duplicates

问题 I have a SQL table with FirstName, LastName, Add1 and other fields. I am working to get this data cleaned up. There are a few instances of likely dupes - All 3 columns are the exact same for more than 1 record The First and Last are the same, only 1 has an address, the other is blank The First and Last are similar (John | Doe vs John C. | Doe) and the address is the same or one is blank I'm wanting to generate a query I can provide to the users, so they can check these records out, compare

问题 I have two SQL tables. One gets a reference value from another table which stores a list of Modules and their ID. But these descriptions are not unique. I am trying to remove the duplicates of Table A but I'm not sure how to update Table B to only reference the single values. Example: Table A: Table B: -------------------------------- ------------------------------------ ID Description RefID ID Name -------------------------------- ------------------------------------ 1 Test 1 2 1

问题 I have a dataset I'm trying to tidy up. I read in the file with read.xlsx, contained in the header is date values that I need to retain their values even when duplicated when I gather/spread the data. The data set looks like the below. The dates from excel read in as numbers (which is fine) the issue is that there can be duplicate dates (e.g. 43693) , which I need to keep their original values. Date 43693 43686 43686 43714 43693 1 Contract 111 222 333 444 555 2 Org1 NR NB NR NB P 3 Org2 P P P

问题 I am aware that I can remove duplicated lines without presorting, for example: awk '!x[$0]++' file However, my goal is to only print lines which are duplicated and only once. If it were not for the presorting problem sort | uniq -d would be perfect. BUT the order is of great importance to me. Is there a way to do this with awk, grep or something similar? I am looking for a one liner which does not require writing a script if possible. 回答1: Just check the value of x[$0] : awk 'x[$0]++ == 1'

问题 I have a list of companies in column a. In column b, I have a number. I need to create a list where the company appears as many times in the list as the value of the number: Company A 4 Company B 2 Company C 3 I want: Company A Company A Company A Company A Company B Company B Company C Company C Company C So, it's sort of a 'Create (n) Duplicates' function. 回答1: Give this a try: Sub KopyKat() Dim N As Long, i As Long, K As Long Dim v As String, kk As Long, m As Long N = Cells(Rows.Count, "B"

问题 I have 3 folders - 1 master and 2 supplemental. I am writing a script that identifies duplicate files in all three via SHA1 hashing. For any duplicates found in master and supplementals (or their subdirectories), I would like to delete the files in the supplemental folders and keep the files in the master folder. If duplicate files are found in the supplemental folders and not the master folder, I would like to keep them and eventually merge with the master. I have written a script (below)

问题 I have a data-frame with 2 columns ID and Product as below : ID Product A Clothing, Clothing Food, Furniture, Furniture B Food,Food,Food, Clothing C Food, Clothing, Clothing I need to have only unique products for each ID, for example : ID Product A Clothing, Food, Furniture B Food, Clothing C Food, Clothing How do I do this using R 回答1: If there are multiple delimiters in the dataset, one way would be to split the 'Product' column using all the delimiters, get the unique and then paste it

问题 What's the best way to remove duplicate objects from array of objects? From var arr = [ {"name":"Joe", "age":17}, {"name":"Bob", "age":17}, {"name":"Carl", "age": 35}, {"name":"Bob", "age":35}, {"name":"Joe", "age":17}, ] when duplicates removed, the expected result is res= arr = [ {"name":"Joe", "age":17}, {"name":"Bob", "age":17}, {"name":"Carl", "age": 35}, {"name":"Bob", "age":35}, ] (5 objects, 1 duplicate, 4 left). The number of properties of each object is fixed, the properties names

问题 How to combine duplicate rows in pandas, filling in missing values? In the example below, some rows have missing values in the c1 column, but the c2 column has duplicates that can be used as an index to look up and fill in those missing values. the input data looks like this: c1 c2 id 0 10.0 a 1 NaN b 2 30.0 c 3 10.0 a 4 20.0 b 5 NaN c desired output: c1 c2 0 10 a 1 20 b 2 30 c But how to do this? Here is the code to generate the example data: import pandas as pd df = pd.DataFrame({ 'c1': [10

问题 I want to duplicate a form with 3 subforms - to explain it simple: imagine a recipe (main form: some general data; sub form 1: list of ingredients, sub form 2: instructions; sub form 3: prices; sometimes the recipes change only the type of flour, so I don't want to type everything again but just have the same form with a new uniqe ID and this one change in the ingredients list) duplicating the main form is easy, but the sub forms are empty. there are some ideas i found online, but it seems