Filtering the dataframe with conditions in Pandas and reaching the rest of the dataframe (.loc)-CodePudding

I would like to create another dataframe with a condition from one column. This method I am trying is working:

   Y = X.loc[(X['ColumnnA'] == "22.33.44.55")
                                                  | (X['ColumnnA'] == "12.12.32.44") 
                                                  | (X['ColumnnA'] == "45.142.22.22") 
                                                  | (X['ColumnnA'] == "55.197.55.8") 
                                                  | (X['ColumnnA'] == "44.44.211.254") 
                                                  | (X['ColumnnA'] == "33.44.234.83") 
                                                  | (X['ColumnnA'] == "33.33.221.240") 
                                                  | (X['ColumnnA'] == "33.33.33.1") 
                                                 ]

But with .loc function, I cannot use this:

restdataframe = X[~Y]
Y=X[Y]

How can I use this with .loc?

Strange but I was using the below method last week and it was working for another dataframe, with the same columns now this runs but it provides me a wrong "shape". With .loc, it gives a correct answer. I want to understand what I am doing wrong with below code? Why it does not work properly?

Y = (X['ColumnnA'] == "22.33.44.55")
| (X['ColumnnA'] == "12.12.32.44") 
| (X['ColumnnA'] == "45.142.22.22") 
| (X['ColumnnA'] == "55.197.55.8") 
| (X['ColumnnA'] == "44.44.211.254") 
| (X['ColumnnA'] == "33.44.234.83") 
| (X['ColumnnA'] == "33.33.221.240") 
| (X['ColumnnA'] == "33.33.33.1")

Note: I run it in one line because of the invalid syntax

Example of X:

CodePudding user response：

Without code to reproduce you X dataframe it is hard to say for sure, but you probably want to use:

restdataframe = X[X!=Y]
Y = X[X==Y]

When you use Y = X.loc[.....] you dont create a mask but select the values from X which meet you conditions. Therefore you have to recreate a mask to make your selection from X. You can do this by comparing where X and Y are/arent the same.

Alternatively you can create Y as a mask:

Y = ((X['ColumnnA'] == "22.33.44.55")
| (X['ColumnnA'] == "12.12.32.44") 
| (X['ColumnnA'] == "45.142.22.22") 
| (X['ColumnnA'] == "55.197.55.8") 
| (X['ColumnnA'] == "44.44.211.254") 
| (X['ColumnnA'] == "33.44.234.83") 
| (X['ColumnnA'] == "33.33.221.240") 
| (X['ColumnnA'] == "33.33.33.1"))

then run your original:

restdataframe = X[~Y]
Y=X[Y]