I have list with different types of data (string, int, etc.). I need to create a new list with, for example, only int elements, and another list with only string elements. How to do it?
We can use the pandas. DataFrame. select_dtypes(include=None, exclude=None) method to select columns based on their data types. The method accepts either a list or a single data type in the parameters include and exclude.
Filter a list of string using filter() method. filter() method accepts two parameters. The first parameter takes a function name or None and the second parameter takes the name of the list variable as values. filter() method stores those data from the list if it returns true, otherwise, it discards the data.
You can accomplish this with list comprehension:
integers = [elm for elm in data if isinstance(elm, int)]
Where data
is the data. What the above does is create a new list, populate it with elements of data
(elm
) that meet the condition after the if
, which is checking if element is instance of an int
. You can also use filter
:
integers = list(filter(lambda elm: isinstance(elm, int), data))
The above will filter out elements based on the passed lambda, which filters out all non-integers. You can then apply it to the strings too, using isinstance(elm, str)
to check if instance of string.
Sort the list by type, and then use groupby
to group it:
>>> import itertools
>>> l = ['a', 1, 2, 'b', 'e', 9.2, 'l']
>>> l.sort(key=lambda x: str(type(x)))
>>> lists = [list(v) for k,v in itertools.groupby(l, lambda x: str(type(x)))]
>>> lists
[[9.2], [1, 2], ['a', 'b', 'e', 'l']]
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