Error in cor(data_factor) : 'x' must be numeric

This error message is indicating that the function cor() is being applied to a non-numeric dataset, which is not allowed. The cor() function is used to calculate the correlation between two numeric variables.

To resolve this error, the dataset needs to be converted to a numeric format before applying the cor() function. This can be done by using the as.numeric() function to convert the data to a numeric format.

Alternatively, if there are non-numeric variables in the dataset that are not needed for the correlation calculation, they can be removed using subsetting or by selecting only the numeric variables in the dataset.

相关问题

mycorr <- cor(data) Error in cor(data) : 'x'必需为数值

这个错误提示意味着你的输入数据必须是数值型的。你提供给 `cor()` 函数的 `data` 变量可能不是数值型的，而是字符型或其他类型的数据。请确保你的输入数据是数值型的，并且每个变量之间有足够的数量级差异，以避免出现奇异矩阵或其他数值问题。你可以使用 `as.numeric()` 函数将数据转换为数值型，例如：`mycorr <- cor(as.numeric(data))`。

TypeError Traceback (most recent call last) Cell In[5], line 13 11 row_cent1 = cor_row_center[cor_ind] 12 col_cent1 = cor_col_center[cor_ind] ---> 13 img_corner = data_mat1[(row_cent1-N_pad): (row_cent1+N_pad+1), (col_cent1-N_pad): (col_cent1+N_pad+1) ] 14 if ((len(np.unique(img_corner))) >2)&(np.sum(img_corner ==1)< 0.8*(N_pad*2+1)**2) : 16 for pic_id2 in search_list: TypeError: slice indices must be integers or None or have an __index__ method

这个错误可能是由于 `row_cent1` 或 `col_cent1` 的值不是整型导致的。可以在调用 `int()` 函数将其强制转换成整型，例如：

img_corner = data_mat1[int(row_cent1-N_pad): int(row_cent1+N_pad+1), int(col_cent1-N_pad): int(col_cent1+N_pad+1)]

这样就可以将 `row_cent1` 和 `col_cent1` 强制转换成整型，避免这个错误。