Python：按特定条件旋转数据表/组

Question

我正在尝试从文本文件（.txt）更改数据结构，该数据如下所示：

:1:A
:2:B
:3:C
:1:D
:2:E
:3:F
:4:G
:1:H
:3:I
:4:J

我想将它们转换为这种格式（例如excel中的数据透视表，其列名是“：”之间的字符，每个组始终以：1：开头）

Group   :1: :2: :3: :4:
1        A   B   C
2        D   E   F   G
3        H       I   J

有人知道吗？预先感谢。

Answer 1

首先通过read_csv和header=None创建DataFrame，因为文件中没有标题：

import pandas as pd

temp=u""":1:A
:2:B
:3:C
:1:D
:2:E
:3:F
:4:G
:1:H
:3:I
:4:J"""
#after testing replace 'pd.compat.StringIO(temp)' to 'filename.csv'
df = pd.read_csv(pd.compat.StringIO(temp), header=None)
print (df)
      0
0  :1:A
1  :2:B
2  :3:C
3  :1:D
4  :2:E
5  :3:F
6  :4:G
7  :1:H
8  :3:I
9  :4:J

通过DataFrame.pop提取原始列，然后通过Series.str.strip和Series.str.split值将对立:删除到2个新列。然后通过与字符串Series.eq与字符串==与0比较Series.cumsum为df[['a','b']] = df.pop(0).str.strip(':').str.split(':', expand=True) df1 = df.set_index([df['a'].eq('1').cumsum(), 'a'])['b'].unstack(fill_value='') print (df1) a 1 2 3 4 a 1 A B C 2 D E F G 3 H I J 创建组，由DataFrame.set_index创建MultiIndex，最后由Series.unstack重塑：< / p>

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Answer 2

使用：

# Reading text file (assuming stored in CSV format, you can also use pd.read_fwf)
df = pd.read_csv('SO.csv', header=None)

# Splitting data into two columns
ndf = df.iloc[:, 0].str.split(':', expand=True).iloc[:, 1:]

# Grouping and creating a dataframe. Later dropping NaNs
res = ndf.groupby(1)[2].apply(pd.DataFrame).apply(lambda x: pd.Series(x.dropna().values))

# Post processing (optional)
res.columns = [':' + ndf[1].unique()[i] + ':' for i in range(ndf[1].nunique())]
res.index.name = 'Group'
res.index = range(1, res.shape[0] + 1)
res

Group   :1: :2: :3: :4:
1        A   B   C
2        D   E   F   G
3        H       I   J

Answer 3

另一种方法：

#read the file
with open("t.txt") as f:
    content = f.readlines()
#Create a dictionary and read each line from file to keep the column names (ex, :1:) as keys and rows(ex, A) as values in dictionary.
my_dict={}
for v in content:
    key = v.rstrip(':')[0:3] # take the value ':1:'
    value = v.rstrip(':')[3] # take value 'A'
    my_dict.setdefault(key,[]).append(value) 
#convert dictionary to dataframe and transpose it
df = pd.DataFrame.from_dict(my_dict,orient='index').transpose()
df

输出将如下所示：

   :1: :2: :3: :4:
0   A   B   C   G
1   D   E   F   J
2   H  None I  None