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社区首页 >问答首页 >熊猫DataFrame计算

问熊猫DataFrame计算
EN

Stack Overflow用户
提问于 2015-04-17 23:38:10
回答 2查看 2.2K关注 0票数 2

我有一个相当复杂的dataframe，如下所示：

代码语言：javascript
复制
df = pd.DataFrame({'0': {('Total Number of End Points', '0.01um', '0hr'): 12,
  ('Total Number of End Points', '0.1um', '0hr'): 8,
  ('Total Number of End Points', 'Control', '0hr'): 4,
  ('Total Number of End Points', '0.01um', '24hr'): 18,
  ('Total Number of End Points', '0.1um', '24hr'): 12,
  ('Total Number of End Points', 'Control', '24hr'): 6,
  ('Total Vessel Length', '0.01um', '0hr'): 12,
  ('Total Vessel Length', '0.1um', '0hr'): 8,
  ('Total Vessel Length', 'Control', '0hr'): 4,
  ('Total Vessel Length', '0.01um', '24hr'): 18,
  ('Total Vessel Length', '0.1um',  '24hr'): 12,
  ('Total Vessel Length', 'Control',  '24hr'): 6},
  '1': {('Total Number of End Points', '0.01um', '0hr'): 12,
  ('Total Number of End Points', '0.1um', '0hr'): 8,
  ('Total Number of End Points', 'Control', '0hr'): 4,
  ('Total Number of End Points', '0.01um', '24hr'): 18,
  ('Total Number of End Points', '0.1um', '24hr'): 12,
  ('Total Number of End Points', 'Control', '24hr'): 6,
  ('Total Vessel Length', '0.01um', '0hr'): 12,
  ('Total Vessel Length', '0.1um', '0hr'): 8,
  ('Total Vessel Length', 'Control', '0hr'): 4,
  ('Total Vessel Length', '0.01um', '24hr'): 18,
  ('Total Vessel Length', '0.1um',  '24hr'): 12,
  ('Total Vessel Length', 'Control',  '24hr'): 6},
  '2': {('Total Number of End Points', '0.01um', '0hr'): 12,
  ('Total Number of End Points', '0.1um', '0hr'): 8,
  ('Total Number of End Points', 'Control', '0hr'): 4,
  ('Total Number of End Points', '0.01um', '24hr'): 18,
  ('Total Number of End Points', '0.1um', '24hr'): 12,
  ('Total Number of End Points', 'Control', '24hr'): 6,
  ('Total Vessel Length', '0.01um', '0hr'): 12,
  ('Total Vessel Length', '0.1um', '0hr'): 8,
  ('Total Vessel Length', 'Control', '0hr'): 4,
  ('Total Vessel Length', '0.01um', '24hr'): 18,
  ('Total Vessel Length', '0.1um',  '24hr'): 12,
  ('Total Vessel Length', 'Control',  '24hr'): 6}})

print(df)
                                                 0   1   2
        Total Number of End Points 0.01um  0hr   12  12  12
                                           24hr  18  18  18
                                   0.1um   0hr    8   8   8
                                           24hr  12  12  12
                                   Control 0hr    4   4   4
                                           24hr   6   6   6
        Total Vessel Length        0.01um  0hr   12  12  12
                                           24hr  18  18  18
                                   0.1um   0hr    8   8   8
                                           24hr  12  12  12
                                   Control 0hr    4   4   4
                                           24hr   6   6   6

我试图将每个值除以相应控制级别中列的平均值。我试过以下几种方法，但都没有用。

代码语言：javascript
复制
df2 = df.divide(df.xs('Control', level=1).mean(axis=1), axis='index')

我对python和大熊猫非常陌生，所以我倾向于用MS的术语来思考这个问题。

如果在Excel中，A1的公式(“端点总数”、“0.01um”、“0HR”、“0)”看起来如下：

=A1 / AVERAGE($A$5:$C$5)

B1 (“端点总数”、“0.01um”、“0HR”，1)将是：

=B1 / AVERAGE($A$5:$C$5)

A2 (“端点总数”、“0.01um”、“24小时”、“0”)为

=A1 / AVERAGE($A$6:$C$6)

本例的预期结果是：

代码语言：javascript
复制
                                                 0  1  2
        Total Number of End Points 0.01um  0hr   3  3  3
                                           24hr  3  3  3
                                   0.1um   0hr   2  2  2
                                           24hr  2  2  2
                                   Control 0hr   1  1  1
                                           24hr  1  1  1
        Total Vessel Length        0.01um  0hr   3  3  3
                                           24hr  3  3  3
                                   0.1um   0hr   2  2  2
                                           24hr  2  2  2
                                   Control 0hr   1  1  1
                                           24hr  1  1  1

