I’m trying to create duplicate rows during a dataframe on conditions. For example, I have this Dataframe. And I would like to get the following output: Answer For pandas 0.25+ is possible use DataFrame.explode with splitted values by Series.str.split and for remark column list comprehension with filtering: And we get the following result:
Tag: duplicates
Remove duplicates and combine multiple lists into one?
How do I remove duplicates and combine multiple lists into one like so: function([[“hello”,”me.txt”],[“good”,”me.txt”],[“good”,”money.txt”], [“rep”, “money.txt”]]) should return exactly: Answer Create a empty array push the index 0 from childs arrays and join to convert all values to a string separate by space .
Count duplicate lists inside a list
I want the result to be 2 since number of duplicate lists are 2 in total. How do I do that? I have done something like this But the count value is 1 as it returns matched lists. How do I get the total number of duplicate lists? Answer Solution You can use collections.Counter if your sub-lists only contain numbers
Checking if a list has duplicate lists
Given a list of lists, I want to make sure that there are no two lists that have the same values and order. For instance with my_list = [[1, 2, 4, 6, 10], [12, 33, 81, 95, 110], [1, 2, 4, 6, 10]] it is supposed to return me the existence of duplicate lists, i.e. [1, 2, 4, 6, 10].
Remove duplicates from a dataframe in PySpark
I’m messing around with dataframes in pyspark 1.4 locally and am having issues getting the dropDuplicates method to work. It keeps returning the error: “AttributeError: ‘list’ object has no attribute ‘dropDuplicates'” Not quite sure why as I seem to be following the syntax in the latest documentation. Answer It is not an import problem. You simply call .dropDuplicates() on a
Remove duplicates by columns A, keeping the row with the highest value in column B
I have a dataframe with repeat values in column A. I want to drop duplicates, keeping the row with the highest value in column B. So this: Should turn into this: I’m guessing there’s probably an easy way to do this—maybe as easy as sorting the DataFrame before dropping duplicates—but I don’t know groupby’s internal logic well enough to figure
How can I remove duplicate words in a string with Python?
Following example: How can I remove the second two duplicates “calvin” and “klein”? The result should look like only the second duplicates should be removed and the sequence of the words should not be changed! Answer
How do I remove duplicates from a list, while preserving order?
How do I remove duplicates from a list, while preserving order? Using a set to remove duplicates destroys the original order. Is there a built-in or a Pythonic idiom? Answer Here you have some alternatives: http://www.peterbe.com/plog/uniqifiers-benchmark Fastest one: Why assign seen.add to seen_add instead of just calling seen.add? Python is a dynamic language, and resolving seen.add each iteration is more