inplace | Restful inplace plugin for Rails | Frontend Framework library

by simplificator Ruby Version: Current License: MIT

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

kandi X-RAY | inplace Summary

inplace is a Ruby library typically used in User Interface, Frontend Framework, React applications. inplace has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.

Inplace is a simple RESTful in place editor based and tested on Rails 2.1.0.

Support

Quality

Security

License

Reuse

Support

inplace has a low active ecosystem.

It has 24 star(s) with 3 fork(s). There are 3 watchers for this library.

It had no major release in the last 6 months.

inplace has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of inplace is current.

Quality

inplace has 0 bugs and 0 code smells.

Security

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

inplace code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

inplace 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

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

Installation instructions are available. Examples and code snippets are not available.

inplace saves you 23 person hours of effort in developing the same functionality from scratch.

It has 65 lines of code, 3 functions and 6 files.

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

Top functions reviewed by kandi - BETA

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

Generates an HTML tag for an element .
Converts a JSON string to a JSON string .

Get all kandi verified functions for this library.

inplace Key Features

No Key Features are available at this moment for inplace.

inplace Examples and Code Snippets

No Code Snippets are available at this moment for inplace.

Community Discussions

Trending Discussions on inplace

Skip first line in import statement using gc.open_by_url from gspread (i.e. add header=0)

Normalizing nested JSON object into Pandas dataframe

Explode pandas column of dictionary with list of tuples as value

Efficient way to extract data from NETCDF files

This pandas series is a view... into what?

Pandas - How to Save A Styled Dataframe to Image

Rolling sum based on all previous dates NOT previous rows sorted by date

Why is this float conversion made

Fillna if all the values of a column are null in pandas

Convert subset of columns to rows by combining columns

QUESTION

Skip first line in import statement using gc.open_by_url from gspread (i.e. add header=0)

Asked 2022-Mar-16 at 08:12

What is the equivalent of header=0 in pandas, which recognises the first line as a heading in gspread?

pandas import statement (correct)

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ANSWER

Answered 2022-Mar-16 at 08:12

Looking at the API documentation, you probably want to use:

Source https://stackoverflow.com/questions/71418682

QUESTION

Normalizing nested JSON object into Pandas dataframe

Asked 2022-Feb-05 at 07:30

Background: I am trying to normalize a json file, and save into a pandas dataframe, however I am having issues navigating the json structure and my code isn't working as expected.

Expected dataframe output: Given the following example json file (uses randomized data, but exactly the same format as the real one), this is the output I am trying to produce -

New Entity Group Entity ID Adjusted Value
(1/31/2022, No Div, USD) Adjusted TWR
(Current Quarter No Div, USD)) Adjusted TWR
(YTD, No Div, USD) Annualized Adjusted TWR
(Since Inception, No Div, USD) Inception Date Risk Target Portfolio_1 $260,786 (44.55%) (44.55%) (44.55%) * Apr 7, 2021 N/A The FW Irrev Family Tr 9552252 $260,786 0.00% 0.00% 0.00% * Jan 11, 2022 N/A Portfolio_2 $18,396,664 (5.78%) (5.78%) (5.47%) * Sep 3, 2021 Growth FW DAF 10946585 $18,396,664 (5.78%) (5.78%) (5.47%) * Sep 3, 2021 Growth Portfolio_3 $60,143,818 (4.42%) (4.42%) 7.75% * Dec 17, 2020 - The FW Family Trust 13014080 $475,356 (6.10%) (6.10%) (3.97%) * Apr 9, 2021 Aggressive FW Liquid Fund LP 13396796 $52,899,527 (4.15%) (4.15%) (4.15%) * Dec 30, 2021 Aggressive FW Holdings No. 2 LLC 8413655 $6,768,937 (0.77%) (0.77%) 11.84% * Mar 5, 2021 N/A FW and FR Joint 9957007 ($1) - - - * Dec 21, 2021 N/A

Actual dataframe output: despite my best efforts, I have only been able to get bolded rows to map into the dataframe:

JSON file: this is the file I am trying to normalize and map into a dataframe:

...

ANSWER

Answered 2022-Feb-04 at 15:02

Since your children's children has same structure as children, you can try using json_normalize twice separately and append it together.

Source https://stackoverflow.com/questions/70936674

QUESTION

Explode pandas column of dictionary with list of tuples as value

Asked 2022-Feb-03 at 21:11

I have the following dataframe where col2 is a dictionary with a list of tuples as values. The keys are consistantly 'added' and 'deleted' in the whole dataframe.

