How to create a new column in a pandas data frame

Question

I am trying to create a new column called "Continent" by grouping the values in another column called "Regions". The only codes that I managed to do are these:

my_data.loc[(my_data ["Region"] == ("Australia and New Zealand")), "Continent"] = "Australia"

But I am having trouble when there is more than one region for a continent. I have done this:

my_data.loc[((my_data ["Region"] == ("Central and Eastern Europe")) & (my_data["Region"] == ("Western Europe"))), "Continent"] = "Europe"

my_data.loc[((my_data ["Region"] == ("Eastern Asia")) & (my_data["Region"] == ("Southeastern Asia"))), "Continent"] = "Asia" & (my_data["Region"] == ("Southern Asia "))), "Continent"] = "Asia"

it seems like it does not recognize the code because when I execute this, it just appears "NaN" in the column, instead of the name of the continent.

Does anybody know what the problem is?

Answer 1

Here is logic problem, never happens one condition AND another one, because test one column.

So need | for bitwise OR :

my_data.loc[((my_data ["Region"] ==  ("Central and Eastern Europe")) | (my_data["Region"] == ("Western Europe"))), "Continent"] = "Europe"

What working same like test by Series.isin :

my_data.loc[my_data ["Region"].isin(["Central and Eastern Europe", "Western Europe"]), "Continent"] = "Europe"