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You can download and use the program for free. You can have comments, but the program does not offer any other functionality. How does Smart clipboard work? Smart clipboard takes all types of text in your clipboard, and combines them in a list with each item having a name and a short description. Any text you copy in other application can be easily imported into your smart clipboard. The sticky notes feature allows you to take notes without any application. Here you can create sticky notes with up to five pages, one to five pages of text, one to five pictures and one to five text blocks. All you need to do is to take a photo with your digital camera and it will be automatically added to the notes. The text blocks can either be in read-only mode or editable. Any text block can contain one or multiple sentences. The program allows you to search for any note using various search conditions, such as any text in any text block. And it also allows you to search for notes, pictures and notes with specific tags. In conclusion, Smart clipboard is a valuable tool that can simplify your MS Windows life. This tool includes Windows clipboard and traditional sticky notes. It's both simple and useful application that you can use anywhere. Previous: (*) View the WhiteHat Linux software section(s) The open source software tool WhiteHat Linux is a useful add-on to your computer. This tool is used to protect your privacy on the Internet. We are always being watched. 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Use a.empty, a.bool(), a.item(), a.any() or a.all() I dont understand why this error is happening here, and why isnt it happening at other lines? A: Pandas is being "clever", and tries to warn you that renaming and indexing in this way will render some transformations ambiguous. This is due to the different semantics of renaming and indexing. renaming does not modify the dataframe itself, while indexing does. In [11]: pd.DataFrame({'A' : [1], 'B' : [2]}, index=['foo']) Out[11]: A B foo 1 2 In [12]: pd.DataFrame({'A' : ['foo', 'bar'], 'B' : ['asdf', 'qwer'], 'C' : [1.0, 2.1]}, index=['foo']) Out[12]: A B C foo bar 1.0 1 2.1 2 Note that the column 'A' is also called 'foo' in the 2nd example, since the name of the column is implicitly important. Indexing the same values will rename them (and mark the original row as "previous"), but not generally index them. In [13]: df Out[13]: A What's New in the? 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