Python NaN问题
Python NaN问题
提问于 2021-08-19 18:53:19
我正在从由熊猫数据帧生成的CSV中读取多组坐标。坐标集合的长度并不相同，所以它们被填充了NaNs。下面是我想要开始工作的代码：
df=pd.read_csv('contours_20150210.csv') # reading in the dataframe and xy coordinates
c131x=np.asarray(df["contour_131_x"])
c131y=np.asarray(df["contour_131_y"])
c193x=np.asarray(df["contour_193_x"])
c193y=np.asarray(df["contour_193_y"])
c211x=np.asarray(df["contour_211_x"])
c211y=np.asarray(df["contour_211_y"])
nn_193_211=[]
dist_193_211 = distance_matrix(c193,c211) #Computing the distances between all the sets of coordinates
for i in range(len(dist_193_211[:][1])):
nn_193_211.append([np.where(dist_193_211[i] == np.nanmin(dist_193_211[i]))[0][0],np.nanmin(dist_193_211[i])])
# I am looking for the nearest neighbors, both the value of the distance between them and which value that is in the list of coordinates问题是，即使我使用的是np.nanmin，当for循环到达nans时，我也会得到以下错误。
/tmp/ipykernel_3022/578260609.py:2: RuntimeWarning: All-NaN slice encountered
nn_193_211.append([np.where(dist_193_211[i] == np.nanmin(dist_193_211[i]))[0][0],np.nanmin(dist_193_211[i])])
---------------------------------------------------------------------------
IndexError Traceback (most recent call last)
/tmp/ipykernel_3022/578260609.py in <module>
1 for i in range(len(dist_193_211[:][1])):
----> 2 nn_193_211.append([np.where(dist_193_211[i] == np.nanmin(dist_193_211[i]))[0][0],np.nanmin(dist_193_211[i])])
3 print(nn_193_211[0:100])
4 #print(np.max(nn_193_211),np.min(nn_193_211))
IndexError: index 0 is out of bounds for axis 0 with size 0我决定只截断填充nan(它们是数组中唯一的nan，其他地方没有丢失的数据)。因此，我阅读了Python中的nans，并运行了以下测试：
print('c131x: ',c131x)
print('np.nan is np.nan:',np.nan is np.nan)
print('c131x[-1] is np.nan:',c131x[-1] is np.nan)
print(np.where(np.vectorize(c131x) is np.nan))
print(np.where(np.vectorize(c131y) is np.nan))
print(np.where(np.vectorize(c193x) is np.nan))
print(np.where(np.vectorize(c193y) is np.nan))
print(np.where(np.vectorize(c211x) is np.nan))
print(np.where(np.vectorize(c211y) is np.nan))这是输出：
c131x: [-202.79993465 -202.49993494 -202.19993523 ... nan nan
nan]
np.nan is np.nan: True
c131x[-1] is np.nan: False
(array([], dtype=int64),)
(array([], dtype=int64),)
(array([], dtype=int64),)
(array([], dtype=int64),)
(array([], dtype=int64),)
(array([], dtype=int64),)我的理解是np.nan is np.nan和c131x[-1] is np.nan都应该返回True：我是不是遗漏了什么？如果我不能确定can在哪里我就不能对数组进行切片。
回答 1
Stack Overflow用户
回答已采纳
发布于 2021-08-19 19:06:47
BlueBuffalo73的建议给了我一个关于不安全类型转换的错误；然而，我受到这个建议的启发并尝试了
c131x=c131x[:np.where(np.isnan(c131x))[0][0]]
这确实起作用了。我现在有了截断的坐标数组。
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原文链接：
https://stackoverflow.com/questions/68853206
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