我觉得必须有一种非常直接的方法来做到这一点，但我找不到。
所以，我有这个数据(注意 description 列在几个之间有共享部分):
import pandas as pd
data = {"description": ["AAAA:A", "AAAA:B", "AAAA:C", "AAAA:D", "BBBB:A", "BBBB:B"],
"sequence": ["AAAAAAAAAAA", "AAAAAAABBBBBB", "AAAAAAAACCCCCCC", "AAAAAAAADDDDDDD",
"BBBBBBAAAAA", "BBBBBBBBBBBBB"]}
df = pd.DataFrame(data)
print df
# description sequence
#0 AAAA:A AAAAAAAAAAA
#1 AAAA:B AAAAAAABBBBBB
#2 AAAA:C AAAAAAAACCCCCCC
#3 AAAA:D AAAAAAAADDDDDDD
#4 BBBB:A BBBBBBAAAAA
#5 BBBB:B BBBBBBBBBBBBB
我的最终目标是将所有序列放在一起，形成一个 4 字母的描述。像这样:
# description sequence_A sequence_B sequence_C sequence_D
#0 AAAA AAAAAAAAAAA AAAAAAABBBBBB AAAAAAAACCCCCCC AAAAAAAADDDDDDD
#1 BBBB BBBBBBAAAAA BBBBBBBBBBBBB NaN NaN
到目前为止，我已经到了这一点:
df = df.apply(lambda row: pd.Series({"description": row["description"].split(":")[0],
"sequence_{}".format(row["description"].split(":")[1]): row["sequence"]}),
axis=1)
print df
# description sequence_A sequence_B sequence_C sequence_D
#0 AAAA AAAAAAAAAAA NaN NaN NaN
#1 AAAA NaN AAAAAAABBBBBB NaN NaN
#2 AAAA NaN NaN AAAAAAAACCCCCCC NaN
#3 AAAA NaN NaN NaN AAAAAAAADDDDDDD
#4 BBBB BBBBBBAAAAA NaN NaN NaN
#5 BBBB NaN BBBBBBBBBBBBB NaN NaN
我猜我需要 df.groupby("description") 然后再执行一步，但我遗漏了最后一点。
最佳答案
split 然后 pivot
df[['New1','New2']]=df.description.str.split(':',expand=True)
s=df[['New1','New2','sequence']]
s.pivot(*s.columns).add_prefix('sequence_')
Out[863]:
New2 sequence_A sequence_B sequence_C sequence_D
New1
AAAA AAAAAAAAAAA AAAAAAABBBBBB AAAAAAAACCCCCCC AAAAAAAADDDDDDD
BBBB BBBBBBAAAAA BBBBBBBBBBBBB None None
关于python - 折叠共享一列值的 python 数据框行，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/49391846/