[Tutor] weird lambda expression -- can someone help me understand how this works

Michael Crawford dalupus at gmail.com
Sat Dec 14 03:38:27 CET 2013


Ah yes I see it.   I forgot you can pass around functions in python.

Thanks for the help,
Mike



On Dec 13, 2013, at 9:29 PM, Amit Saha <amitsaha.in at gmail.com> wrote:

> On Sat, Dec 14, 2013 at 12:14 PM, Michael Crawford <dalupus at gmail.com> wrote:
>> I found this piece of code on github
>> 
>> https://gist.github.com/kljensen/5452382
>> 
>> def one_hot_dataframe(data, cols, replace=False):
>>    """ Takes a dataframe and a list of columns that need to be encoded.
>>        Returns a 3-tuple comprising the data, the vectorized data,
>>        and the fitted vectorizor.
>>    """
>>    vec = DictVectorizer()
>>    mkdict = lambda row: dict((col, row[col]) for col in cols)
>> #<<<<<<<<<<<<<<<<<<
>>    vecData = pandas.DataFrame(vec.fit_transform(data[cols].apply(mkdict,
>> axis=1)).toarray())
>>    vecData.columns = vec.get_feature_names()
>>    vecData.index = data.index
>>    if replace is True:
>>        data = data.drop(cols, axis=1)
>>        data = data.join(vecData)
>>    return (data, vecData, vec)
>> 
>> I don't understand how that lambda expression works.
>> For starters where did row come from?
>> How did it know it was working on data?
> 
> Consider this simple example:
> 
>>>> l = lambda x: x**2
>>>> apply(l, (3,))
> 9
> 
> A lambda is an anonymous function. So, when you use apply(), the
> lambda, l gets the value 3 in x and then returns x**2 which is 9 in
> this case.
> 
> Hope this helps you.
> 
> Best,
> Amit.

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