将列表列表转换为数据帧

时间:2015-01-27 21:25:25

标签: python python-2.7 pandas

我在2天前得到了一些关于一个问题的帮助我在一些“帽子”中计算了1,2和3的频率。

data = {'hat9': [[1, 2, 3, 2, 2, 3, 3, 3, 1, 1, 1, 3, 1, 3, 1, 3, 3, 2, 2, 3, 3, 2, 3, 2, 1, 1, 3, 3, 1, 3, 3, 3, 1, 3, 3, 3, 3, 1, 3, 3, 3, 3, 1, 2, 1, 1, 3, 3, 1, 3, 1, 2, 1, 3, 3, 3, 3, 3, 1, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 2, 3, 3, 3, 1, 3, 1, 3, 3, 1, 3, 3, 3, 1, 3, 1, 1, 1, 3, 1, 3, 1, 3]], 'hat8': [[1, 2, 3, 3, 3, 3, 3, 3, 1, 3, 3, 3, 2, 1, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 1, 3, 3, 3, 3, 3, 3, 3, 3, 3, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3]], 'hat1': [[1, 2, 3]], 'hat20': [[1, 2, 3, 2, 3, 1, 2, 2, 2, 2, 2, 2, 2, 3, 2, 2, 2, 2, 1, 2, 2, 2, 2, 2, 2, 2, 1, 2, 3, 1, 2, 2, 2, 2, 2, 2, 2, 2, 1, 2, 1, 2, 2, 1, 2, 3, 2, 2, 2, 2, 2, 1, 2, 2, 2, 2, 2, 2, 2, 3, 2, 2, 2, 3, 2, 2, 2, 2, 1, 2, 2, 3, 2]], 'hat3': [[1, 2, 3, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 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2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 1, 1, 2, 1, 2, 2, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 2, 2, 2, 1, 2, 1, 2]], 'hat17': [[1, 2, 3, 1, 1, 1, 3, 2, 2, 1, 2, 2, 2, 1, 2, 1, 2, 2, 1, 2, 1, 1, 2, 2, 2, 2, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 2, 2, 3, 2, 1, 1, 2, 1, 2, 1, 1, 2, 2, 1, 2, 1, 2, 2, 1, 2, 1, 2, 1, 2, 1, 1, 2, 2, 1, 2, 1, 3, 2, 2, 1, 2, 1, 2, 2, 1, 1, 2, 1, 2, 2, 2, 1, 2, 1, 2, 2, 1, 2, 1, 2, 2, 1, 1, 2, 2, 2, 2, 1, 3, 1, 1, 2, 1, 2, 2, 2, 1, 1, 2, 1, 1, 2, 1, 1, 3, 2, 2, 1, 3, 2, 1, 2, 1, 2, 1, 1, 1, 2, 2, 2, 1, 1, 1, 2, 2, 1, 2, 2, 1, 2, 1, 2, 1, 2, 3, 3, 2, 2, 1, 1, 1, 1, 3, 1, 2, 1, 1, 1, 2, 2, 1, 2, 2, 2, 2, 2, 2, 1, 1, 2, 1, 2, 1, 2, 1, 1, 1, 2, 2, 1, 2, 2, 2, 1, 2, 2, 2, 1, 2, 2, 1, 2, 2, 2, 1, 1, 2, 1, 1, 1, 2, 1, 2, 3, 1, 1, 1, 2, 1, 2, 1, 2, 2, 1, 1, 2, 1, 1, 2, 1, 1, 1, 1, 1, 1, 2, 1, 3, 1, 2, 2, 2, 1, 2, 1, 1, 2, 1, 2, 2, 1, 2, 2, 2, 2, 2, 2, 1, 2, 1, 2, 2, 2, 2, 2, 1, 1, 3, 2, 2, 1, 2, 3, 1, 1, 1, 2, 1, 1, 1, 1, 2, 2, 2, 3, 2, 2, 2, 2, 1, 1, 2, 2, 2, 1, 2, 1, 1, 2, 2, 1, 1, 1, 3, 1, 1, 2, 2, 2, 1, 1, 1, 1, 1, 2, 2, 2, 1, 3, 1, 1, 2, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 2, 2, 1]], 'hat16': [[1, 2, 3, 1, 1, 1, 1, 2, 3, 1, 2, 2, 2, 2, 2, 2, 2, 2, 1, 2, 3, 3, 3, 3, 3, 1, 2, 1, 3, 1, 1, 1, 1, 1, 3, 2, 3, 3, 1, 2, 2, 2, 1, 1, 3, 1, 2, 3, 3, 1, 3, 1, 1, 3, 3, 2, 2, 2, 2, 3, 3, 1, 1, 2, 2, 1, 2, 3, 1, 