cannot do positional indexing on RangeIndex with these indexers [True] of type bool_
时间: 2024-04-13 13:25:34 浏览: 19
这个错误通常是因为使用了布尔型索引器 [True] 来进行位置索引,但是 RangeIndex 不支持这种类型的索引。RangeIndex 是 pandas 库中的一种默认索引类型,通常用于表示自动生成的整数索引。如果你想使用位置索引,可以使用整数索引器,如 iloc。例如,使用 df.iloc[0] 来访问第一个位置的数据。
相关问题
cannot do positional indexing on RangeIndex with these indexers [0.4] of type float
As an AI language model, I don't have enough context to understand the specific problem you are facing. However, I can provide you with some general information on this error message.
This error usually occurs when you try to access a specific row or column in a dataframe using a float value as the index. RangeIndex is a type of index that is automatically generated by Pandas when no specific index is provided. It is a sequence of integers starting from 0 and ending at n-1, where n is the number of rows in the dataframe.
Since RangeIndex is an integer-based index, you cannot use float values to access specific rows or columns. To access a specific row or column in a dataframe, you need to use integer-based indexes.
For example, if you want to access the fourth row in a dataframe, you can use the following code:
```
df.iloc[3]
```
Here, iloc stands for "integer location" and returns the row at the specified integer location.
If you want to access a specific column in a dataframe, you can use the following code:
```
df['column_name']
```
Here, 'column_name' is the name of the column you want to access.
In summary, to avoid the "cannot do positional indexing on RangeIndex with these indexers [0.4] of type float" error, you should make sure to use integer-based indexes when accessing specific rows or columns in a dataframe.
TypeError: cannot do positional indexing on RangeIndex with these indexers [750.0] of type float
这个错误通常是由于使用了一个浮点数类型的索引,而数据的索引是整数类型。在pandas中,RangeIndex是默认的整数索引类型,因此当您使用浮点数索引时,会出现这个错误。
要解决这个问题,您可以将浮点数索引转换为整数索引。例如,假设您的DataFrame是df,您需要将索引为750.0的行的值设置为1,您可以这样写:
```
df.loc[int(750.0)] = 1
```
在这里,我们使用int()函数将浮点数索引750.0转换为整数索引750,然后使用.loc[]操作符将该行的值设置为1。
如果您需要在DataFrame中使用浮点数索引,可以使用如下代码将其转换为整数索引:
```
df.index = df.index.astype(int)
```
这将把DataFrame的索引转换为整数类型。
相关推荐
![pdf](https://img-home.csdnimg.cn/images/20210720083512.png)
![zip](https://img-home.csdnimg.cn/images/20210720083736.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)