Numpy_arraysetops_EP | Numpy group_by and set-operations | Data Manipulation library

by EelcoHoogendoorn Python Version: 0.3.5 License: MIT

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

kandi X-RAY | Numpy_arraysetops_EP Summary

Numpy_arraysetops_EP is a Python library typically used in Utilities, Data Manipulation, Numpy applications. Numpy_arraysetops_EP has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can install using 'pip install Numpy_arraysetops_EP' or download it from GitHub, PyPI.

Numpy group_by and set-operations

Support

Quality

Security

License

Reuse

Support

Numpy_arraysetops_EP has a low active ecosystem.

It has 140 star(s) with 16 fork(s). There are 9 watchers for this library.

It had no major release in the last 12 months.

There are 5 open issues and 5 have been closed. On average issues are closed in 120 days. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of Numpy_arraysetops_EP is 0.3.5

Quality

Numpy_arraysetops_EP has 0 bugs and 0 code smells.

Security

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

Numpy_arraysetops_EP code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

Numpy_arraysetops_EP is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

Numpy_arraysetops_EP releases are available to install and integrate.

Deployable package is available in PyPI.

Build file is available. You can build the component from source.

Numpy_arraysetops_EP saves you 441 person hours of effort in developing the same functionality from scratch.

It has 1042 lines of code, 138 functions and 13 files.

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

Top functions reviewed by kandi - BETA

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

This tests the mesh solver
Convert keys to an index
Return the unique keys in the given axis
Convert columns to a structured array
Test the radial reduction
Compute the variance of each group
Compute the mean over each group
Compute the standard deviation over each axis
Compute the mode for each group
Return the index of the maximum value of values
Return the maximum value of each group
Compute the sum over each group
Return the rank of the given keys
Convert an array to an object
Reduce an array along an axis
Return the minimum value for the given values
Return the inverse of the given keys
Allocates a new array
Return the maximum value of the table
Return the unique value for each entry in the table
Return a tuple of unique indices
Compute the first value in the table
Compute the mean of the table
Return unique keys
Return the last value in the table
Check if keys are uniform

Get all kandi verified functions for this library.

Numpy_arraysetops_EP Key Features

No Key Features are available at this moment for Numpy_arraysetops_EP.

Numpy_arraysetops_EP Examples and Code Snippets

No Code Snippets are available at this moment for Numpy_arraysetops_EP.

Community Discussions

Trending Discussions on Data Manipulation

R: Is there a "Un-Character" Command in R?

Creating new columns based on data in row separated by specific character in R

Multiplying and Adding Values across Rows

How to make a rank column in R

How to return the column title wherein the row contains the greatest value in Pandas Dataframe

Split large csv file into multiple files based on column(s)

Get the first non-null value from selected cells in a row

pivot_longer with column pairs

Simulating Random Draws From a "Hat"

Break Apart a String into Separate Columns R

QUESTION

R: Is there a "Un-Character" Command in R?

Asked 2022-Apr-10 at 17:37

I am working with the R programming language.

I have the following dataset:

...

ANSWER

Answered 2022-Apr-10 at 05:36

Up front, "1,3,4" != 1. It seems you should look to split the strings using strsplit(., ",").

Source https://stackoverflow.com/questions/71813866

QUESTION

Creating new columns based on data in row separated by specific character in R

Asked 2022-Mar-15 at 08:48

I've the following table

Owner Pet Housing_Type A Cats;Dog;Rabbit 3 B Dog;Rabbit 2 C Cats 2 D Cats;Rabbit 3 E Cats;Fish 1

The code is as follows:

...

ANSWER

Answered 2022-Mar-15 at 08:48

One approach is to define a helper function that matches for a specific animal, then bind the columns to the original frame.

Note that some wrangling is done to get rid of whitespace to identify the unique animals to query.

Source https://stackoverflow.com/questions/71478316

QUESTION

Multiplying and Adding Values across Rows

Asked 2022-Mar-10 at 08:24

I have this data frame:

...

ANSWER

Answered 2022-Mar-10 at 04:12

We can use stri_replace_all_regex to replace your color_1 into integers together with the arithmetic operator.

Here I've stored your values into a vector color_1_convert. We can use this as the input in stri_replace_all_regex for better management of the values.

