Question

我想从数据框中的一列中获取匹配项。属性列是一个列表。下面是一个示例：

  date        tableNameFrom    tableNameJoin   attributeName
1 29-03-2019  film             language        [film.languageId, language.languageID, film.filmID]
2 30-03-2019  inventory as i   rental as r     [i.inventoryId, r.filmId]

这是我尝试过的：

df1 = (pd.DataFrame(df['attribute'].values.tolist())
                      .stack()
                      .str.split('.', expand=True)
                      .reset_index(drop=True))
df1.columns = ['tableName','attributeName']
print(df1)

还有我得到的输出：

  tableName    attributeName
1 film         languageId
2 language     languageID
3 film         filmId

需要的输出：

  date        tableName    attributeName
1 29-03-2019  film         languageId
2 29-03-2019  language     languageID
3 29-03-2019  film         filmId
4 30-03-2019  inventory    inventoryId
5 30-03-2019  rental       filmId

任何想法我该怎么办？感谢您的帮助。

Answer 1

首先由Series.str.split和as为字典创建字典：

df3 = df[['tableNameFrom','tableNameJoin']].stack().str.split(' as ',  expand=True).dropna()
d = dict(zip(df3[1], df3[0]))
print (d)
{'i': 'inventory', 'r': 'rental'}

将索引参数添加到DataFrame构造函数中，并删除最后一个reset_index：

df1 = (pd.DataFrame(df['attributeName'].values.tolist(), index=df.index)
                      .stack()
                      .str.split('.', expand=True))
df1.columns = ['tableName','attributeName']
print(df1)
    tableName attributeName
1 0      film    languageId
  1  language    languageID
  2      film        filmID
2 0         i   inventoryId
  1         r        filmId

仅选择列date和DataFrame.join新的DataFrame：

df2 = df[['date']].join(df1.reset_index(level=1, drop=True))

最后Series.replace，按字典：

df2['tableName'] = df2['tableName'].replace(d)
df2 = df2.reset_index(drop=True)
print (df2)
         date  tableName attributeName
0  29-03-2019       film    languageId
1  29-03-2019   language    languageID
2  29-03-2019       film        filmID
3  30-03-2019  inventory   inventoryId
4  30-03-2019     rental        filmId

如何在数据框中的列之间匹配值

1 个答案: