复制单元格包含多个数据的行 [英] Duplicating rows where a cell contains multiple pieces of data

问题描述

我想获取一个数据框并复制某些行. 一列称为name，可能具有多个名称. 下面是一个示例数据框:

I would like to take a dataframe and duplicate certain rows. One column, called name, may have multiple names. An example dataframe is contructed below:

data = [
    ['Joe', '17-11-2018', '2'],
    ['Karen', '17-11-2018', '4'],
    ['Bill, Avery', '17-11-2018', '6'],
    ['Sam', '18-11-2018', '4'],
    ['Alex, Frank', '18-11-2018', '6'],
    ['Chris', '18-11-2018', '8'],
]
df = pd.DataFrame(data, columns = ['name','date','number'])

这将产生以下数据帧:

          name        date number
0          Joe  17-11-2018      2
1        Karen  17-11-2018      4
2  Bill, Avery  17-11-2018      6
3          Sam  18-11-2018      4
4  Alex, Frank  18-11-2018      6
5        Chris  18-11-2018      8

我想对所有具有多个名称(用逗号分隔)的行进行处理，并为每个单独的名称重复它们.结果数据框应如下所示:

I would like to take all rows where there are multiple names (comma-separated) and duplicate them for each individual name. The resulting dataframe should look like this:

    name        date number
0    Joe  17-11-2018      2
1  Karen  17-11-2018      4
2   Bill  17-11-2018      6
3  Avery  17-11-2018      6
4    Sam  18-11-2018      4
5   Alex  18-11-2018      6
6  Frank  18-11-2018      6
7  Chris  18-11-2018      8

推荐答案

在str.split之后，它变成了

After str.split , it become a unnest problem

df['name']=df.name.str.split(',')

unnesting(df,['name'])
Out[97]: 
     name        date number
0     Joe  17-11-2018      2
1   Karen  17-11-2018      4
2    Bill  17-11-2018      6
2   Avery  17-11-2018      6
3     Sam  18-11-2018      4
4    Alex  18-11-2018      6
4   Frank  18-11-2018      6
5   Chris  18-11-2018      8

---

def unnesting(df, explode):
    idx = df.index.repeat(df[explode[0]].str.len())
    df1 = pd.concat([
        pd.DataFrame({x: np.concatenate(df[x].values)}) for x in explode], axis=1)
    df1.index = idx
    return df1.join(df.drop(explode, 1), how='left')

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