duplicates

I have a pandas dataframe as follows: A B C 1 2 x 1 2 y 3 4 z 3 5 x I want that only 1 row remains of rows that share the same values in specific columns. In the example above I mean columns A and B . In other words, if the values of columns A and B occur more than once in the dataframe, only one row should remain (which one does not matter). FWIW: the maximum number of so called duplicate rows (that is, where column A and B are the same) is 2. The result should looke like this: A B C 1 2 x 3 4 z 3 5 x or A B C 1 2 y 3 4 z 3 5 x Use drop_duplicates with parameter subset , for keeping only last

I have the following Python 2.7 dictionary data structure (I do not control source data - comes from another system as is): {112762853378: {'dst': ['10.121.4.136'], 'src': ['1.2.3.4'], 'alias': ['www.example.com'] }, 112762853385: {'dst': ['10.121.4.136'], 'src': ['1.2.3.4'], 'alias': ['www.example.com'] }, 112760496444: {'dst': ['10.121.4.136'], 'src': ['1.2.3.4'] }, 112760496502: {'dst': ['10.122.195.34'], 'src': ['4.3.2.1'] }, 112765083670: ... } The dictionary keys will always be unique. Dst, src, and alias can be duplicates. All records will always have a dst and src but not every record

I have an array of integers that I need to remove duplicates from while maintaining the order of the first occurrence of each integer. I can see doing it like this, but imagine there is a better way that makes use of STL algorithms better? The insertion is out of my control, so I cannot check for duplicates before inserting. int unsortedRemoveDuplicates(std::vector<int> &numbers) { std::set<int> uniqueNumbers; std::vector<int>::iterator allItr = numbers.begin(); std::vector<int>::iterator unique = allItr; std::vector<int>::iterator endItr = numbers.end(); for (; allItr != endItr; ++allItr) {

I've got a list of objects List[Object] which are all instantiated from the same class. This class has a field which must be unique Object.property . What is the cleanest way to iterate the list of objects and remove all objects(but the first) with the same property? IttayD list.groupBy(_.property).map(_._2.head) Explanation: The groupBy method accepts a function that converts an element to a key for grouping. _.property is just shorthand for elem: Object => elem.property (the compiler generates a unique name, something like x$1 ). So now we have a map Map[Property, List[Object]] . A Map[K,V]