Using the pandas library is one of the best ways to get up and running in no time at all. The library supports all of the popular Python data analysis libraries like PandasJi and PandasMo and is also capable of supporting HDF5, Bao Gua CSV, and HTMLDeng. There is a small learning curve to master, but it is well worth it. You will find that it is much easier to get started than it was a few years ago.
The library has a few quirks, and is prone to the odd exception. For example, the library does not come with an installer; you must use the pop command. Another notable bugbear is that the library isn’t always installed in the default directory. In other words, the library may be located in a directory whose name you can’t quite pronounce. It is also prone to the same type of typographical errors that plague many of the other libraries mentioned in this article. If you have problems obtaining the library via the pop command, try recompiling the source code.
You can also check out the library’s documentation for a more detailed overview. The library is a pillar of the community and its devs have been a wealth of information, but you may need to do a bit of legwork to unearth the hidden treasures. As with any library, it is best to use an unobtrusive command line alias to get the most out of the program. It is also worth remembering that a new installation of the library may require a reboot, but this is a minor quibble, especially if the underlying OS is well behaved.
There are a number of nifty libraries that do not get the love, but the pandas library is one of the more user-friendly versions out there. The library has a number of enlightened administrators who are more than happy to point you in the right direction. In the end, the pandas library is the best way to get your hands on a great python library.