使用其他行中的非唯一值从 Dataframe 行中提取值

Question

Given the following Dataframe,

  SecondsInDay  Min  Max
0             0    1    2
1           300    3    4
2           600    5    6
3             0    7    8
4           300    1    0
5           300    2   12
6           300    4   56

I want to extract overall minimum and maximum value for every row where SecondsInDay = 300.

Being new to DataFrames, it took a while but I wrote the following code:

val = df[df.SecondsInDay==300]
index=val.index
maxVal=val['Max'][index[0]]
minVal=val['Min'][index[0]]
for d in index:
    if maxVal < val['Max'][d]:
        maxVal = val['Max'][d]
    if minVal> val['Min'][d]:
        minVal= val['Min'][d]

which indeed returns the correct values

maxVal=56
minVal=1

However, I read that iterating through DataFrames is not good particularly at scale,

therefore could I have written this better?

thanks in advance

Answer 1

So we can do agg

df.loc[df.SecondsInDay==300].agg({'Min':'min','Max':'max'})
Out[122]: 
Min     1
Max    56
dtype: int64

Answer 2

IICU

df[df['SecondsInDay']==300].agg(['max','min'] )