Pandas - How can I change the values of a column based on a given non-python dictionary?

Question

I have a dataframe that looks like this (i've filtered it down to the important parts):

              INC_KEY               PTOCCUPATIONALINDUSTRY
96       170000016620                       Other Services
127      170000016651                       Other Services
170      170000016694                        Manufacturing
181      170000016706                         Construction
268      170000016793                       Other Services

I was also given a 'dictionary' (not a python dictionary), that looks like this:

My task is to convert the values in PTOCCUPATIONALINDUSTRY to the numbers that you see in the dictionary. Is there an easy way to do this? Or do I need to manually do if statements for each value?

The reason I'm looking for a shortcut is because I need to do this exact task over ~30 different columns, so it would take forever to do it manually.

in what form is the dictionary presented? Is this a txt file? — padu, Sep 18 '21 at 15:05
Presumably you'd need to turn that text file/document/structure into a python dictionary. Then the standard pandas `map` replace` operations would work as normal. — Henry Ecker, Sep 18 '21 at 15:05

score 0 · Accepted Answer · answered Sep 18 '21 at 15:09

0

Create your dict :

map_dict = {"Finance, Insurance, and Real Estate": 1, "etc...}

Then, simply do :

df["PTOCCUPATIONALINDUSTRY"] = df["PTOCCUPATIONALINDUSTRY"].map(map_dict)

answered Sep 18 '21 at 15:09

Odhian

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Pandas - How can I change the values of a column based on a given non-python dictionary?

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