首页ValueError: endog and exog matrices are different sizes

ValueError: endog and exog matrices are different sizes

时间: 2024-06-04 12:11:15 浏览: 474

Python ValueError: invalid literal for int() with base 10 实用解决方法

今天在写爬虫程序的时候由于要翻页，做除法分页的时候出现了复制代码代码如下: totalCount = ‘100’ totalPage = int(totalCount)/20 ValueError: invalid literal for int() with base 10的错误网上同样的错误有人建议用round(float(“1.0″))，但是解决不了我这个问题，round(float(“1.0″))是用于解决浮点数转换为整形数的，而我这个则是因为原字符串转换为整形后做除法，虽然一段时间内可能不报错，但时间久了就会提示（其实就是一个warning，但是会强制终止你的程序），正确

This error usually occurs when the number of rows in the endogenous variable (y) is not equal to the number of rows in the exogenous variables (X). In other words, the data sets you're using to fit the model have different lengths. To fix this error, you need to make sure that both the endogenous and exogenous variables have the same number of rows. Here are some common reasons why the matrices might have different sizes: 1. Missing values: If there are missing values in your data, this could cause the matrices to have different sizes. You can try dropping the missing values or imputing them before fitting the model. 2. Mismatched index: If you're using pandas data frames, make sure that the index of the endogenous variable matches the index of the exogenous variables. If they don't match, you can reindex the data frames or merge them on a common column. 3. Incorrect data set: Make sure that you're using the correct data set for both the endogenous and exogenous variables. If you're using different data sets, they might have different lengths. Once you've identified the source of the problem, you can take steps to fix it and try fitting the model again.

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