Input df

col1 col2 value1 {'added': [(59, 'dep1_v2'), (60, 'dep2_v2')], 'deleted': [(59, 'dep1_v1'), (60, 'dep2_v1')]} value 2 {'added': [(61, 'dep3_v2')], 'deleted': [(61, 'dep3_v1')]}

Here's a copy-pasteable example dataframe:

...

ANSWER

Answered 2022-Feb-03 at 01:47

Here's a solution. It's a little long, but it works:

Source https://stackoverflow.com/questions/70964740

QUESTION

Efficient way to extract data from NETCDF files

Asked 2022-Jan-21 at 18:30

I have a number of coordinates (roughly 20000) for which I need to extract data from a number of NetCDF files each comes roughly with 30000 timesteps (future climate scenarios). Using the solution here is not efficient and the reason is the time spent at each i,j to convert "dsloc" to "dataframe" (look at the code below). ** an example NetCDF file could be download from here **

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ANSWER

Answered 2021-Sep-26 at 00:51

I have a potential solution. The idea is to convert xarray data array to pandas first, then get a subset of the pandas dataframe based on lat/lon conditions.

Source https://stackoverflow.com/questions/69330668

QUESTION

This pandas series is a view... into what?

Asked 2022-Jan-15 at 02:55

Consider the following example.

...

ANSWER

Answered 2022-Jan-15 at 02:55

inplace does not guarantee that the dataframe will be modified in place. In this case, as in many cases, it creates a copy and reassigns it to df. See the discussion of inplace here.

As for x being a view, if you execute x.values.base you will get:

Source https://stackoverflow.com/questions/70718307

QUESTION

Pandas - How to Save A Styled Dataframe to Image

Asked 2022-Jan-01 at 17:04

I have styled a dataframe output and have gotten it to display how I want it in a Jupyter Notebook but I am having issues find a good way to save this as an image. I have tried https://pypi.org/project/dataframe-image/ but the way I have this working it seem to be a NoneType as it's a styler object and errors out when trying to use this library.

This is just a snippet of the whole code, this is intended to loop through several 'col_names' and I want to save these as images (to explain some of the coding).

...

ANSWER

Answered 2022-Jan-01 at 17:04

Was able to change how I was using dataframe-image on the styler object and got it working. Passing it into the export() function rather than calling it off the object directly seems to be the right way to do this.

The .render() did get the HTML but was often losing much of the styling when converting it to image or when not viewed with Ipython HTML display. See comparision below.

Working Code:

Source https://stackoverflow.com/questions/70546823

QUESTION

Rolling sum based on all previous dates NOT previous rows sorted by date

Asked 2021-Dec-21 at 20:17

Given the following dataframe:

...

ANSWER

Answered 2021-Dec-20 at 01:49

One way is to aggregate your amounts by date first, then compute the rolling sum, and join this sum to the original list of dates to apply the rolling sum to all dates

Source https://stackoverflow.com/questions/70416616

QUESTION

Why is this float conversion made

Asked 2021-Dec-16 at 20:39

I have this dataframe

...

ANSWER

Answered 2021-Dec-16 at 20:33

x.iloc[0] selects a single "row". A new series object is actually created. When it decides on the dtype of that row, a pd.Series, it uses a floating point type, since that would not lose information in the "Nr" column.

On the other hand, x['Selected'].iloc[0] first selects a column, which will always preserve the dtype.

pandas is fundamentally "column oriented". You can think of a dataframe as a dictionary of columns (it isn't, although I believe it used to essentially have that under the hood, but now it uses a more complex "block manager" approach, but these are internal implementation details)

Source https://stackoverflow.com/questions/70385155

QUESTION

Fillna if all the values of a column are null in pandas

Asked 2021-Nov-17 at 10:38

I have to fill a column only if all the values of that column are null. For example c

...

ANSWER

Answered 2021-Nov-17 at 10:38

Warning: after OP modified the question and gave more details on the exact expected output, this answer is no longer valid.

You almost had it ;)

Source https://stackoverflow.com/questions/70002365

QUESTION

Convert subset of columns to rows by combining columns

Asked 2021-Oct-26 at 04:54

Pandas 1.1.4

MRE:

...

ANSWER

Answered 2021-Oct-26 at 03:13

This is essentially a reshape operation using stack

Source https://stackoverflow.com/questions/69716911

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

Vulnerabilities

No vulnerabilities reported

Install inplace

You can download it from GitHub.
On a UNIX-like operating system, using your system’s package manager is easiest. However, the packaged Ruby version may not be the newest one. There is also an installer for Windows. Managers help you to switch between multiple Ruby versions on your system. Installers can be used to install a specific or multiple Ruby versions. Please refer ruby-lang.org for more information.

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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