ValueError:无法将字符串转换为浮点型-没有位置指示 [英] ValueError: could not convert string to float - without positional indication

问题描述

对于当前的项目，我计划在包含数字数据的CSV集合上运行scikit-learn随机梯度助推器算法.

For a current project, I am planning to run a scikit-learn Stochastic Graduent Booster algorithm over a CSV set that includes numerical data.

当调用脚本的 sgbr.fit(X_train，y_train)行时，我收到了 ValueError:无法将字符串转换为float:，没有更多详细信息在无法格式化的相应区域上给出.

When calling line sgbr.fit(X_train, y_train) of the script, I am however receiving a ValueError: could not convert string to float: with no further details given on the respective area that cannot be formatted.

我认为此错误与Python代码本身无关，而与CSV输入有关.但是，我已经检查了CSV文件，以确认所有部分都专门包含浮点数:

I assume that this error is not related to the Python code itself but rather the CSV input. I have however already checked the CSV file to confirm all sections exclusively include floats:

有人知道为什么 ValueError 会在没有位置指示的情况下出现吗?

Does anyone have an idea why the ValueError is appearing without further positional indication?

推荐答案

我没有直接的功能来获取位置指示.您可以尝试进行转换

I thing there are not direct function to get positional indication. you can try this to convert

   print (df)
       column
    0  01
    1  02
    2  03
    3  04
    4  05
    5  LS

print (pd.to_numeric(df.column.str, errors='coerce'))
0    1.0
1    2.0
2    3.0
3    4.0
4    5.0
5    NaN
Name: column, dtype: float64

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