英文:
Perform a "Text-To-Columns' in a Panda's DF and copy existing row into a new row
问题
我有一个包含特定列值的数据框，我想将其拆分并复制到新的行中。例如：
Order# Price Quantity
123 $20 5
456,789 $50 7
321 $45 3
121,651 $76 9
在"Order#"列中的某些行包含由逗号分隔的两个订单号。我希望每个订单号都有自己的行。例如，我希望将第二行（456, 789）通过逗号分隔符拆分为两行。最终结果应该如下所示：
Order# Price Quantity
123 $20 5
456 $50 7
789 $50 7
321 $45 3
121 $76 9
651 $76 9
我尝试了以下代码：
df['Order Column'].str.split(",", expand=True)
但是卡住了。感谢任何帮助。
英文:
I have a df with certain column values that I want to split and then copy into new rows. For example:
Order# Price Quantity
123 $20 5
456,789 $50 7
321 $45 3
121,651 $76 9
Some rows in the "order#" column contain two order numbers separated by a column. I want each order# to have its own row. For example, I want the second row (456, 789) to be split by the column delimeter into two rows. The final result would look like:
Order# Price Quantity
123 $20 5
456 $50 7
789 $50 7
321 $45 3
121 $76 9
651 $76 9
I tried doing something like:
df['Order Column'].str.split(",", expand=True)
but then got stuck.
Appreciate any input.
答案1
得分: 0
你需要在split之后使用explode函数：
df["Order#"] = df["Order#"].str.split(",")
df.explode("Order#")
这样可以将Order#列中的每个元素拆分成多行，并复制其他列的值。
英文:
You need to explode after split:
df["Order#"] = df["Order#"].str.split(",")
>>> df.explode("Order#")
Order# Price Quantity
0 123 $20 5
1 456 $50 7
1 789 $50 7
2 321 $45 3
3 121 $76 9
3 651 $76 9
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