python Pandas : Combine Dataframes that are unevenly filled

Question

再会，
从我们的一位客户那里，我们得到了看起来像这样的 csv 导出:

id  |  name  |  object_a  |  amount_a  |  object_b  |  amount_b  |  object_c  |  amount_c
1      abc      object_1     12           none         none         none         none


id  |  name  |  object_a  |  amount_a  |  object_b  |  amount_b  |  object_c  |  amount_c
2      def      object_2     7            object_3     19           none         none


id  |  name  |  object_a  |  amount_a  |  object_b  |  amount_b  |  object_c  |  amount_c
3      ghi      object_4     25           none         none         none         none

现在我真的只关心这对对象(对象名称和数量)。在每组数据中，最大对数总是相同的，但它们是随机填充的。
我的问题:是否可以将它们全部加载到数据帧中并将它们转换为这样的:

object   |   amount
object_1     12
object_2     7
object_3     19
object_4     25

将所有这些 csv-exports 加载到单个数据帧中不是问题，但 panda 是否包含此类问题的解决方案？
感谢你的帮助!

Answer 1

第一 concat所有的 csvs，然后使用 pd.wide_to_long :

csv_paths = ["your_csv_paths..."]

df = pd.concat([pd.read_csv(i) for i in csv_paths]).replace("none", np.NaN)

print (pd.wide_to_long(df, stubnames=["object","amount"],
                       i=["id","name"],j="Hi", suffix="\w*",
                       sep="_").dropna())

              object amount
id name Hi                 
1  abc  a   object_1     12
2  def  a   object_2      7
        b   object_3     19
3  ghi  a   object_4     25