Python Pandas:从数据帧计算RMSE的简单示例 [英] Python Pandas: Simple example of calculating RMSE from data frame
问题描述
需要一个使用Pandas DataFrame计算RMSE的简单示例.提供可以按周期返回真实值和预测值的函数:
Need a simple example of calculating RMSE with Pandas DataFrame. Providing there is function that returns in cycle true and predicted value:
def fun (data):
...
return trueVal, predVal
for data in set:
fun(data)
然后一些代码将这些结果放入以下数据帧中,其中x
是真实值,而p
是预测值:
And then some code puts these results in the following data frame where x
is a real value and p
is a predicted value:
In [20]: d
Out[20]: {'p': [1, 10, 4, 5, 5], 'x': [1, 2, 3, 4, 5]}
In [21]: df = pd.DataFrame(d)
In [22]: df
Out[22]:
p x
0 1 1
1 10 2
2 4 3
3 5 4
4 5 5
问题:
1)如何将fun
函数的结果放入df
数据框中?
1) How to put results from fun
function in df
data frame?
2)如何使用df
数据帧计算RMSE?
2) How to calculate RMSE using df
data frame?
推荐答案
问题1
这取决于数据的格式.我希望您已经有了自己的真实值,因此该功能只是传递.
Question 1
This depends on the format that data is in. And I'd expect you already have your true values, so this function is just a pass through.
问题2
Question 2
使用pandas
((df.p - df.x) ** 2).mean() ** .5
使用numpy
(np.diff(df.values) ** 2).mean() ** .5
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