A good addition is the opportunity to fall columns only whenever they exist. In this way you could cover more use cases, and it will only drop the existing columns with the labels handed to it:
Personally, I like utilizing the axis parameter to denote columns or index since it will be the predominant key word parameter used in almost all pandas methods. But, now you may have some additional decisions in Edition 0.21.
I am going to also focus on the final Alternative of deleting numerous columns directly and making it possible for to the try to delete columns not present. Using these methods are typical and can perform for the simple circumstance as well.
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Nice energy, but possibly you ought to take into account pull request to pandas to only put into practice drop() with whichever you think of (then the consumer would not require to write ugly code)? [Having said that it's been 7 many years and maybe There was some effectiveness advancement considering the fact that then]
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This solution isn't really suitable - the pandas builders did not, but that doesn't imply it is hard to do.
the identify on the attribute is currently taken by A further attribute belonging on the dataframe. Do you want to change
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Deleting a column using the iloc perform of dataframe and slicing, when We've got an average column name with unwanted values:
Deleting a column is semantically similar to deciding on another columns. I am going to present a couple of supplemental approaches to contemplate.