CODEWITHSUNDEEP
pythonpython-2.7pandasdataframe
Tomas
Tomas

Reputation: 305

Python - opposite of __contains__

GENERAL QUESTION

I was wondering if there exists a Python opposite to __contains__ (i.e., something like __notcontains__).

MY EXAMPLE

I need it for the following piece of code:

df_1 = df[(df.id1 != id1_array) | (df.id2.apply(id2_array.__contains__)]
df_2 = df[(df.id1 == id1_array) & (df.id2.apply(id2_array.__notcontains__)]

In other words, in df1 I want only observations for which id1 is not in id1_array1 or id2 is in id2_array, while for df2 I want only observations for which id1 is in id1_array and id2 is not in id2_array.

Who can help me out here? Thanks in advance!

Upvotes: 4

Views: 4312

Answers (5)

Bissdom Technologies
Bissdom Technologies

Reputation: 1

opposite of __contains___

one way to use this as follows:

list.__contains__('ABC') #true if ABC is present in list

not list.__contains__('ABC') # false if ABC is present in list

Upvotes: 0

zar pa
zar pa

Reputation: 1

Sorry for the (very) late response. If what you're tryin' is to analize wether a character is or not in a string, you could check this out! It isn't very optimized but it might work :))

 while yourCharacter == False:
    stringVariable = str(input("text"))

    for characterPosition in range(0, len(stringVariable)):
        characterTest = stringVariable[characterPosition]
        if characterTest == "yourCharacter":
            yourCharacter = True

this (as you probably know), will able you to use the yourCharacter variable to check if the character is in the string or input.

I hope it helps somehow, and again, sorry for the late response :)

Upvotes: 0

EdChum
EdChum

Reputation: 394031

To answer how to do this in pure pandas you can use isin and use the negation operator ~ to invert the boolean series:

df_1 = df[(df.id1 != id1_array) | (df.id2.isin(id2_array)]
df_2 = df[(df.id1 == id1_array) & (~df.id2.isin(id2_array)]

This will be faster than using apply on a larger dataset as isin is vectorised

When using the comparison operators such as == and != this will return True/False where the array values are same/different in the same position. If you are testing just for membership, i.e. does a list of values exist anywhere in the array then use isin this will also return a boolean series where matches are found, to invert the array use ~.

Also as a general rule, avoid using apply unless it's not possible, the reason is that apply is just syntactic sugar to execute a for loop on the df and this isn't vectorised. There are usually ways to achieve the same result without using apply if you dig hard enough.

Upvotes: 3

Samuel
Samuel

Reputation: 4387

EDIT: I didn't notice this was using panda's specifically. My answer may not be accurate.

Generally, the magic functions (anything with __'s before and after) are not meant to be called directly. In this case, __contains__ is referenced by using the in keyword.

>>> a = ['b'] 
>>> 'b' in a 
True 
>>> 'b' not in a 
False

Upvotes: 2

ndou
ndou

Reputation: 1178

No there is no __notcontains__ method or similar. When using x not in y, the method __contains__ is actually used, as shown bellow:

class MyList(list):
    def __contains__(self, x):
        print("__contains__ is called")
        return super().__contains__(x)

l = MyList([1, 2, 3])

1 in l
# __contains__ is called

1 not in l
# __contains__ is called

Upvotes: 2

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