根据其他列值在数据框中创建 ID 列 / Pandas -Python

Question

我有一个这样的数据框

L_1  D_1   L_2  D_2    L_3    D_3         C_N
1    Boy                                 Boy||
1    Boy   1-1  play                     Boy|play|
1    Boy   1-1  play  1-1-21  car        Boy|play|car
1    Boy   1-1  play  1-1-1   online     Boy|play|online
2    Girl                                Girl||
2    Girl  2-1  dance                    Girl|dance|

我使用代码

创建了C_N标签

df['C_N'] = df[['D_1','D_2', 'D_3']].apply(lambda x: '|'.join(x), axis=1)

现在我想要另一列，我也可以在其中获取特定组的 ID，我的理想输出是：

L_1  D_1   L_2  D_2    L_3    D_3      IDs        C_N
1    Boy                               1         Boy||
1    Boy   1-1  play                   1-1       Boy|play|
1    Boy   1-1  play  1-1-21  car      1-1-21    Boy|play|car
1    Boy   1-1  play  1-1-1   online   1-1-1     Boy|play|online
2    Girl                              2         Girl||
2    Girl  2-1  dance                  2-1       Girl|dance|

谁能帮我解决这个问题。提前致谢！

Answer 1

df = df.replace("^\s*$", np.nan, regex=True)

id_inds = df.filter(like="L_").agg(pd.Series.last_valid_index, axis=1)

# either this (but deprecated..)
df["IDs"] = df.lookup(df.index, id_inds)

# or this
df["IDs"] = df.to_numpy()[np.arange(len(df)), df.columns.get_indexer(id_inds)]

首先，我们用 NaN 替换空单元格，然后查看 L_* 列。获取他们的 last_valid_indexes，它给出列 names。然后我们可以 lookup （已弃用），或者转到 numpy 值并使用 get_indexer、

进行花式索引

得到

>>> df
   L_1   D_1  L_2    D_2     L_3     D_3              C_N     IDs
0    1   Boy  NaN    NaN     NaN     NaN            Boy||       1
1    1   Boy  1-1   play     NaN     NaN        Boy|play|     1-1
2    1   Boy  1-1   play  1-1-21     car     Boy|play|car  1-1-21
3    1   Boy  1-1   play   1-1-1  online  Boy|play|online   1-1-1
4    2  Girl  NaN    NaN     NaN     NaN           Girl||       2
5    2  Girl  2-1  dance     NaN     NaN      Girl|dance|     2-1

您现在可以根据需要用空字符串替换 NaNs。

Answer 2

我已经定义了一个自定义函数来检索所需的数据：

df = pd.DataFrame([
    ['1', 'Boy','','','',''],
    ['1', 'Boy','1-1','play','',''],
    ['1', 'Boy','1-1','play','1-1-21','car'],
    ['1', 'Boy','1-1','play','1-1-1','online'],
    ['2', 'Girl','','','',''],
    ['2', 'Girl','','dance','','']], columns=['L_1','D_1','L_2','D_2','L_3','D_3']
)
df['C_N'] = df[['D_1','D_2', 'D_3']].apply(lambda x: '|'.join(x), axis=1)

def get_data(x,y,z):
    result = []
    if x != '':
        result.append(x)
    if y != '':
        result.append(y)
    if z != '':
        result.append(z)
    return result[-1]

df['IDs'] = ''
df['IDs'] = df.apply(lambda row: get_data(row['L_1'], row['L_2'], row['L_3']), axis=1)

输出df

根据其他列值在数据框中创建 ID 列 / Pandas -Python

create ID column in dataframe based on other column values / Pandas -Python

python

dataframe

python-2.7

python-3.x

pandas