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Coerce function isn't columns-only #114
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If using in other modules, should the "_" of |
Great question! Think about what def coerce(data, cast_to=numpy.float64):
if isinstance(data, pandas.DataFrame):
for column in data.columns:
data[column] = coerce(data[column], cast_to=cast_to)
return data
else:
try:
return data.astype(cast_to)
except:
return data |
Aha. This makes sense. Would it be a good idea to change
it might instead look like:
but Also, how do you get the syntax highlighting in this markdown? |
I'm OK defining things recursively in the pattern I've shown you. That, generally, is quite useful! Polymorphic functions are very good things, especially when they are quite general. I am happy to have wide-ranging changes that improve the library 😄
When you use three ticks for code blocks, put the name of the language you want to highlight in at the end of the three ticks. def do_something():
for i in range(1, n):
print(i) Julia: function do_something(n)
for i in 1:n
println(i)
end
end |
So, to make sure I'm comprehending, you're for the idea of changing def test():
print("Science!") Cooooooool. Thanks! |
yep! |
Is it valid to have the tuple |
yes! |
The _coerce function can take in multiple columns at once. The docstring and argument name (
column
vscolumns
) say it can only deal with a single column. Is this something that should be changed?The text was updated successfully, but these errors were encountered: