duplicates

问题 I have cells containing duplicate values that i want to merge quickly. The table looks like this: Sub MergeCells() Application.DisplayAlerts = False Dim n As Name Dim fc As FormatCondition Dim Rng As Range, R As Range Dim lRow As Long Dim I&, J& Dim arr As Variant ReDim arr(1 To 1) As Variant With ThisWorkbook.Sheets("tst") Set Rng = .Range("A2:D11") lRow = Rng.End(xlDown).Row For J = 1 To 4 For I = lRow To 2 Step -1 'last row to 2nd row If Trim(UCase(.Cells(I, J))) = Trim(UCase(.Cells(I - 1,

问题 I have a array of page numbers: foreach($elements as $el) { $pageno = $el->getAttribute("pageno"); echo $pageno ; } Sadly it contains duplicates. I tried the follow code but it won't return a thing: foreach(array_unique($elements) as $el) { $pageno = $el->getAttribute("pageno"); echo $pageno ; } How to remove the duplicate page numbers? Thanks in advance :) 回答1: Since I do not have your data structure, I am providing a generic solution. This can be optimized if we know the structure of

问题 I'm trying to have all duplicates in a range highlighted. The twist is I want each different value to have a different color. For example all the values "Apple" would be one color. All the values "Car" would be another color etc. I've found a way to do this, although it can only be run on one Column. I need some help getting it to run on multiple columns. Here is a photo of my example: Here is the VBA code I'm running which currently highlights only column C: Sub different_colourTest2() Dim

问题 With following dataframes, how do I extract and keep in different dataframes: rows with unique Account only all rows with duplicated Account s I have two datasets, df[0] ...: Account Verified Paid Col1 Col2 Col3 1234 True True ... ... ... 1237 False True 1234 True True 4211 True True 1237 False True 312 False False ...and df[1] : Account Verified Paid Col1 Col2 Col3 41 True True ... ... ... 314 False False 41 True True 65 False False To pass through all dataframes in my list, without

问题 I have 2d numpy array: arr = np.array([[0.1, 0.1, 0.3, 0.4, 0.5], [0.06, 0.1, 0.1, 0.1, 0.01], [0.24, 0.24, 0.24, 0.24, 0.24], [0.2, 0.25, 0.3, 0.12, 0.02]]) print (arr) [[0.1 0.1 0.3 0.4 0.5 ] [0.06 0.1 0.1 0.1 0.01] [0.24 0.24 0.24 0.24 0.24] [0.2 0.25 0.3 0.12 0.02]] I want filter top N values, so I use argsort : N = 2 arr1 = np.argsort(-arr, kind='mergesort') < N print (arr1) [[False False False True True] [ True False False True False] <- first top 2 are duplicates [ True True False

问题 My question is similar to this previous SO question I have a very two large lists of data (almost 120 million data points) that contains numerous consecutive duplicates. I would like to remove the consecutive duplicate as follow list1 = [1,1,1,1,1,1,2,3,4,4,5,1,2] #This is 20M long! list2 =[another list of size len(list1)]#This is also 20M long! i = 0 while i < len(list)-1: if list[i] == list[i+1]: del list1[i] del list2[i] else: i = i+1 And the output should be [1, 2, 3, 4, 5, 1, 2]

问题 I have a dataset in which I need to conditionally remove duplicated rows based on values in another column. Specifically, I need to delete any row where size = 0 only if SampleID is duplicated . SampleID<-c("a", "a", "b", "b", "b", "c", "d", "d", "e") size<-c(0, 1, 1, 2, 3, 0, 0, 1, 0) data<-data.frame(SampleID, size) I want to delete rows with: Sample ID size a 0 d 0 And keep: SampleID size a 1 b 1 b 2 b 3 c 0 d 1 e 0 Note. actual dataset it very large, so I am not looking for a way to just

问题 I was trying to remove duplicates from a list using the following code: a = [1,2,3,4,2,6,1,1,5,2] res = [] [res.append(i) for i in a if i not in res] But I would like to do this without defining the list I want as an empty list (ie, omit the line res = [] ) like: a = [1,2,3,4,2,6,1,1,5,2] #Either: res = [i for i in a if i not in res] #Or: [i for i in a if i not in 'this list'] # this list is not a string. I meant it as the list being comprehensed I want to avoid library imports and set() 回答1:

问题 I was trying to remove duplicates from a list using the following code: a = [1,2,3,4,2,6,1,1,5,2] res = [] [res.append(i) for i in a if i not in res] But I would like to do this without defining the list I want as an empty list (ie, omit the line res = [] ) like: a = [1,2,3,4,2,6,1,1,5,2] #Either: res = [i for i in a if i not in res] #Or: [i for i in a if i not in 'this list'] # this list is not a string. I meant it as the list being comprehensed I want to avoid library imports and set() 回答1:

问题 I am trying to find duplicates rows in a pandas dataframe. df=pd.DataFrame(data=[[1,2],[3,4],[1,2],[1,4],[1,2]],columns=['col1','col2']) df Out[15]: col1 col2 0 1 2 1 3 4 2 1 2 3 1 4 4 1 2 duplicate_bool = df.duplicated(subset=['col1','col2'], keep='first') duplicate = df.loc[duplicate_bool == True] duplicate Out[16]: col1 col2 2 1 2 4 1 2 Is there a way to add a column referring to the index of the first duplicate (the one kept) duplicate Out[16]: col1 col2 index_original 2 1 2 0 4 1 2 0