![]() ![]() The above line of code applies the pd.read_csv function to each filename in csv_files – thus, reading in each CSV file’s data. We could use a list comprehension to read in each of the files in one line of code:ĭfs = Suppose, for example, that we have a list of CSV files like below.Ĭsv_files = Other ways we might use a list comprehension might include reading in a collection of data frames from CSV files. The above code will create a new list, words, where each element is the 0th character of the corresponding elements in the words list, “z”, “o”, and “p.” Reading in all the CSV files in a directory – with a list comprehension List comprehensions can also be constructed on lists of strings. Prior to the for keyword, we code the operation we want to perform on each value, num, in the list – in this case that is just num * 2.Īnother simple math operation might be something like this: ![]() Effectively, the above code is looping through each value in sample_list (where each value is called num). New_list = Ībove we define a list by enclosing brackets around a single-line for loop of sorts. ![]() A simplified way to accomplish the same result is by using a list comprehension like this: This would create a new list (called new_list) where each element is double each element in sample_list. Without list comprehensions, we could do something like the following: For instance, suppose we wanted to double every element in a list. The result of a list comprehension is also a list. List comprehensions provide a compact way of defining a list by looping through the elements of another list or some other data structure. #Python list comprehension how toThis tutorial will walk through what they are, how they work, and several examples of how to use them. List comprehensions are one of the coolest features of Python. Click here for a comprehensive tutorial on lists. ![]()
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