python - 使用 Pandas 过滤 Excel 表格

Question

我已经使用 Pandas 导入了 Excel 表格。该表包含四列，分别代表节点、X、Y 和 Z 数据。我使用了以下脚本:

import pandas as pd
SolidFixity = pd.read_excel('GeomData.xlsx', sheetname = 'SurfaceFixitySolid')

接下来我想做的是使用过滤表过滤此数据帧以选择感兴趣的节点。我使用了这个命令:

SolidFixity.filter(like = '797', axis = 'Nodes')

这不起作用并引发以下错误:

ValueError: No axis named Nodes for object type

我知道有一个名为 Nodes 的轴，因为以下命令:

In[17]SolidFixity.axes

输出以下内容:

Out[17]: 
[RangeIndex(start=0, stop=809, step=1),
 Index(['Nodes', 'X', 'Y ', 'Z'], dtype='object')]

节点就在那里，像太阳一样闪闪发光。

我在这里做错了什么？

Answer 1

看来你需要boolean indexing或query带面具contains或与 797 进行比较以获得精确匹配:

SolidFixity = pd.DataFrame({'Nodes':['797','sds','797 dsd','800','s','79785'],
                            'X':[5,3,6,9,2,4]})

print (SolidFixity)
     Nodes  X
0      797  5
1      sds  3
2  797 dsd  6
3      800  9
4        s  2
5    79785  4

a = SolidFixity[SolidFixity.Nodes.str.contains('797')]
print (a)
     Nodes  X
0      797  5
2  797 dsd  6
5    79785  4

b = SolidFixity[SolidFixity.Nodes == '797']
print (b)
  Nodes  X
0   797  5

b = SolidFixity.query("Nodes =='797'")
print (b)
 Nodes  X
0   797  5

filter函数可能只有轴值:

axis : int or string axis name

The axis to filter on. By default this is the info axis, index for Series, columns for DataFrame

并通过参数返回所有列如、regex和items:

df = pd.DataFrame({'A':list('abcdef'),
                   'B':[4,5,4,5,5,4],
                   'C797':[7,8,9,4,2,3],
                   '797':[1,3,5,7,1,0],
                   'E':[5,3,6,9,2,4],
                   'F':list('aaabbb')})

print (df)
   797  A  B  C797  E  F
0    1  a  4     7  5  a
1    3  b  5     8  3  a
2    5  c  4     9  6  a
3    7  d  5     4  9  b
4    1  e  5     2  2  b
5    0  f  4     3  4  b

a = df.filter(like = '797', axis = 1)
#same as
#a = df.filter(like = '797', axis = 'columns')
print (a)
   797  C797
0    1     7
1    3     8
2    5     9
3    7     4
4    1     2
5    0     3

<小时/>

c = df.filter(items = ['797'], axis = 1)
#same as
#c = df.filter(items = ['797'], axis = 'columns')
print (c)
   797
0    1
1    3
2    5
3    7
4    1
5    0