注意:实际数据中有许多索引和列。

pandas
python
python-2.7
EN

回答 2

Stack Overflow用户

发布于 2015-04-18 01:27:12

在它们自己的列中包含Control值是很有帮助的。您可以使用unstack来实现这一点。

代码语言：javascript
复制
df.index.names = ['field', 'type', 'time']
df2 = df.unstack(['type']).swaplevel(0, 1, axis=1)

# type                            0.01um 0.1um Control 0.01um 0.1um Control  \
#                                      0     0       0      1     1       1   
# field                      time                                             
# Total Number of End Points 0hr      12     8       4     12     8       4   
#                            24hr     18    12       6     18    12       6   
# Total Vessel Length        0hr      12     8       4     12     8       4   
#                            24hr     18    12       6     18    12       6   

# type                            0.01um 0.1um Control  
#                                      2     2       2  
# field                      time                       
# Total Number of End Points 0hr      12     8       4  
#                            24hr     18    12       6  
# Total Vessel Length        0hr      12     8       4  
#                            24hr     18    12       6

现在查找每个控件的平均值：

代码语言：javascript
复制
ave = df2['Control'].mean(axis=1)
# field                       time
# Total Number of End Points  0hr     4
#                             24hr    6
# Total Vessel Length         0hr     4
#                             24hr    6
# dtype: float64

正如您所期望的，您可以使用df2.divide来计算所需的结果。确保使用axis=0根据行索引告诉Pandas匹配值(在df2和ave中)。

代码语言：javascript
复制
result = df2.divide(ave, axis=0)
# type                            0.01um 0.1um Control 0.01um 0.1um Control  \
#                                      0     0       0      1     1       1   
# field                      time                                             
# Total Number of End Points 0hr       3     2       1      3     2       1   
#                            24hr      3     2       1      3     2       1   
# Total Vessel Length        0hr       3     2       1      3     2       1   
#                            24hr      3     2       1      3     2       1   

# type                            0.01um 0.1um Control  
#                                      2     2       2  
# field                      time                       
# Total Number of End Points 0hr       3     2       1  
#                            24hr      3     2       1  
# Total Vessel Length        0hr       3     2       1  
#                            24hr      3     2       1

本质上有你所追求的价值。但是，如果您想重新排列DataFrame以使其看起来与您发布的完全相同，那么：

代码语言：javascript
复制
result = result.stack(['type'])
result = result.reorder_levels(['field','type','time'], axis=0)
result = result.reindex(df.index)

收益率

代码语言：javascript
复制
                                         0  1  2
field                      type    time         
Total Number of End Points 0.01um  0hr   3  3  3
                                   24hr  3  3  3
                           0.1um   0hr   2  2  2
                                   24hr  2  2  2
                           Control 0hr   1  1  1
                                   24hr  1  1  1
Total Vessel Length        0.01um  0hr   3  3  3
                                   24hr  3  3  3
                           0.1um   0hr   2  2  2
                                   24hr  2  2  2
                           Control 0hr   1  1  1
                                   24hr  1  1  1

把这一切结合在一起：

代码语言：javascript
复制
df.index.names = ['field', 'type', 'time']
df2 = df.unstack(['type']).swaplevel(0, 1, axis=1)
ave = df2['Control'].mean(axis=1)
result = df2.divide(ave, axis=0)
result = result.stack(['type'])
result = result.reorder_levels(['field','type','time'], axis=0)
result = result.reindex(df.index)
票数 1
EN

Stack Overflow用户

发布于 2015-04-18 00:49:33

这里的问题是熊猫组织起来很容易计算列，这个问题需要从其他行中扣除一行的平均值。熊猫不是为了那样工作而设计的。

但是，您可以使用转置.T轻松地切换行和列，然后它可能更容易处理，实际上控制方式是一个一行。

代码语言：javascript
复制
>>> df.T[(u'Total Vessel Length', u'Control', u'0hr')].mean()
4.0

此4.0来自原始数据中的两个4.0值：

代码语言：javascript
复制
>>> df.T[(u'Total Vessel Length', u'Control', u'0hr')]
a    4
b    4

此时，for循环将处理这个问题。

未经测试：

代码语言：javascript
复制
for primary in (u'Total Vessel Length',u'Total Number of End Points'):
     for um in (u'0.01um',u'0.1um'):
         for hours in (u'0hr',u'24hr'):
             df.T[(primary,um,hours)]=df.T[(primary,um,hours)]/df.T[(primary, u'Control', hours)].mean()

请注意，这并没有划分非控制列，但是在um循环中包含“control”是很容易的。

UPDATE不工作，不知怎么的，它没有修改数据格式。现在，我不知道为什么。

但是，您可以通过对dict理解调用pd.DataFrame来构造一个新的数据框架。

这看起来很管用..。

代码语言：javascript
复制
import pandas as pd

df = pd.DataFrame({'0': {('Total Number of End Points', '0.01um', '0hr'): 12,
  ('Total Number of End Points', '0.1um', '0hr'): 8,
  ('Total Number of End Points', 'Control', '0hr'): 4,
  ('Total Number of End Points', '0.01um', '24hr'): 18,
  ('Total Number of End Points', '0.1um', '24hr'): 12,
  ('Total Number of End Points', 'Control', '24hr'): 6,
  ('Total Vessel Length', '0.01um', '0hr'): 12,
  ('Total Vessel Length', '0.1um', '0hr'): 8,
  ('Total Vessel Length', 'Control', '0hr'): 4,
  ('Total Vessel Length', '0.01um', '24hr'): 18,
  ('Total Vessel Length', '0.1um',  '24hr'): 12,
  ('Total Vessel Length', 'Control',  '24hr'): 6},
  '1': {('Total Number of End Points', '0.01um', '0hr'): 12,
  ('Total Number of End Points', '0.1um', '0hr'): 8,
  ('Total Number of End Points', 'Control', '0hr'): 4,
  ('Total Number of End Points', '0.01um', '24hr'): 18,
  ('Total Number of End Points', '0.1um', '24hr'): 12,
  ('Total Number of End Points', 'Control', '24hr'): 6,
  ('Total Vessel Length', '0.01um', '0hr'): 12,
  ('Total Vessel Length', '0.1um', '0hr'): 8,
  ('Total Vessel Length', 'Control', '0hr'): 4,
  ('Total Vessel Length', '0.01um', '24hr'): 18,
  ('Total Vessel Length', '0.1um',  '24hr'): 12,
  ('Total Vessel Length', 'Control',  '24hr'): 6},
  '2': {('Total Number of End Points', '0.01um', '0hr'): 12,
  ('Total Number of End Points', '0.1um', '0hr'): 8,
  ('Total Number of End Points', 'Control', '0hr'): 4,
  ('Total Number of End Points', '0.01um', '24hr'): 18,
  ('Total Number of End Points', '0.1um', '24hr'): 12,
  ('Total Number of End Points', 'Control', '24hr'): 6,
  ('Total Vessel Length', '0.01um', '0hr'): 12,
  ('Total Vessel Length', '0.1um', '0hr'): 8,
  ('Total Vessel Length', 'Control', '0hr'): 4,
  ('Total Vessel Length', '0.01um', '24hr'): 18,
  ('Total Vessel Length', '0.1um',  '24hr'): 12,
  ('Total Vessel Length', 'Control',  '24hr'): 6}})

print df

df2 = pd.DataFrame({(primary,um,hours):df.T[(primary,um,hours)]/df.T[(primary,u'Control',hours)].mean() for primary in (u'Total Vessel Length',u'Total Number of End Points') for um in (u'0.01um',u'0.1um') for hours in (u'0hr',u'24hr')})

print df2.T

输出

代码语言：javascript
复制
paul@home:~/SO$ python ./r.py 
                                              0   1   2
(Total Number of End Points, 0.01um, 0hr)    12  12  12
(Total Number of End Points, 0.01um, 24hr)   18  18  18
(Total Number of End Points, 0.1um, 0hr)      8   8   8
(Total Number of End Points, 0.1um, 24hr)    12  12  12
(Total Number of End Points, Control, 0hr)    4   4   4
(Total Number of End Points, Control, 24hr)   6   6   6
(Total Vessel Length, 0.01um, 0hr)           12  12  12
(Total Vessel Length, 0.01um, 24hr)          18  18  18
(Total Vessel Length, 0.1um, 0hr)             8   8   8
(Total Vessel Length, 0.1um, 24hr)           12  12  12
(Total Vessel Length, Control, 0hr)           4   4   4
(Total Vessel Length, Control, 24hr)          6   6   6

[12 rows x 3 columns]
                                            0  1  2
(Total Number of End Points, 0.01um, 0hr)   3  3  3
(Total Number of End Points, 0.01um, 24hr)  3  3  3
(Total Number of End Points, 0.1um, 0hr)    2  2  2
(Total Number of End Points, 0.1um, 24hr)   2  2  2
(Total Vessel Length, 0.01um, 0hr)          3  3  3
(Total Vessel Length, 0.01um, 24hr)         3  3  3
(Total Vessel Length, 0.1um, 0hr)           2  2  2
(Total Vessel Length, 0.1um, 24hr)          2  2  2

[8 rows x 3 columns]
票数 0
EN
页面原文内容由Stack Overflow提供。腾讯云小微IT领域专用引擎提供翻译支持
原文链接：

https://stackoverflow.com/questions/29711130

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