列的最大值和最小值之间的差异

时间:2019-10-25 08:31:13

标签: python pandas

我有一个2000列以上的pandas数据框。所有列均具有数值。我想找到每列的最小值和最大值之间的差异。然后,我想过滤出差异最大的前十列。

Col1 Col2 Col3 ..... Col2500
 4     1    3  .....    6
 7     5   10  .....    17
 1    22    4  .....    2

我尝试了几种选择,但是没有一个可行! 请提出解决方案。

4 个答案:

答案 0 :(得分:1)

这将为您提供2019-10-24T14:11:44.162+01:00 [CELL/0] [ERR] Timed out after 1m0s: health check never passed. 2019-10-24T14:11:44.162+01:00 [HEALTH/0] [ERR] Failed to make TCP connection to port 8080: connection refused 2019-10-24T14:11:44.168+01:00 [CELL/SSHD/0] [OUT] Exit status 0 2019-10-24T14:11:44.368+01:00 [APP/PROC/WEB/0] [OUT] Exit status 143 中的结果:

Series

示例:

df.T.apply(lambda x: x.max() - x.min(), axis=1).nlargest(10)

或者只是:

df

   Col1  Col2  Col3  Col2500
0     4     1     3        6
1     7     5    10       17
2     1    22     4        2

df.T.apply(lambda x: x.max() - x.min(), axis=1).nlargest(3)

Col2       21
Col2500    15
Col3        7
dtype: int64

答案 1 :(得分:0)

这是我的解决方法

>>> data = {'Col1':[4,7,1],'Col2':[1,5,22], 'Col3':[3,10,4], 'Col2500':[6,17,2]}
>>> df = pd.DataFrame(data)
>>> df
   Col1  Col2  Col3  Col2500
0     4     1     3        6
1     7     5    10       17
2     1    22     4        2
>>> diff = df.max() - df.min()
>>> diff
Col1        6
Col2       21
Col3        7
Col2500    15
>>> pd.DataFrame(diff).sort_values(by=0, ascending=False)
          0
Col2     21
Col2500  15
Col3      7
Col1      6

答案 2 :(得分:0)

希望这会有所帮助!

diff = df.max() - df.min()

diff.sort_values()

示例:

>>> df.values
array([[  0,  12,  42],
       [  1,  13,  21],
       [ 12,   1,  30],
       [  3,  45, -39],
       [  4,   1,  38]])

>>> diff = df.max() - df.min()
>>>
>>> diff.sort_values(ascending=False)
T3    81
T2    44
T1    12
dtype: int64
>>> diff.sort_values()
T1    12
T2    44
T3    81
dtype: int64
>>>

答案 3 :(得分:-1)

import pandas as pd
import numpy as np

#sample data
df = pd.DataFrame(np.random.randint(0,100,size=(100, 4)), columns=list('ABCD'))

#transposing data so columns are now rows and column names are indices
df = df.transpose()

#Calculation of Max - Min per row
df['dif'] = df.max(axis=1) - df.min(axis = 1)

#Number of results at the end (10 in your case)
TOP_N = 2

#Resetting the index to get column names and sorting by difference high to low
result = df.reset_index().rename(columns={'index':'ColumnName'})[['ColumnName','dif']].sort_values(by=['dif'],ascending=[False]).head(TOP_N)

print(result)