如何将列值中的数据分解为熊猫数据框中的多行

Question

我有一个问题，我的 csv 文件中有多个行，必须转换为 pandas 数据框，但是有些行的“名称”和“业务”列有多个名称和业务应该在单独的行，需要拆分，同时保持其他列的数据对于拆分的每一行都相同。

这是示例数据：

输入：

software	name	business
abc	Andrew Johnson, Steve Martin	Outsourcing/Offshoring, 201-500 employees,Health, Wellness and Fitness, 5001-10,000 employees
xyz	Jack Jones, Rick Paul, Johnny Jones	Banking, 1001-5000 employees,Construction, 51-200 employees,Consumer Goods, 10,001+ employees
def	Tom D., Connie J., Ricky B.	Unspecified, Unspecified, Self-employed

我需要的输出：

software	name	business
abc	Andrew Johnson	Outsourcing/Offshoring, 201-500 employees
abc	Steve Martin	Health, Wellness and Fitness, 5001-10,000 employees
xyz	Jack Jones	Banking, 1001-5000 employees
xyz	Rick Paul	Construction, 51-200 employees
xyz	Johnny Jones	Consumer Goods, 10,001+ employees
def	Tom D	Unspecified
def	Connie J	Unspecified
def	Ricky B	Self-employed

还有类似于“name”和“business”的附加列，其中包含需要拆分的多条信息，就像“name”和“business”一样。包含多条信息的单元格按顺序排列（有序）。

这是我目前拥有的代码并创建了新行，但它只拆分了 name 列中的内容，但是留下了 business 列和剩下的一些其他列需要与来自名称列。

name2 = df.name.str.split(',', expand=True).stack()
df = df.join(pd.Series(index=name2.index.droplevel(1), data=name2.values, name = 'name2'))

dict = df.to_dict('record')
for row in dict:
    new_segment = {}
    new_segment['name'] = str(row['name2'])
    #df['name'] = str(row['name2'])

    for col,content in new_segment.items():
            row[col] = content

df = pd.DataFrame.from_dict(dict)

df = df.drop('name2', 1)

这是我也在尝试的另一种解决方案，但它也给了我一个错误：

review_path = r'data/base_data'
review_files = glob.glob(review_path + "/test_data.csv")

review_df_list = []
for review_file in review_files:
    df = pd.read_csv(io.StringIO(review_file), sep = '\t')
    print(df.head())
    df["business"] = (df["business"].str.extractall(r"(?:[\s,]*)(.*?(?:Unspecified|employees|Self-employed))").groupby(level=0).agg(list))
    df["name"] = df["name"].str.split(r"\s*,\s*")
    print(df.explode(["name", "business"]))
    outPutPath = Path('data/base_data/test_data.csv')
    df.to_csv(outPutPath, index=False)

替代解决方案的错误消息：

读取：data/base_data/review_base.csv

成功了！

空数据框

列：[data/base_data/test_data.csv]

索引：[]

Answer 1

试试：

df["business"] = (
    df["business"]
    .str.extractall(r"(?:[\s,]*)(.*?(?:Unspecified|employees|Self-employed))")
    .groupby(level=0)
    .agg(list)
)
df["name"] = df["name"].str.split(r"\s*,\s*")

print(df.explode(["name", "business"]))

打印：

  software            name                                             business
0      abc  Andrew Johnson            Outsourcing/Offshoring, 201-500 employees
0      abc    Steve Martin  Health, Wellness and Fitness, 5001-10,000 employees
1      xyz      Jack Jones                         Banking, 1001-5000 employees
1      xyz       Rick Paul                       Construction, 51-200 employees
1      xyz    Johnny Jones                    Consumer Goods, 10,001+ employees
2      def          Tom D.                                          Unspecified
2      def       Connie J.                                          Unspecified
2      def        Ricky B.                                        Self-employed