Source https://stackoverflow.com/questions/71418533

QUESTION

How to make a rank column in R

Asked 2022-Mar-07 at 16:19

I have a database with columns M1, M2 and M3. These M values correspond to the values obtained by each method. My idea is now to make a rank column for each of them. For M1 and M2, the rank will be from the highest value to the lowest value and M3 in reverse. I made the output table for you to see.

...

ANSWER

Answered 2022-Mar-07 at 14:15

Using rank and relocate:

Source https://stackoverflow.com/questions/71381995

QUESTION

How to return the column title wherein the row contains the greatest value in Pandas Dataframe

Asked 2022-Feb-24 at 20:56

I working on a Python project that has a DataFrame like this:

...

ANSWER

Answered 2022-Feb-24 at 20:48

You could use the idxmax method on axis:

Source https://stackoverflow.com/questions/71258033

QUESTION

Split large csv file into multiple files based on column(s)

Asked 2022-Feb-07 at 12:49

I would like to know of a fast/efficient way in any program (awk/perl/python) to split a csv file (say 10k columns) into multiple small files each containing 2 columns. I would be doing this on a unix machine.

...

ANSWER

Answered 2021-Dec-12 at 05:22

With your show samples, attempts; please try following awk code. Since you are opening files all together it may fail with infamous "too many files opened error" So to avoid that have all values into an array and in END block of this awk code print them one by one and I am closing them ASAP all contents are getting printed to output file.

Source https://stackoverflow.com/questions/70320648

QUESTION

Get the first non-null value from selected cells in a row

Asked 2022-Feb-04 at 09:55

Good afternoon, friends!

I'm currently performing some calculations in R (df is displayed below). My goal is to display in a new column the first non-null value from selected cells for each row.

My df is:

...

ANSWER

Answered 2022-Feb-03 at 11:16

One option with dplyr could be:

Source https://stackoverflow.com/questions/70970158

QUESTION

pivot_longer with column pairs

Asked 2022-Feb-03 at 14:02

I am again struggling with transforming a wide df into a long one using pivot_longer The data frame is a result of power analysis for different effect sizes and sample sizes, this is how the original df looks like:

...

ANSWER

Answered 2022-Feb-03 at 10:59

library(tidyverse)

example %>% 
  pivot_longer(cols = starts_with("es"), names_to = "type", names_prefix = "es_", values_to = "es") %>%
  pivot_longer(cols = starts_with("pwr"), names_to = "pwr", names_prefix = "pwr_") %>% 
  filter(substr(type, 1, 3) == substr(pwr, 1, 3)) %>% 
  mutate(pwr = parse_number(pwr)) %>% 
  arrange(pwr, es, type)

Source https://stackoverflow.com/questions/70969176

QUESTION

Simulating Random Draws From a "Hat"

Asked 2021-Dec-28 at 21:50

Suppose I have the following 10 variables (num_var_1, num_var_2, num_var_3, num_var_4, num_var_5, factor_var_1, factor_var_2, factor_var_3, factor_var_4, factor_var_5):

...

ANSWER

Answered 2021-Dec-26 at 10:11

You may define a function FUN(n) that creates a data set as shown in OP.

Source https://stackoverflow.com/questions/70483731

QUESTION

Break Apart a String into Separate Columns R

Asked 2021-Dec-17 at 20:39

I am trying to tidy up some data that is all contained in 1 column called "game_info" as a string. This data contains college basketball upcoming game data, with the Date, Time, Team IDs, Team Names, etc. Ideally each one of those would be their own column. I have tried separating with a space delimiter, but that has not worked well since there are teams such as "Duke" with 1 part to their name, and teams with 2 to 3 parts to their name (Michigan State, South Dakota State, etc). There also teams with "-" dashes in their name.

Here is my data:

...

ANSWER

Answered 2021-Dec-16 at 15:25

Here's one with regex. See regex101 link for the regex explanations

Source https://stackoverflow.com/questions/70381064

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

Vulnerabilities

No vulnerabilities reported

Install Numpy_arraysetops_EP

You can install using 'pip install Numpy_arraysetops_EP' or download it from GitHub, PyPI.
You can use Numpy_arraysetops_EP 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 .

Find more information at: