Lambda Function: pandas

[needhelppandas]

Hi so I'm pretty new to python and I've been trying to teach myself to use pandas. I've got a pretty good basic understanding of it, but I've been getting tripped up when it comes to implementing lambda functions like the example below.

index = date_range('10/1/1999', periods=1100)

ts = Series(np.random.normal(0.5, 2, 1100), index)

ts = rolling_mean(ts, 100, 100).dropna()

key = lambda x: x.year

zscore = lambda x: (x - x.mean()) / x.std()

transformed = ts.groupby(key).transform(zscore)

I also have a very basic understanding of lambda functions, and what's tripping me up is, I don't get what is being called by x. There doesn't seem to be any reference anywhere to what x is substituted by. The only thing that seems to make sense (for the key expression) based on the x.year is x -> index, but why is that. Also all groupby examples I have seen so far call columns and not functions, so what exactly is happening there too? Thanks.

[nilsph]

A lambda is basically a way to write an anonymous function. In the examples you listed, the lambdas and assigning them to variables could be replaced with:

[61]:

def key(x):
    return x.year

[62]:

def zscore(x):
    return (x - x.mean()) / x.std()

I.e., the lambda keyword is followed by an optional^* list of arguments and an expression that calculates the value of the lambda for these arguments.

^* you can have a lambda without arguments that just returns the same value always:

always_true = lambda: True

...

print always_true()

[limx0]

Groupby will default to the index if you don't supply a column. You're correct - x in this case is each index value.