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I ask the following question which is more pure Python than Sage, since I am mixing both.
I have a dataframe and one column looks like that
I would like to keep only the non rows or to drop the numeric ones. I have not found a way to do that in Pandas. As you see the numerical values can change --- in the contrary it would be easy.
I ask the following question which is more pure Python than Sage, since I am mixing both.
I have a dataframe and one column looks like that
I would like to keep only the non rows or to drop the numeric ones. I have not found a way to do that in Pandas. As you see the numerical values can change --- in the contrary it would be easy.
I ask the following question which is more pure Python than Sage, since I am mixing both.
I have a dataframe and one column looks like that
I would like to keep only the non rows or to drop the numeric ones. I have not found a way to do that in Pandas. As you see the numerical values can change --- in the contrary it would be easy.
When I try something like
feuille_utilise[feuille_utilise['Entreprise liée'].str.contains("non")]
I obtain the following message
Cannot mask with non-boolean array containing NA / NaN values
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