duplicates

I have array data from two separate mysql queries. Array data looks like below: 0 : {user_id: 82, ac_type: 1,…} 1 : {user_id: 80, ac_type: 5,…} 2 : {user_id: 76, ac_type: 1,…} 3 : {user_id: 82, ac_type: 1,…} 4 : {user_id: 80, ac_type: 5,…} I want to remove the duplicate array items. So, my output will be like this: 0 : {user_id: 82, ac_type: 1,…} 1 : {user_id: 80, ac_type: 5,…} 2 : {user_id: 76, ac_type: 1,…} I want to check duplicate by user_id. I have tried the following solutions, but neither are not working as desired. $input = array_unique($res, SORT_REGULAR); $input = array_map(

I need some help to filter a dataframe. The df has several columns and I want to split it into two dataframes: 1- One including only the rows in which the first column is a duplicate (including all of the replicas). 2- The rest of the rows, which are not duplicates. Here is an example: This would be the original. V1 V2 [1,] "A" "1" [2,] "B" "1" [3,] "A" "1" [4,] "C" "2" [5,] "D" "3" [6,] "D" "4" I want to turn into this: V1 V2 [1,] "A" "1" [2,] "A" "1" [3,] "D" "3" [4,] "D" "4" And this: V1 V2 [1,] "B" "1" [2,] "C" "2" Is there a way to do that? I have tried exporting to Excel, but the dataset

I have the below XML <Automobiles> <Cars> <YearofMfr>2010</YearofMfr> <Mileage>12</Mileage> <MeterReading>1500</MeterReading> <Color>Red</Color> <Condition>Excellent</Condition> </Cars> <Cars> <YearofMfr>2010</YearofMfr> <Mileage>12</Mileage> <MeterReading>1500</MeterReading> <Color>Red</Color> <Condition>Excellent</Condition> </Cars> <Cars> <YearofMfr>2008</YearofMfr> <Mileage>11</Mileage> <MeterReading>20000</MeterReading> <Color>Pearl White</Color> <Condition>Good</Condition> </Cars> </Automobiles> I was looking for a LINQ Query which would return duplicate nodes. In the above XML there are

Given n dictionaries, write a function that will return a unique dictionary with a list of values for duplicate keys. Example: d1 = {'a': 1, 'b': 2} d2 = {'c': 3, 'b': 4} d3 = {'a': 5, 'd': 6} result: >>> newdict {'c': 3, 'd': 6, 'a': [1, 5], 'b': [2, 4]} My code so far: >>> def merge_dicts(*dicts): ... x = [] ... for item in dicts: ... x.append(item) ... return x ... >>> merge_dicts(d1, d2, d3) [{'a': 1, 'b': 2}, {'c': 3, 'b': 4}, {'a': 5, 'd': 6}] What would be the best way to produce a new dictionary that yields a list of values for those duplicate keys? def merge_dicts(*dicts): d = {} for

In my code this command is run only once: jQuery("#commentrating").append('A'); but inside the div #commentrating there appears two "A" elements! What may be causing this bug? P.S. .after() is buggy as well :S Maybe it's caused by event-bubbling.(just a guess as long as no further info is available) Assuming this: <script type="text/javascript"> jQuery( function($) { $('div') .click(function(e) { $('span',this).append('A'); } ); } ); </script> <div><div><b>click here:</b><span></span></div></div> if you click on the text, the click will trigger on the inner div and bubble up to the outer div,

I have many data.frames, for example: df1 = data.frame(names=c('a','b','c','c','d'),data1=c(1,2,3,4,5)) df2 = data.frame(names=c('a','e','e','c','c','d'),data2=c(1,2,3,4,5,6)) df3 = data.frame(names=c('c','e'),data3=c(1,2)) and I need to merge these data.frames, without delete the name duplicates > result names data1 data2 data3 1 'a' 1 1 NA 2 'b' 2 NA NA 3 'c' 3 4 1 4 'c' 4 5 NA 5 'd' 5 6 NA 6 'e' NA 2 2 7 'e' NA 3 NA I cant find function like merge with option to handle with name duplicates. Thank you for your help. To define my problem. The data comes from biological experiment where one

The purpose of my code is to import 2 Excel files, compare them, and print out the differences to a new Excel file. However, after concatenating all the data, and using the drop_duplicates function, the code is accepted by the console. But, when printed to the new excel file, duplicates still remain within the day. Am I missing something? Is something nullifying the drop_duplicates function? My code is as follows: import datetime import xlrd import pandas as pd #identify excel file paths filepath = r"excel filepath" filepath2 = r"excel filepath2" #read relevant columns from the excel files df1