The problem is that pd.notnull([‘foo’, ‘bar’]) operates elementwise and returns array([ True, True], dtype=bool). Your if condition trys to convert that to a boolean, and that’s when you get the exception. To fix it, you could simply wrap the isnull statement with np.all: df[[‘A’,’C’]].apply(lambda x: my_func(x) if(np.all(pd.notnull(x[1]))) else x, axis = 1) Now you’ll see … Read more
It’s Array.prototype.push, not Array.push
pandas.core.groupby.GroupBy.apply does NOT have named parameter args, but pandas.DataFrame.apply does have it. So try this: df.groupby(‘columnName’).apply(lambda x: myFunction(x, arg1)) or as suggested by @Zero: df.groupby(‘columnName’).apply(myFunction, (‘arg1’)) Demo: In [82]: df = pd.DataFrame(np.random.randint(5,size=(5,3)), columns=list(‘abc’)) In [83]: df Out[83]: a b c 0 0 3 1 1 0 3 4 2 3 0 4 3 4 2 … Read more
try this : t[‘combined’]= t.values.tolist() t Out[50]: A B C D combined 0 hello 1 GOOD long.kw [hello, 1, GOOD, long.kw] 1 1.20 chipotle NaN bingo [1.2, chipotle, nan, bingo] 2 various NaN 3000 123.46 [various, nan, 3000, 123.456]
Source code is here. exports/require are not keywords, but global variables. Your main script is wrapped before start in a function which has all the globals like require, process etc in its context. Note that while module.js itself is using require(), that’s a different require function, and it is defined in the file called “node.js” … Read more