I know there are a number of topics on this question, but none of the methods worked for me so I\'m posting about my specific situation
I have a dataframe that looks
You can also try using apply
with get
method of dictionary
, seems to be little faster than replace
:
data['sex'] = data['sex'].apply({1:'Male', 0:'Female'}.get)
Testing with timeit
:
%%timeit
data['sex'].replace([0,1],['Female','Male'],inplace=True)
Result:
The slowest run took 5.83 times longer than the fastest. This could mean that an intermediate result is being cached.
1000 loops, best of 3: 510 µs per loop
Using apply
:
%%timeit
data['sex'] = data['sex'].apply({1:'Male', 0:'Female'}.get)
Result:
The slowest run took 5.92 times longer than the fastest. This could mean that an intermediate result is being cached.
1000 loops, best of 3: 331 µs per loop
Note: apply
with dictionary should be used if all the possible values of the columns in the dataframe are defined in the dictionary else, it will have empty for those not defined in dictionary.