python - 如何在 Pandas 中获得同一条船连续安装的最旧部分安装？

Question

我有一个 pandas DataFrame，其部分安装在船上。我想保留每艘船/部件的连续安装中最早的安装(参见日期)。我怎样才能做到这一点？

输入:

| date  | boat | part
|-------|------|-----
| 01/01 | A    | C <-- Keep this row because this is first install of C in A
| 01/02 | A    | C  
| 01/03 | A    | C
| 01/04 | A    | D <-- Keep this row because this is first install of D in A
| 01/05 | A    | D
| 01/06 | A    | C <-- Keep this row because this is first install of C in A after D
| 01/07 | A    | C
| 01/08 | A    | C
| 01/09 | B    | C <-- Keep this row because this is first install of C in B
| 01/10 | B    | C

输出:

| date  | boat | part
|-------|------|-----
| 01/01 | A    | C
| 01/04 | A    | D
| 01/06 | A    | C
| 01/09 | B    | C

Answer 1

用途:

df = df[df[['boat','part']].ne(df[['boat','part']].shift()).any(axis=1)]
print (df)

    date boat part
0  01/01    A    C
3  01/04    A    D
5  01/06    A    C
8  01/09    B    C

详细信息:

首先将连续值与 DataFrame.ne 进行比较和转移:

print (df[['boat','part']].ne(df[['boat','part']].shift()))
    boat   part
0   True   True
1  False  False
2  False  False
3  False   True
4  False  False
5  False   True
6  False  False
7  False  False
8   True  False
9  False  False

然后按 DataFrame.any 每行至少测试一个 True :

print (df[['boat','part']].ne(df[['boat','part']].shift()).any(axis=1))
0     True
1    False
2    False
3     True
4    False
5     True
6    False
7    False
8     True
9    False
dtype: bool