Reindex | Kashyap Software - Magento 2 Reindex From Backend | Ecommerce library

by softwarekashyap PHP Version: Current License: No License

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kandi X-RAY | Reindex Summary

Reindex is a PHP library typically used in Web Site, Ecommerce applications. Reindex has no bugs, it has no vulnerabilities and it has low support. You can download it from GitHub.

This extension will add the ability to Reindex from backend. Magento 2 Reindex From Backend by Kashyap Software allows store admins to update individual or all indexes manually right from the admin backend easily instead of running command line.

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Support

Reindex has a low active ecosystem.

It has 2 star(s) with 0 fork(s). There are 2 watchers for this library.

It had no major release in the last 6 months.

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

It has a neutral sentiment in the developer community.

The latest version of Reindex is current.

Quality

Reindex has 0 bugs and 0 code smells.

Security

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

Reindex code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

Reindex 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

Reindex 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.

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Reindex Examples and Code Snippets

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Community Discussions

Trending Discussions on Reindex

How to reorder the days of week in this Pandas Pivot Table?

Trying Sort Data in a Cell by Date in Pandas

Sort PivotTable values descending order in pandas

Normalizing nested JSON object into Pandas dataframe

Extracting latest values in a Dask dataframe with non-unique index column dates

How to filter column names from multiindex dataframe for a specific condition?

Multiply dataframe with series having index duplicates and excluding one column

groupby rolling date window sum with duplicate dates

A Lexicographical Bug in Pandas?

How to convert and reshape MultiIndex to 3D Numpy array?

QUESTION

How to reorder the days of week in this Pandas Pivot Table?

Asked 2022-Mar-22 at 17:04

import numpy as np 
import pandas as pd 
import matplotlib.pyplot as plt
import seaborn as sns
import datetime
    
df = pd.read_excel("Baltimore Towing Division.xlsx",sheet_name="TowingData")

df['Month'] = pd.DatetimeIndex(df['TowedDate']).strftime("%b")
df['Week day'] = pd.DatetimeIndex(df['TowedDate']).strftime("%a")


monthOrder = ['Jan', 'Feb', 'Mar', 'Apr','May','Jun','Jul','Aug','Sep','Oct','Nov','Dec']
dayOrder = ['Mon','Tue','Wed','Thu','Fri','Sat','Sun']


Pivotdf = pd.pivot_table(df, index=['Month'],
                        values=['TowedDate'],
                        columns=['Week day'],
                        fill_value=0,
                        aggfunc='count').reindex(monthOrder,axis=0).reindex(dayOrder,axis=1)

print(df)

...

ANSWER

Answered 2022-Mar-22 at 16:33

Maybe using loc:

Source https://stackoverflow.com/questions/71575524

QUESTION

Trying Sort Data in a Cell by Date in Pandas

Asked 2022-Mar-08 at 22:33

I have a data set and in a column of which each cell contains data which is an mixture of strings and a date like this

AE 2018-04-30 10:28, Bokning, Johan Skoglund, 1295 imkanal 2019-08-12 15:27, CrossNej, nan, nan 2020-06-25 18:21, CrossNej, nan, nan :---- 2018-09-13 12:25, Bokning, Simon Wallin, 2195 im och frånluften 2019-07-26 16:26, CrossNej, nan, nan 2020-09-01 14:49, RetentionTelsvarare, nan, nan :---- 2019-02-25 14:00, Bokning, Jan Gunnarsson, Imkanal 1495 kr 2019-11-07 15:39, CrossNej, nan, nan 2020-01-14 17:52, CrossNej, nan, nan 2020-12-16 11:14, CrossRensat 12 mån, nan, nan

What I want to do is to arrange values in each cell by date in descending order (from highest to lowest). I have tried almost every solution present online but I have been unable to do so. Either it's only a date or only a string. I am splitting it by line break

...

ANSWER

Answered 2022-Mar-08 at 02:01

Your description of the problem and expected results is not very clear, I can only guess by myself, try the following code:

Source https://stackoverflow.com/questions/71388813

QUESTION

Sort PivotTable values descending order in pandas

Asked 2022-Feb-23 at 10:51

I have a Pivot table that is plotted into a vertical plot that leaves gaps in between the bars.

I would like to sort the values for each month 'DATE' in descending order so the Plot leaves no gaps in between:

I have tried to sort_values() before and during the plotting, which didn't work.

It might be related to sorting by levels in a multi-index (also tried) or to reindex, but I can't get it to work.

...

ANSWER

Answered 2022-Feb-23 at 10:51

To get the expected result, in this solution the idea is to draw different plots (one for each value of Date) next to each other. It is done for 2 subgroups (June and July) but can be generalized easily.

Source https://stackoverflow.com/questions/71133726

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

Extracting latest values in a Dask dataframe with non-unique index column dates

Asked 2022-Jan-24 at 23:36

I'm quite familiar with pandas dataframes but I'm very new to Dask so I'm still trying to wrap my head around parallelizing my code. I've obtained my desired results using pandas and pandarallel already so what I'm trying to figure out is if I can scale up the task or speed it up somehow using Dask.

Let's say my dataframe has datetimes as non-unique indices, a values column and an id column.

...

ANSWER

Answered 2021-Dec-16 at 07:42

The snippet below shows that it's a very similar syntax:

Source https://stackoverflow.com/questions/70374896

QUESTION

How to filter column names from multiindex dataframe for a specific condition?

Asked 2022-Jan-19 at 11:48


df1 = pd.DataFrame(
{
    "empid" : [1,2,3,4,5,6],
    "empname" : ['a', 'b','c','d','e','f'],
    "empcity" : ['aa','bb','cc','dd','ee','ff']
})
df1

df2 = pd.DataFrame(
{
    "empid" : [1,2,3,4,5,6],
    "empname" : ['a', 'b','m','d','n','f'],
    "empcity" : ['aa','bb','cc','ddd','ee','fff']
})
df2

df_all = pd.concat([df1.set_index('empid'),df2.set_index('empid')],axis='columns',keys=['first','second'])
df_all

df_final = df_all.swaplevel(axis = 'columns')[df1.columns[1:]]
df_final

orig = df1.columns[1:].tolist()
print (orig)
['empname', 'empcity']

df_final = (df_all.stack()
                  .assign(comparions=lambda x: x['first'].eq(x['second']))
                  .unstack()
                  .swaplevel(axis = 'columns')
                  .reindex(orig, axis=1, level=0))
print (df_final)

...

ANSWER

Answered 2022-Jan-19 at 11:48

First test if in level comparions are all Trues by DataFrame.xs with DataFrame.all:

Source https://stackoverflow.com/questions/70769977

QUESTION

Multiply dataframe with series having index duplicates and excluding one column

Asked 2021-Dec-29 at 02:23

A shortened version of my dataframe looks like this:

...

ANSWER

Answered 2021-Dec-28 at 23:39

Starting from pandas 0.24.0 you can merge series to a dataframe directly as long as the series is named:

Source https://stackoverflow.com/questions/70513664

QUESTION

groupby rolling date window sum with duplicate dates

Asked 2021-Dec-26 at 21:42

This answer provides a solution to get a rolling sum of a column grouped by another column based on a date window. To reproduce it here:

...

ANSWER

Answered 2021-Dec-22 at 04:44

Based on comments to the question, it appears that OP already found a solution. However, this is an attempt at providing another way to resolve this, which is to solve the root cause of the error - duplicate date values.

To resolve it, we can add aggregation by date within the apply. In the snippet below, the Amount values are aggregated using sum, but it is possible that in some contexts another aggregation should be used, e.g. min or max. This is the relevant part:

Source https://stackoverflow.com/questions/70398462

QUESTION

A Lexicographical Bug in Pandas?

Asked 2021-Dec-21 at 22:53

Please take this question lightly as asked from curiosity:

As I was trying to see how the slicing in MultiIndex works, I came across the following situation ↓

...

ANSWER

Answered 2021-Dec-21 at 22:53

The difference between your 2 dataframes is the following:

Source https://stackoverflow.com/questions/69909707

QUESTION

How to convert and reshape MultiIndex to 3D Numpy array?

Asked 2021-Nov-26 at 05:47

I have 4D data in a data frame. I need to convert it to 3D Numpy array. I can do it with for-loops, but is there more efficient way?

...

ANSWER

Answered 2021-Nov-24 at 16:22

It seems like np.swapaxes does the trick you need: arr.reshape(2,3,4,4).swapaxes(2,3).reshape(2,3,16)

The main idea is to swap the axes in the most inner data:

Source https://stackoverflow.com/questions/70099337

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

Vulnerabilities

No vulnerabilities reported

Install Reindex

Download zip file of this extension
Place all the files of the extension in your Magento 2 installation in the folder app/code/Kashyap/Reindex
Enable the extension: php bin/magento --clear-static-content module:enable Kashyap_Reindex
Upgrade db scheme: php bin/magento setup:upgrade
Deply Static Content: php bin/magento setup:static-content:deploy -f Developer Mode
Deply Static Content: php bin/magento setup:static-content:deploy Production Mode

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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