不在 matplotlib 中绘制“零”或将零更改为无 [Python]
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Not plotting 'zero' in matplotlib or change zero to None [Python]
提问by Ashleigh Clayton
I have the code below and I would like to convert all zero's in the data to None's (as I do not want to plot the data here in matplotlib). However, the code is notworking and 0.is still being printed
我有下面的代码，我想将数据中的所有零转换为None's （因为我不想在 matplotlib 中绘制数据）。但是，代码不起作用并且0.仍在打印
sd_rel_track_sum=np.sum(sd_rel_track, axis=1)
for i in sd_rel_track_sum:
print i
if i==0:
i=None
return sd_rel_track_sum
Can anyone think of a solution to this. Or just an answer for how I can transfer all 0 to None. Or just not plot the zero values in Matplotlib.
任何人都可以想到解决这个问题的方法。或者只是我如何将所有 0 转移到None. 或者只是不在 Matplotlib 中绘制零值。
采纳答案by tamasgal
Using numpy is of course the better choice, unless you have any good reasons not to use it ;) For that, see Daniel's answer.
使用 numpy 当然是更好的选择，除非您有充分的理由不使用它；) 为此，请参阅 Daniel 的回答。
If you want to have a bare Python solution, you might do something like this:
如果你想要一个裸 Python 解决方案，你可以这样做：
values = [3, 5, 0, 3, 5, 1, 4, 0, 9]
def zero_to_nan(values):
"""Replace every 0 with 'nan' and return a copy."""
return [float('nan') if x==0 else x for x in values]
print(zero_to_nan(values))
gives you:
给你：
[3, 5, nan, 3, 5, 1, 4, nan, 9]
Matplotlib won't plot nan(not a number) values.
Matplotlib 不会绘制nan（不是数字）值。
回答by Daniel
Why not use numpy for this?
为什么不为此使用 numpy？
>>> values = np.array([3, 5, 0, 3, 5, 1, 4, 0, 9], dtype=np.double)
>>> values[ values==0 ] = np.nan
>>> values
array([ 3., 5., nan, 3., 5., 1., 4., nan, 9.])
It should be noted that values cannot be an integer type array.
需要注意的是，values 不能是整数类型的数组。
