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  2. You can define lmap function (on the analogy of python2's imap) that returns list: Then calling lmap instead of map will do the job: lmap(str, x) is shorter by 5 characters (30% in this case) than list(map(str, x)) and is certainly shorter than [str(v) for v in x]. You may create similar functions for filter too.

  3. Make a list - Computer - Google Keep Help

    support.google.com/keep/answer/6395451

    Choose a list. Point to the item you want to move. At the left, click and hold Move. Drag the item where you want. You can update settings to add new checkboxes to the top or bottom of a list. On your computer, go to Google Keep. At the top right, click Settings Settings. Under "Notes and Lists," you can check or uncheck "Add new items to the ...

  4. Agree with @Bogdan. This answer creates a string in which the list elements are joined together with no whitespace or comma in between. You can use ', '.join(list1) to join the elements of the list with comma and whitespace or ' '.join(to) to join with only white space –

  5. 1. The method shown in the top answer (lst[-1]) is the most Pythonic way to get the last element of a list. Yet another way is to use collections.deque from the standard library. The key is to pass the maxlen=1 parameter so that only the last element of the list remains in it. from collections import deque.

  6. This makes indexing a list a[i] an operation whose cost is independent of the size of the list or the value of the index. When items are appended or inserted, the array of references is resized. Some algorithm is applied to improve the performance of appending items repeatedly; when the array must be grown, some extra space is allocated so the ...

  7. Get a list from Pandas DataFrame column headers

    stackoverflow.com/questions/19482970

    Create a list of keys/columns - object method to_list() and the Pythonic way: my_dataframe.keys().to_list() list(my_dataframe.keys()) Basic iteration on a DataFrame returns column labels: [column for column in my_dataframe] Do not convert a DataFrame into a list, just to get the column labels.

  8. The three forms of looping are nearly identical. The enhanced for loop:. for (E element : list) { . . . } is, according to the Java Language Specification, identical in effect to the explicit use of an iterator with a traditional for loop.

  9. slice - How slicing in Python works - Stack Overflow

    stackoverflow.com/questions/509211

    Here is the logical equivalent code in Python. This function takes a Python object and optional parameters for slicing and returns the start, stop, step, and slice length for the requested slice. def py_slice_get_indices_ex(obj, start=None, stop=None, step=None): length = len(obj) if step is None: step = 1.

  10. To select rows not in list_of_values, negate isin()/in: df[~df['A'].isin(list_of_values)] df.query("A not in @list_of_values") # df.query("A != @list_of_values") 5. Select rows where multiple columns are in list_of_values. If you want to filter using both (or multiple) columns, there's any() and all() to reduce columns (axis=1) depending on the ...

  11. Use their links to know more about them, I.E: to know which fits better your needs. The 3 most commonly used ones probably are: List<String> supplierNames1 = new ArrayList<String> (); List<String> supplierNames2 = new LinkedList<String> (); List<String> supplierNames3 = new Vector<String> (); Bonus: You can also instantiate it with values, in ...