysis scree in R?

Asked 2022-Feb-12 at 13:17

Dataset Dput ...

ANSWER

Answered 2022-Feb-12 at 13:17

The only problem is that there are Heywood cases, so the fa analysis isn't trustworthy.

Source https://stackoverflow.com/questions/71091241

QUESTION

ONNX Runtime Inference | session.run() multiprocessing

Asked 2022-Jan-21 at 16:56

Goal: run Inference in parallel on multiple CPU cores

I'm experimenting with Inference using simple_onnxruntime_inference.ipynb.

Individually:

...

ANSWER

Answered 2022-Jan-21 at 16:56

def run_inference(i):
    output_name = session.get_outputs()[0].name
    return session.run([output_name], {input_name: inputs[i]})[0]  # [0] bc array in list

outputs = pool.map(run_inference, [i for i in range(test_data_num)])

Source https://stackoverflow.com/questions/70803924

QUESTION

Problem minimising a function using L-BFGS-B method in R?

Asked 2022-Jan-08 at 02:02

A similar question was asked here but it didn't receive any answers.

I have a function that I need to minimize. My function has 3 parameters, x, y, and w. Given w, I need to find the optimal pair of x and y that minimizes my function. However, x and y are restricted in the interval (-0.5 ,0.5]

I tried to use the optim function and it works when I don't have restrictions. However, when I apply the restrictions and use the L-BFGS-B method, I get an error. I cant figure out why I am getting this error.

Below is an example of my function and some of the methods I have tried. This is the function that Im trying to minimize:

...

ANSWER

Answered 2022-Jan-08 at 02:02

Here's a start. I added a line

Source https://stackoverflow.com/questions/70628439

QUESTION

Descriptive Statistic in R with more than one X

Asked 2021-Dec-29 at 23:18

I'm currently working with the psych package. I have the variables StockPrice, BookValuePS (PS = per share), EPS (= Earnings per share) and ESGscore.

I want to do some descriptive statistic for my final paper.

The code I use at the moment is:

...

ANSWER

Answered 2021-Dec-29 at 23:18

First

11 and 12 means: Not item, the item column is 1 and 2 meaning that your grouping variable ggroup has 2 items or two levels.

11 and 12 are row names: if you wrap the whole thing around tibble() thy will disappear. In detail they mean first 1 = variable1, second 1 of 11 means level or item 1 of the grouping variable. You can get it if you follow the example at the end.

Second

You can analyze the complete dataset grouped with this formula input: describeBy(data_excel ~ ggroup)

To avoind the error:

Source https://stackoverflow.com/questions/70525691

QUESTION

Error applying facet_wrap() in geom_sf() incomplete polygon in ggplot R

Asked 2021-Nov-07 at 17:43

I have a shapefile with 7 regions. I have an excel file with data about reptiles in these 7 regions. I merged this shapefile with excel.

Using ggplot I tried to generate facet_wrap() from nome_popular, however the rest of the polygon parts were omitted in each facet created.

My tentative code

shapefile: https://drive.google.com/file/d/1I1m9lBX69zjsdGBg2zfpii5H4VFYE1_0/view?usp=sharing

excel:https://docs.google.com/spreadsheets/d/1eKQWWCAalehTTrUuqUlMPQnSTEZxF--g/edit?usp=sharing&ouid=118442515534677263769&rtpof=true&sd=true

...

ANSWER

Answered 2021-Oct-31 at 05:58

The issue is that with faceting the data is splitted in groups and only the polygons contained in the splitted data will show up.

If you want all regions to be shown in each facet then one option would be to add a base map via second geom_sf layer. In your case + geom_sf(regiao) + geom_sf() should do the job.

As an example I make use of the default example from ?geom_sf:

Source https://stackoverflow.com/questions/69783859

QUESTION

How do I use lapply or sapply for boostraping or KM calculations on three different DFs when functions are nested?

Asked 2021-Oct-31 at 06:12

I want to run a bootstrap (k=10,000) and Kaplan-Meier calculations on the numeric column of three different data frames using lapply or sapply when functions are nested.

I have defined three functions to use as arguments in the command for boostrapping. One function returns a set of predefined quantiles, another the median, and a thrid a 95% confidence interval for the median. Bootstrapping fails altogether. The error I get for bootstrapping reads, "Error in x[, "Result", drop = FALSE] : incorrect number of dimensions"

KM only completes for the first data frame on the list (df).

I am using the boot and NADA2 libraries for the calculations.

Below is a REPREX of the data, functions, and commands:

...

ANSWER

Answered 2021-Oct-31 at 06:12

First of all you should use list instead of c and give the data frames names like so:

Source https://stackoverflow.com/questions/69776987

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install quant

You can download it from GitHub.
You can use quant like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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