忽略NaN，从scipy执行pearsonr()关联

Question

我想关联具有相同列名Length date(i)的df1和df2。两个数据帧都具有NaN的单元格。我想忽略这些单元格，跳过两个数据帧中的这一行。

measurements = 10
for i in range(1,measurements+1):
    cor_len = pearsonr(df1['Length date(' + str(i) + ')'], df2['Length date(' + str(i) + ')'])

到目前为止，我总是得到：

ValueError:数组不能包含infs或NaNs

两个df看起来都像：

Length date(1)  Length date(2)  Length date(3)  Length date(4)  Length date(5)  Length date(6)
8.512326        5.758995       39.743087       52.811855       75.285461       65.122357
18.852476       56.067361       93.113099      177.415235      184.472485      161.042771
92.391779       53.909429       76.507877      149.716421      147.524874      110.94987
NaN             21.220149        NaN             NaN             NaN             NaN
NaN             27.559950        NaN             NaN             NaN             NaN

Answer 1

此解决方案运行良好：

for i in range(1,measurements+1):
    xl  = dfr['Length date(' + str(i) + ')'].dropna()
    yl = df['Length date(' + str(i) + ')'].dropna()
    dl = pd.concat([xl,yl], axis = 1)
    dl = dl.dropna()
    cor_len = dl.corr()