Compare a list with a date in pandas in Python

Question

Hello I have this list:

b = [[2018-12-14, 2019-01-11, 2019-01-25, 2019-02-08, 2019-02-22, 2019-07-26],
    [2018-06-14, 2018-07-11, 2018-07-25, 2018-08-08, 2018-08-22, 2019-01-26],
    [2017-12-14, 2018-01-11, 2018-01-25, 2018-02-08, 2018-02-22, 2018-07-26]]

dtype: datetime64[ns]]

and I want to know if it's possible to compare this list of dates with another date. I am doing it like this:

r = df.loc[(b[1] > vdate)]

with:

vdate = dt.date(2018, 9, 19)

the output is correct because it select the values that satisfy the condition. But the problem is that I want to do that for all the list values. Something like:

r = df.loc[(b > vdate)] # Without [1]

but this get as an output an error as I expected. I try some for loop and it seems like it works but I am not sure:

g = []
for i in range(len(b)):
    r = df.loc[(b[i] > vdate)]
    g.append(r)

Thank you so much for your time and any help would be perfect.

You want to have boolean value if your date is < than every dates in your list? — Dawid Fieluba, Oct 29 '18 at 14:52
Right now `b` is a list of lists. You may want to use a for loop to go through individual lists — SmitM, Oct 29 '18 at 14:53
@DawidFieluba no, I want to have the values of the df when my date is < than every date in the list. Thank you for taking your time to read it and help — Amartin, Oct 29 '18 at 14:58
@SmitM I try something, I will edit and post it to see if it help. — Amartin, Oct 29 '18 at 15:01
Then find the minimum date in the list and check if the `DataFrame` values are less than that single date. — ALollz, Oct 29 '18 at 15:09

score 1 · Answer 1 · answered Oct 29 '18 at 15:08

1

if you want to go through the entire list just use the following method:

ds['new_list'] = ds['list_dates'].apply(function)

use the .apply () method to process your list through a function

answered Oct 29 '18 at 15:08

Jose Salas

7
2

SantiStSupery · Accepted Answer · 2018-10-29T15:54:56.160

1

One may use the apply function as stated by @Joseph Developer, but a simple list comprehension would not require you to write the function. The following will give you a list of boolean telling you whether or not each date is greater than vdate :

is_after_b = [x > vdate for x in b]

And if you want to include this directly in your DataFrame you may write :

df['is_after_b'] = [ x > vdate for x in df.b]

Assuming that b is a column of df, which btw would make sure that the length of b and your DataFrame's columns match.

EDIT

I did not consider that b was a list of list, you would need to flatten b by using :

flat_b = [item for sublist in b for item in sublist]

And you can now use :

is_after_b = [x > vdate for x in flat_b]

edited Oct 29 '18 at 15:54

answered Oct 29 '18 at 15:21

SantiStSupery

202
3
14

And it is a way to do it if b is not a column of the dataframe? I have a way using iloc[] to get the boolean output as a column but I don't know how to transfor it to the values – Amartin Oct 29 '18 at 15:28
I edited my answer, now it should work flawlessly. The list comprehension is faster than looping and using .loc, for more on this aspect see [this question](https://stackoverflow.com/questions/22108488/are-list-comprehensions-and-functional-functions-faster-than-for-loops) – SantiStSupery Oct 29 '18 at 15:55

Compare a list with a date in pandas in Python

2 Answers2