[英]How to min/max value in multiple columns of a pandas dataframe?
how can i get one min/max value of several columns from a dataframe?如何从 dataframe 中获取多个列的一个最小值/最大值? I could not find a simple way to get these values, only with looping over the columns or converting the dataframe multiple times.
我找不到获取这些值的简单方法,只能循环遍历列或多次转换 dataframe。 I think there must be a better way to solve this.
我认为必须有更好的方法来解决这个问题。
For example, here are some code...例如,这里有一些代码......
import pandas as pd
df = pd.DataFrame([[0,1,2,3],
[6,5,None,pd.NaT],
[8,None,9,None],
[None,12,7,14]], columns=list('ABCD'))
... this is what's the dataframe looks like and I want the min/max of column 'C' and 'D'. ...这就是 dataframe 的样子,我想要列“C”和“D”的最小值/最大值。
A B C D
0 0.0 1.0 2.0 3
1 6.0 5.0 NaN NaT
2 8.0 NaN 9.0 None
3 NaN 12.0 7.0 14
What is a good way to do this?这样做的好方法是什么?
Additional Note: The result of both columns ['C','D'] should be one value for min (2) and one value for max (14)附加说明:两列 ['C','D'] 的结果应为最小值 (2) 和最大值 (14) 的一个值
Use DataFrame.agg
with selected columns by list - ['C','D']
:将
DataFrame.agg
与列表中的选定列一起使用 - ['C','D']
:
df1 = df[['C','D']].agg(['min','max'])
print (df1)
C D
min 2.0 3
max 9.0 14
EDIT: For 2 scalars you can use:编辑:对于 2 个标量,您可以使用:
s = df[['C','D']].stack()
print (s)
0 C 2
D 3
2 C 9
3 C 7
D 14
dtype: object
a = s.max()
print (a)
14
b = s.min()
print (b)
2
You can use,您可以使用,
df[['C','D']].min().min()
2.0
and和
df[['C', 'D']].max().max()
14.0
If you are not sure about the column names, and want to do it on last 2 columns, you can do this:如果您不确定列名,并想在最后 2 列上这样做,您可以这样做:
In [2138]: df.iloc[:, -2:].agg(['max', 'min'])
Out[2138]:
C D
max 9.0 14
min 2.0 3
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