也没有Apply to each

如果您的 Power Automate 中没有 "Apply to each" 操作，您可以使用 "Until" 循环来实现对多个 ZIP 文件的解压缩。以下是具体步骤：

1. 创建一个新的流程，并添加 "获取文件路径" 操作，选择您要解压缩的文件夹。

2. 添加 "Until" 操作，并设置条件为：当文件夹中没有 ZIP 文件时退出循环。

3. 在 "Until" 操作中，添加 "解压缩文件" 操作，并将文件的路径作为输入。

4. 在 "解压缩文件" 操作中，添加 "Get files (properties only)" 操作，选择您要解压缩的文件夹，并设置筛选条件为：文件扩展名为 ".zip"。

5. 添加 "Condition" 操作，判断是否有 ZIP 文件。如果有，那么将文件的路径输出到 "解压缩文件" 操作中进行解压缩。

6. 最后，保存并运行流程，即可对指定文件夹下的所有 ZIP 文件进行解压缩。

在这个流程中， "Until" 操作用于循环检查文件夹中是否还有 ZIP 文件，直到没有为止。然后在 "解压缩文件" 操作中，使用 "Get files (properties only)" 操作来获取文件夹中的所有 ZIP 文件，再通过 "Condition" 操作进行筛选和判断。

希望这能够帮到您。如果您还有其他关于 Power Automate 的问题，可以继续向我提出。

相关问题

apply(lambda)

`apply(lambda)` is a method in pandas library which is used to apply a function to each element or row of a pandas dataframe or series. The `lambda` function is a small anonymous function which takes an argument and returns a value. It is used when we need a simple function for a short period of time.

For example, suppose we have a pandas series with numerical values and we want to square each value in the series. We can use `apply(lambda)` to achieve this as follows:

import pandas as pd

# create a pandas series
s = pd.Series([1, 2, 3, 4, 5])

# apply lambda function to square each value in the series
s_squared = s.apply(lambda x: x**2)

print(s_squared)

Output:

0     1
1     4
2     9
3    16
4    25
dtype: int64

In the above example, we have used `apply(lambda)` to apply a lambda function to each element of the series to square it.

help(pd.read_csv()[].apply().tolist)

`pd.read_csv()` is a function in the pandas library that reads a CSV file and returns a pandas DataFrame. The `[]` operator is used to select a specific column or columns from the DataFrame. The `.apply()` method is used to apply a function to each element of the selected column(s). Finally, the `.tolist()` method is used to convert the resulting pandas Series or DataFrame to a Python list.

So the code `pd.read_csv()[].apply().tolist` doesn't make sense as there are no arguments passed to the `apply()` method. You need to provide a function to the `apply()` method to transform the data in the selected column(s) before converting it to a list with `tolist()`.