修改来自Python Pandas的输出描述 [英] Modify output from Python Pandas describe

问题描述

是否可以忽略熊猫描述的某些输出? 该命令为我提供了所需的表输出(simpleDate的executeTime的计数和均值)

Is there a way to omit some of the output from the pandas describe? This command gives me exactly what I want with a table output (count and mean of executeTime's by a simpleDate)

df.groupby('simpleDate').executeTime.describe().unstack(1)

但是，我想要的只是这些，数数和均值.我要删除std，min，max等.到目前为止，我只读了如何修改列大小.

However that's all I want, count and mean. I want to drop std, min, max, etc... So far I've only read how to modify column size.

我猜测答案将是重新编写该行，而不是使用describe，但是我没有通过simpleDate 进行任何分组，并且 executeTime.

I'm guessing the answer is going to be to re-write the line, not using describe, but I haven't had any luck grouping by simpleDate and getting the count with a mean on executeTime.

我可以按日期计数:

df.groupby(['simpleDate']).size()

或按日期执行时间:

df.groupby(['simpleDate']).mean()['executeTime'].reset_index()

但是无法弄清楚组合它们的语法.

But can't figure out the syntax to combine them.

我想要的输出:

            count  mean  
09-10-2013      8  20.523   
09-11-2013      4  21.112  
09-12-2013      3  18.531
...            ..  ...

推荐答案

Describe返回一个序列，因此您只需选择所需的对象即可

Describe returns a series, so you can just select out what you want

In [6]: s = Series(np.random.rand(10))

In [7]: s
Out[7]: 
0    0.302041
1    0.353838
2    0.421416
3    0.174497
4    0.600932
5    0.871461
6    0.116874
7    0.233738
8    0.859147
9    0.145515
dtype: float64

In [8]: s.describe()
Out[8]: 
count    10.000000
mean      0.407946
std       0.280562
min       0.116874
25%       0.189307
50%       0.327940
75%       0.556053
max       0.871461
dtype: float64

In [9]: s.describe()[['count','mean']]
Out[9]: 
count    10.000000
mean      0.407946
dtype: float64

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