So, arrays are more efficient for large datasets of numbers. 2019-07-14T02:30:58.24Z+00:00 ... I think you (meant)want an list with the first 30 cells already filled. So ... An example to where this could be used is in Fibonacci sequence. See problem 2 in Project Euler ... That's a rather baroque way of initialising a list. Try f = [0] * 30 instead. 2010-12-18T06:24:00.68Z+00:00 ... Is not the same than a = range(10) from @slehar anwer? Love python... More on stackoverflow.com

Another problem you have is if i== 2 or 4 or 7: as it doesn't work the way you think it does. Replace it with if i in {2, 4, 7}: and it'll work. On another note, these are technically not arrays but lists. "What's the difference?", I hear you ask; arrays are homogeneous, lists are heterogeneous. In practice this means arrays contain data of a single type, while lists can contain data of multiple types. Python does have arrays, but the built-in one you basically never see used (array.array) and Numpy arrays aren't built-in though they're common in heavy number crunching workloads. EDIT: As for how I'd write this code; data = [] for idx in range(10): if idx in {2, 4, 7}: data.append('orange') else: data.append('white') for word in data: print(word) That first loop could further be condensed into data = [ 'orange' if idx in {2, 4, 7} else 'white' for idx in range(10) ] or, as a one-liner (though not preferably): data = ['orange' if idx in {2, 4, 7} else 'white' for idx in range(10)] More on reddit.com

“Array” is an ambiguous term in Python and best not used. Most beginners use it to refer to the list type, but are unaware that there is actually an array.array type in the standard library as well. More on reddit.com

Arrays really aren't a thing in python. There are lists [], tuples (), and dictionaries {}. All of them can hold pretty much any data type and you can actually intermix data types. As far as strings and a csv--if it is a database like structure yes you can store data in almost any of the primary Python data structures. Throwing them into a list of lists could be one way, another would be a list of dictionaries. Using named tuples may be a really good option but that gets a little more into stuff. Pandas is also probably a good route--but again if you're asking about arrays vs. lists that is probably going beyond what you are looking for. Feel free to PM me if you need clarification. More on reddit.com