[英]Adding new records to a numpy structured array
这是对numpy数组的早期学习的延续。
从列表的元素创建结构化的数组-然后使用值填充(以下未显示)。
>>> o = ['x','y','z']
>>> import numpy as np
>>> b = np.zeros((len(o),), dtype=[(i,object) for i in o])
>>> b
array([(0, 0, 0, 0, 0), (0, 0, 0, 0, 0), (0, 0, 0, 0, 0)],
dtype=[('x', '|O4'), ('y', '|O4'), ('z', '|O4')])
填充的数组如下所示:
x y z
x 0 1 0
y 1 0 1,5
z 0 1,5 0
1.我们如何在上面添加新的顶点?
2.一旦添加了顶点,将以下数组添加到结构化数组的最干净的过程是什么(注意:并非此数组中的所有顶点都是新的):
d e y
d 0 '1,2' 0
e '1,2' 0 '1'
f 0 '1' 0
预期的输出(请多多包涵):
x y z d e f
x 0 1 0 0 0 0
y 1 0 1,5 0 1 0
z 0 1,5 0 0 0 0
d 0 0 0 0 1,2 0
e 0 1 0 1,2 0 0
f 0 0 0 0 1 0
似乎是python pandas的工作。
>>> import numpy as np
>>> import pandas as pd
>>> data=np.zeros((4,5))
>>> df=pd.DataFrame(data,columns=['x','y','z','a','b'])
>>> df
x y z a b
0 0 0 0 0 0
1 0 0 0 0 0
2 0 0 0 0 0
3 0 0 0 0 0
>>> df['c']=0 #Add a new column
>>> df
x y z a b c
0 0 0 0 0 0 0
1 0 0 0 0 0 0
2 0 0 0 0 0 0
3 0 0 0 0 0 0
>>> new_data=pd.DataFrame([['0','1,2','0'],['1,2','0','1'],['0','1','0']],columns=['d','e','y'])
>>> new_data
d e y
0 0 1,2 0
1 1,2 0 1
2 0 1 0
>>> df.merge(new_data,how='outer') #Merge data
x y z a b c d e
0 0 0 0 0 0 0 NaN NaN
1 0 0 0 0 0 0 NaN NaN
2 0 0 0 0 0 0 NaN NaN
3 0 0 0 0 0 0 NaN NaN
4 NaN 0 NaN NaN NaN NaN 0 1,2
5 NaN 0 NaN NaN NaN NaN 0 1
6 NaN 1 NaN NaN NaN NaN 1,2 0
有很多方法可以合并显示的数据,能否请您更详细地解释结尾数组的外观?
声明:本站的技术帖子网页,遵循CC BY-SA 4.0协议,如果您需要转载,请注明本站网址或者原文地址。任何问题请咨询:yoyou2525@163.com.