我想重塑我的数据框，它只有键值对。
例如，
key value
0 Message-ID <5525962.1075855679785.JavaMail.evans@thyme>
1 Date Wed, 13 Dec 2000 07:04:00 -0800 (PST)
2 From phillip.allen@enron.com
3 To christi.nicolay@enron.com, james.steffes@enron...
4 X-From Phillip K Allen
5 X-To Christi L Nicolay, James D Steffes, Jeff Dasov...
6 X-cc: None
7 X-bcc: None
8 X-Origin Allen-P
9 Message-ID <4650921.1075855679981.JavaMail.evans@thyme>
10 Date Tue, 5 Dec 2000 07:31:00 -0800 (PST)
11 From ina.rangel@enron.com
12 To amanda.huble@enron.com
13 X-From Ina Rangel
14 X-To Amanda Huble
15 X-cc: None
16 X-bcc: None
17 X-Origin Allen-P
我想将其转换为：
Message-ID Date From To X-From X-To X-cc: X-bcc: X-Origin
<5525962.10... Wed, 13 Dec 2000... phillip.allen... christi.nicolay.. Phillip K Allen.. Christi L Nicolay, Ja... NaN NaN Allen-P
<4650921.10... Tue, 5 Dec 2000 ... ina.rangel... amanda.huble@... Ina Rangel Amanda Huble NaN NaN Allen-P
我尝试过旋转表，但是我对于应该作为索引参数的内容感到困惑。请帮我解决这个问题。
如果发现重复，可以将其标记为重复。
答案 0 :(得分：3)
如果每个组总是有9个值，则可以将2d array与DataFrame一起使用numpy.reshape和key，对于列值，也要取列print (df['value'].values.reshape(-1, 9))
[['<5525962.1075855679785.JavaMail.evans@thyme>'
'Wed, 13 Dec 2000 07:04:00 -0800 (PST)' 'phillip.allen@enron.com'
'christi.nicolay@enron.com, james.steffes@enron...' 'Phillip K Allen'
'Christi L Nicolay, James D Steffes, Jeff Dasov...' 'None' 'None'
'Allen-P']
['<4650921.1075855679981.JavaMail.evans@thyme>'
'Tue, 5 Dec 2000 07:31:00 -0800 (PST)' 'ina.rangel@enron.com'
'amanda.huble@enron.com' 'Ina Rangel' 'Amanda Huble' 'None' 'None'
'Allen-P']]
df = pd.DataFrame(df['value'].values.reshape(-1, 9), columns=df['key'].iloc[:9])
print (df)
key Message-ID \
0 <5525962.1075855679785.JavaMail.evans@thyme>
1 <4650921.1075855679981.JavaMail.evans@thyme>
key Date From \
0 Wed, 13 Dec 2000 07:04:00 -0800 (PST) phillip.allen@enron.com
1 Tue, 5 Dec 2000 07:31:00 -0800 (PST) ina.rangel@enron.com
key To X-From \
0 christi.nicolay@enron.com, james.steffes@enron... Phillip K Allen
1 amanda.huble@enron.com Ina Rangel
key X-To X-cc: X-bcc: X-Origin
0 Christi L Nicolay, James D Steffes, Jeff Dasov... None None Allen-P
1 Amanda Huble None None Allen-P
的前9个值： >
Message-ID如果始终可以在每个组的数据中Series行，则将set_index与由布尔掩码的cumsum创建的助手==一起使用-与eq比较{ {1}}，用于确定每个组的开始：
df = df.set_index([df['key'].eq('Message-ID').cumsum(), 'key'])['value'].unstack()
print (df)
key Date From \
key
1 Wed, 13 Dec 2000 07:04:00 -0800 (PST) phillip.allen@enron.com
2 Tue, 5 Dec 2000 07:31:00 -0800 (PST) ina.rangel@enron.com
key Message-ID \
key
1 <5525962.1075855679785.JavaMail.evans@thyme>
2 <4650921.1075855679981.JavaMail.evans@thyme>
key To X-From \
key
1 christi.nicolay@enron.com, james.steffes@enron... Phillip K Allen
2 amanda.huble@enron.com Ina Rangel
key X-Origin X-To X-bcc: X-cc:
key
1 Allen-P Christi L Nicolay, James D Steffes, Jeff Dasov... None None
2 Allen-P Amanda Huble None None