lambda x,y: x*y is an anonymous function otherwise equivalent to
def foo(x, y):
return x*y
To understand its use in reduce(lambda ...), consider the example from the docs:
reduce(lambda x, y: x+y, [1, 2, 3, 4, 5]) calculates ((((1+2)+3)+4)+5).
Similarly, reduce(lambda x,y:x*y,[3,4,5]) calculates ((3*4)*5).
Answer from unutbu on Stack Overflow
Why do you need to state both 'x' and 'y' before the ':'?
Because a lambda is (conceptually) the same as a function, just written inline. Your example is equivalent to
def f(x, y) : return x + y
just without binding it to a name like f.
Also how do you make it return multiple arguments?
The same way like with a function. Preferably, you return a tuple:
lambda x, y: (x+y, x-y)
Or a list, or a class, or whatever.
The thing with self.entry_1.bind should be answered by Demosthenex.
I believe bind always tries to send an event parameter. Try:
self.entry_1.bind("<Return>", lambda event: self.calculate(self.buttonOut_1.grid_info(), 1))
You accept the parameter and never use it.
Creating a simple lambda function that checks if 2 variables exist!
How to write a lambda function that is conditional on two variables (columns) in python - Stack Overflow
python - defining a lambda function with two arguments - Stack Overflow
Need some help with variables in qtile
You've fallen into a trap that often catches a lot of people out (me included).
If you loop over a variable and want to pass that specific value to a lambda function, you need to do something like lambda value=i: logger.warning(f"{value}").
I want to get better at creating lambda function, I don't understand the format of how to create one yet so I tried with this, but its not working :( I want to make this into a single line lambda function:
var_1 = 1
var_2 = 'lettuce'
def check_exists(var1=None,var2=None):
if var1 and var2:
return True
else:
return FalseThis didn't work, I'm not sure why, could someone explain?
lambda var_1, var_2 : if var_1 and var_2 else False
I see the error: SyntaxError: invalid syntax
Use where:
df['dummyVar '] = df['x'].where((df['x'] > 100) & (df['y'] < 50), df['y'])
This will be much faster than performing an apply operation as it is vectorised.
Like this:
f = lambda x, y: x if x>100 and y<50 else y
Lambda(s) in Python are equivalent to a normal function definition.
def f(x, y):
return x if x>100 and y<50 else y
NB: The body of a Lambda must be a valid expression. This means you cannot use things like: return for example; a Lambda will return the last expression evaluated.
For some good reading see:
- Defining Functions
- Lambdas
One way to do this is the following:
power = lambda x, n: math.pow(x,n)
list = [1,2,3,4,5]
map(power,list,[2]*len(list))
The expression [2]*len(list) creates another list the same length as your existing one, where each element contains the value 2. The map function takes an element from each of its input lists and applies that to your power function.
Another way is:
power = lambda x, n: math.pow(x,n)
list = [1,2,3,4,5]
map(lambda x: power(x, 2),list)
which uses partial application to create a second lambda function that takes only one argument and raises it to the power 2.
Note that you should avoid using the name list as a variable because it is the name of the built-in Python list type.
import math
power = lambda n: lambda x: math.pow(x,n)
list = [1,2,3,4,5]
map(power(2),list)