当重复仅在第一列中时，drop

当重复仅在第一列中时，drop_duplicates在pandas中(drop_duplicates in pandas when duplicate is only in first column)

我有一个包含两列的数据框。 第一列，比如A，有重复，第二列没有。

我试过了

df["A"].drop_duplicates(inplace=True)

但是返回相同的行数。 如何删除“A”列中的值相同的行？

例：

John Miller John Smith Mark Robinson Jeffrey Robinson

应该回来

John Miller Mark Robinson Jeffrey Robinson

I have a dataframe with two columns. The first column, say A, has duplicates, the second does not.

I have tried

df["A"].drop_duplicates(inplace=True)

but that returns the same number of rows. How can I drop the rows where the value in column "A" is the same?

Example:

John Miller John Smith Mark Robinson Jeffrey Robinson

should return

John Miller Mark Robinson Jeffrey Robinson

最满意答案

将drop_duplicates与参数subset一起使用：

df.drop_duplicates(subset=['A'],inplace=True) print (df) A B 0 John Miller 2 Mark Robinson 3 Jeffrey Robinson

文档：

subset ：列标签或标签序列，可选

仅考虑用于标识重复项的某些列，默认情况下使用所有列

Use drop_duplicates with parameter subset:

df.drop_duplicates(subset=['A'],inplace=True) print (df) A B 0 John Miller 2 Mark Robinson 3 Jeffrey Robinson

Docs:

subset : column label or sequence of labels, optional

Only consider certain columns for identifying duplicates, by default use all of the columns