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I cannot find any resources about wether one of the following three methods for getting a list of column names is preferred over the others. The first and simplest, seems to work with my current example. Is there any reason I should not use it ?

>>> import pandas as pd >>> import numpy as np >>> df = pd.DataFrame(np.random.rand(5,3)) >>> df.columns RangeIndex(start=0, stop=3, step=1) >>> list(df.columns) [0, 1, 2] >>> df.columns.get_values().tolist() [0, 1, 2] >>> list(df.columns.get_values()) [0, 1, 2]

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Performance - related answer here: https://stackoverflow.com/a/27236748/605328

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  • pick the one that has your preferred balance of readability and performance. Commented Jan 9, 2019 at 16:29
  • I feel like there's no difference among the three. For me, the easier and simpler the better, so I chooose #1. Commented Jan 9, 2019 at 16:29
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    related: stackoverflow.com/questions/19482970/… you can do list(df) if you hate typing my_dataframe.columns.values.tolist() if you want speed Commented Jan 9, 2019 at 16:31
  • @coldspeed my question is wether all these methods are equal, or if there is a difference. I don't think its duplicate. Commented Jan 9, 2019 at 16:34
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    @Giannis the differences and benefits are discussed at length in the other question. Commented Jan 9, 2019 at 16:34

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You can also use:

df.columns.tolist()
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2 Comments

I guess, my question is if one of them is more "correct", i.e there is some edge case that the others will fail.
None of them will fail. I just gave you the one which is quite fast.

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