The first way works for a list or a string; the second way only works for a list, because slice assignment isn't allowed for strings. Other than that I think the only difference is speed: it looks like it's a little faster the first way. Try it yourself with timeit.timeit () or preferably timeit.repeat ().

Dec 16, 2011 · How can I create a list which contains only zeros? I want to be able to create a zeros list for each int in range(10) For example, if the int in the range was 4 I will get: [0,0,0,0] and for 7: ...

Caveats Linear time-complexity in list length An index call checks every element of the list in order, until it finds a match. If the list is long, and if there is no guarantee that the value will be near the beginning, this can slow down the code. This problem can only be completely avoided by using a different data structure.

Sorted list: [20.455, 23.455, 24.455, 28.455] Are you sure you are not verifying list instead of sortedList [in above example] i.e. you are storing the result of stream() in a new List object and verifying that object?

Sep 20, 2010 · What is the syntax to insert one list into another list in python? [duplicate] Asked 14 years, 10 months ago Modified 6 years, 1 month ago Viewed 349k times

Dec 3, 2016 · If your list of lists comes from a nested list comprehension, the problem can be solved more simply/directly by fixing the comprehension; please see How can I get a flat result from a list comprehension instead of a nested list?. The most popular solutions here generally only flatten one "level" of the nested list. See Flatten an irregular (arbitrarily nested) list of lists …

Use a list of values to select rows from a Pandas dataframe Asked 12 years, 11 months ago Modified 4 months ago Viewed 1.8m times

Jul 8, 2018 · Is there a way in Python to list all installed packages and their versions? I know I can go inside python/Lib/site-packages and see what files and directories exist, but I find this very awkward. ...

Dec 22, 2017 · You can get the unique values in the whole df with this one-liner: pd.Series(df.values.flatten()).unique() You basically transform your df to a numpy array, flatten and come back to a pandas Series, so you can use unique(). However, types might be transformed along the way if you have multiple types in your original df, so be careful.

Sep 14, 2015 · Another common mistake is to initialize a list but try to assign values to it using a key. The initialization probably happened dynamically and it's not clear later on that it's in fact a list. For example, in the following case, d is initialized as a …