cannot do positional indexing on RangeIndex with these indexers [True] of type bool_

抱歉，我之前的回答有误。在使用`df.loc`时，如果使用布尔数组作为索引器，会出现这个错误。我已经找到了解决方案，下面是修改后的代码：

import pandas as pd

# 读取Excel文件
df = pd.read_excel('file.xlsx')

# 指定要查找的数值
target_value = 10

# 获取所有列中值为特定数的行
target_rows = df[df == target_value]

# 获取这些行对应的列
target_columns = target_rows.dropna(axis=1)

# 打印结果
print(target_columns)

请确保安装了pandas库，并将`file.xlsx`替换为你实际的文件路径。代码中，我们首先使用`pd.read_excel`读取Excel文件并将其存储在DataFrame对象`df`中。然后，我们指定要查找的特定数值`target_value`。接下来，通过`df[df == target_value]`获取所有列中值为`target_value`的行，并将结果存储在DataFrame对象`target_rows`中。然后，使用`dropna(axis=1)`来删除含有NaN值的列，得到最终的结果DataFrame对象`target_columns`。最后，打印出这些列。

这样就能够获取Excel文件中值为特定数的几列了。你可以根据需要修改目标数值和文件路径。

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。