duplicates

问题 I would like to remove duplicate dicts in list. Specifically, if two dict having the same content under the key paper_title, maintain one and remove the other duplicate. For example, given the list below test_list = [{"paper_title": 'This is duplicate', 'Paper_year': 2}, \ {"paper_title": 'This is duplicate', 'Paper_year': 3}, \ {"paper_title": 'Unique One', 'Paper_year': 3}, \ {"paper_title": 'Unique two', 'Paper_year': 3}] It should return return_value = [{"paper_title": 'This is duplicate'

问题 x1 = [5, 5] x2 = [1, 5, 5, 2] x3 = [5, 5, 1, 2, 5, 5] x4 = [5, 5, 1, 5, 5, 2, 5, 5] x5 = [5, -5] x6 = [1, 2, 3, 4] x7 = [5, 5, 5, 5, 5, 5] How do I remove one of the duplicate values that are next to each other on every list? After all one of the duplicate values that are next to each other are removed, they should look like this: x1 = [5] x2 = [1, 5, 2] x3 = [5, 1, 2, 5] x4 = [5, 1, 5, 2, 5] x5 = [5, -5] x6 = [1, 2, 3, 4] x7 = [5] 回答1: When there can be three or more values in a row and only

问题 x1 = [5, 5] x2 = [1, 5, 5, 2] x3 = [5, 5, 1, 2, 5, 5] x4 = [5, 5, 1, 5, 5, 2, 5, 5] x5 = [5, -5] x6 = [1, 2, 3, 4] x7 = [5, 5, 5, 5, 5, 5] How do I remove one of the duplicate values that are next to each other on every list? After all one of the duplicate values that are next to each other are removed, they should look like this: x1 = [5] x2 = [1, 5, 2] x3 = [5, 1, 2, 5] x4 = [5, 1, 5, 2, 5] x5 = [5, -5] x6 = [1, 2, 3, 4] x7 = [5] 回答1: When there can be three or more values in a row and only

问题 I have a dataframe containing a set of parts and test results. The parts are tested on 3 sites (North Centre and South). Sometimes those parts are re-tested. I want to eventually create some charts that compare the results from the first time that a part was tested with the second (or third, etc.) time that it was tested, e.g. to look at tester repeatability. As an example, I've come up with the below code. I've explicitly removed the "Experiment" column from the morley data set, as this is

问题 I have a correlation matrix that i melted into a dataframe so now i have the following for example: First Second Value A B 0.5 B A 0.5 A C 0.2 i want to delete only one of the first two rows. What would be the way to do it? 回答1: Use: #if want select columns by columns names m = ~pd.DataFrame(np.sort(df[['First','Second']], axis=1)).duplicated() #if want select columns by positons #m = ~pd.DataFrame(np.sort(df.iloc[:,:2], axis=1)).duplicated() print (m) 0 True 1 False 2 True dtype: bool df =

问题 I have a correlation matrix that i melted into a dataframe so now i have the following for example: First Second Value A B 0.5 B A 0.5 A C 0.2 i want to delete only one of the first two rows. What would be the way to do it? 回答1: Use: #if want select columns by columns names m = ~pd.DataFrame(np.sort(df[['First','Second']], axis=1)).duplicated() #if want select columns by positons #m = ~pd.DataFrame(np.sort(df.iloc[:,:2], axis=1)).duplicated() print (m) 0 True 1 False 2 True dtype: bool df =

问题 I am going to work on some projects to deal with entity deduplication. Datasets (one or more) which may contain duplicate entity. In the realtime, entity may represent the name, address, country, email, social media id in the different form. My goal is to identify that these are possible duplicates based on different weightage for the different entity Info. I am trying to look for a library that is open-source & preferably written in Java. As I need to process the millions of data, I need to

问题 How can I keep my duplicates, but remove unique values based on one column(qol)? ID qol Sat A 7 6 A 7 5 B 3 3 B 3 4 B 1 7 C 2 7 c 1 2 But I need this: ID qol Sat A 7 6 A 7 5 B 3 3 B 3 4 What can I do? 回答1: dplyr solution: library(dplyr) ID <- c("A", "A", "B", "B", "B", "C", "c") qol <- c(7,7,3,3,1,2,1) Sat <- c(6,5,3,4,7,7,2) test_df <- data.frame(cbind(ID, qol, Sat)) filtered_df <- test_df %>% group_by(qol) %>% filter(n()>1) Please note that this will return ID qol Sat 1 A 7 6 2 A 7 5 3 B 3

问题 How can I keep my duplicates, but remove unique values based on one column(qol)? ID qol Sat A 7 6 A 7 5 B 3 3 B 3 4 B 1 7 C 2 7 c 1 2 But I need this: ID qol Sat A 7 6 A 7 5 B 3 3 B 3 4 What can I do? 回答1: dplyr solution: library(dplyr) ID <- c("A", "A", "B", "B", "B", "C", "c") qol <- c(7,7,3,3,1,2,1) Sat <- c(6,5,3,4,7,7,2) test_df <- data.frame(cbind(ID, qol, Sat)) filtered_df <- test_df %>% group_by(qol) %>% filter(n()>1) Please note that this will return ID qol Sat 1 A 7 6 2 A 7 5 3 B 3

问题 I have a list of dictionaries in Python 3.5.2 that I am attempting to "deduplicate". All of the dictionaries are unique, but there is a specific key I would like to deduplicate on, keeping the dictionary with the most non-null values. For example, I have the following list of dictionaries: d1 = {"id":"a", "foo":"bar", "baz":"bat"} d2 = {"id":"b", "foo":"bar", "baz":None} d3 = {"id":"a", "foo":"bar", "baz":None} d4 = {"id":"b", "foo":"bar", "baz":"bat"} l = [d1, d2, d3, d4] I would like to