问题描述
我有一个 DataFrame df 填充有重复 Id 的行和列:
I have a DataFrame df filled with rows and columns where there are duplicate Id's:
Index Id Type 0 a1 A 1 a2 A 2 b1 B 3 b3 B 4 a1 A ...
当我使用时:
uniqueId = df["Id"].unique()
我得到一个唯一 ID 列表.
I get a list of unique IDs.
但是,我怎样才能在整个 DataFrame 上应用此过滤,以便它保留结构但删除重复项(基于Id")?
How can I however apply this filtering on the whole DataFrame such that it keeps the structure but that the duplicates (based on "Id") are removed?
推荐答案
看来你需要DataFrame.drop_duplicates 参数 subset 指定测试重复的位置:
It seems you need DataFrame.drop_duplicates with parameter subset which specify where are test duplicates:
#keep first duplicate value df = df.drop_duplicates(subset=['Id']) print (df) Id Type Index 0 a1 A 1 a2 A 2 b1 B 3 b3 B
<小时>
#keep last duplicate value df = df.drop_duplicates(subset=['Id'], keep='last') print (df) Id Type Index 1 a2 A 2 b1 B 3 b3 B 4 a1 A
<小时>
#remove all duplicate values df = df.drop_duplicates(subset=['Id'], keep=False) print (df) Id Type Index 1 a2 A 2 b1 B 3 b3 B