英文:
split values from columns and generate sequence number
问题
我有一个数据框中有两列。每列在一行中有多个值。我想要将每个值拆分到另一个表中的新行中，并生成序列号。给定的数据是：
新数据框应该是这样的：
x 76.25
y 87.12
序列号 1
x 345.65
y 96.45
序列号 2
x 78.12
y 85.23
序列号 1
x 35.1
y 65.21
序列号 2
x 98.27
y 56.63
序列号 3
所有的值都是字符串。我不知道该如何做。我应该编写一个函数还是数据框中有任何命令？任何帮助都将不胜感激。
英文:
I have two columns in a df. each column has multiple values in 1 row.I want to split each value in a new row in another table and generate sequence number. given data is
<!-- language: none -->
x y
76.25, 345.65 87.12,96.45
78.12,35.1,98.27 85.23,65.2,56.63
new df should be like this
<!-- language: none -->
x 76.25
y 87.12
sequence number 1
x 345.65
y 96.45
sequence number 2
x 78.12
y 85.23
sequence number 1
x 35.1
y 65.21
sequence number 2
x 98.27
y 56.63
sequence number 3
all values are strings. I have no idea how should I do it.Should I write a function or there is any command in dataframe? any help is appreciated
答案1
得分: 0
你可以使用iterrows()和concat()来实现：
df = pd.DataFrame({
'x': ('76.25,345.65', '78.12,35.1,98.27'),
'y': ('87.12,96.45', '85.23,65.2,56.63')
})
def get_parts():
for index, row in df.iterrows():
x = row['x'].split(',')
y = row['y'].split(',')
for index, _ in enumerate(x):
# len(x)必须等于len(y)...
yield 'x', x[index]
yield 'y', y[index]
# 在每个拆分的项目之后生成数字
yield 'sequence number', index + 1
# 从各个部分生成Series并合并成新的DataFrame
new_df = pd.concat([
pd.Series(],
])
for p in get_parts()
])
希望这对你有所帮助。
英文:
You can do it using iterrows() + concat():
df = pd.DataFrame({
'x': ('76.25,345.65', '78.12,35.1,98.27'),
'y': ('87.12,96.45', '85.23,65.2,56.63')
})
def get_parts():
for index, row in df.iterrows():
x = row['x'].split(',')
y = row['y'].split(',')
for index, _ in enumerate(x):
# len(x) must be equal len(y)...
yield 'x', x[index]
yield 'y', y[index]
# generate number after each splitted item
yield 'sequence number', index + 1
# generate Series from parts and union into new dataframe
new_df = pd.concat([
pd.Series(],
])
for p in get_parts()
])
Hope this helps.
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