I feel like this may be a really easy question but I can't figure it out I have a data frame that looks like this

one two three

1 2 3

2 3 3

3 4 4

The third column has duplicates if I want to keep the first row but drop the second row because there is a duplicate on row two how would I do this.

CodePudding user response：

Pandas DataFrame objects have a method for this; assuming df is your dataframe, df.drop_duplicates(subset='name_of_third_column') returns the dataframe with any rows containing duplicate values in the third column removed.