3, 1, 3, 1, 3, 2, 1, 1, 2, 2, 2, 1, 1, 3, 2, 3, 3, 3, 3, 3, 1, 2, 2, 2, 1, 2, 2, 1, 3, 3, 2, 2, 1, 2, 2, 1, 2, 1, 2, 2, 2, 1, 3, 2, 2, 3, 3, 2, 3, 1, 1, 3, 1, 3, 2, 2, 1, 3, 1, 1, 2, 3, 3, 3, 3, 2, 2, 2, 2, 1, 3, 3, 1, 3, 2, 3, 3, 2, 3, 3, 1, 3, 3, 2, 2, 2, 2, 3, 1, 1, 3, 1, 3, 3, 1, 3, 3, 2, 2, 2, 3, 3, 3, 3, 1, 1, 1, 3, 3, 3, 2, 1, 2, 2, 1, 1, 1, 1, 1, 1, 3, 3, 3, 3, 3, 1, 3, 3, 3, 2, 3, 2, 3, 3, 2, 1, 1, 2, 1, 1, 1, 3, 1, 2, 3, 2, 1, 1, 2, 1, 3, 2, 3, 3, 2, 2, 2, 1, 2, 1, 3, 1, 1, 3, 3, 3, 3, 1, 3, 3, 3]], 'hat19': [[1, 2, 3, 3, 2, 3, 2, 2, 2, 3, 2, 2, 3, 3, 2, 1, 2, 2, 3, 2, 3, 2, 2, 3, 1, 1, 1, 1, 1, 3, 2, 2, 2, 2, 1, 2, 1, 3, 3, 3, 2, 2, 1, 1, 2, 3, 2, 2, 2, 1, 2, 1, 2, 3, 2, 2, 2, 3, 1, 1, 2, 2, 2, 1, 2, 2, 2, 2, 1, 2, 1, 1, 3, 2, 3, 3, 3, 2, 2, 2, 3, 2]], 'hat18': [[1, 2, 3, 1, 1, 1, 1, 3, 1, 1, 1, 3, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 3, 1, 1, 2, 1, 1, 1, 3, 2, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 3, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 3, 1, 1, 1, 1, 1, 1, 1, 1, 3, 1, 3, 1, 3, 1, 1, 1, 1, 3, 2, 1, 1, 1, 3, 3, 1, 1, 1, 1, 1, 1, 1, 3, 1, 1, 1, 3, 1, 2, 1, 1, 1, 1, 1, 3, 1, 1, 1, 1, 1, 3, 3, 1, 1, 3, 1, 3, 2, 2, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 3, 1, 1, 1, 1, 1, 1, 3, 1, 1, 1, 1, 1, 1, 1, 3, 1, 1, 2, 1, 1, 3, 2, 1, 3, 1, 1, 3, 3, 1, 1, 1, 1, 3, 1, 1, 1, 1, 1, 1, 3, 3, 1, 1, 1, 1, 1, 1, 1, 3, 1, 3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 3, 1, 1, 2, 3, 1, 1, 3, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 1, 1, 2, 1, 3, 3, 1, 1, 1, 3, 1, 1, 1, 3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 3, 1, 1, 1, 1, 1, 1, 3, 3, 1, 1, 1, 1, 1, 1, 1, 1, 3, 1, 1, 2, 1, 1, 1, 3, 1, 1, 1, 1, 3, 1, 1, 3, 1, 1, 3, 2, 1, 2, 1, 1, 1, 1, 3, 1, 1, 3, 3, 3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 3, 1, 1, 1, 1, 3, 1, 1, 3, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 3, 1, 1, 1, 3, 2, 3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 1, 1, 1, 1, 2, 3, 3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]], 'hat21': [[1, 2, 3, 1, 3, 3, 3, 1, 3, 3, 1, 3, 1, 3, 2, 2, 3, 3, 3, 3, 3, 3, 2, 3, 3, 3, 3, 3, 1, 1, 3, 3, 3, 1, 3, 3, 3, 2, 3, 3, 3, 3, 3, 3, 2, 3, 3, 3, 3, 3, 2, 3, 2, 3, 1, 3, 3, 1, 1, 3, 3, 3, 3, 3, 3, 3, 3, 3, 1, 3, 2, 1, 3, 3, 1, 1, 3, 2, 2, 3, 3, 2, 2, 3, 3, 1, 3, 1, 2, 3, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 2, 2, 1, 3, 3, 3, 2, 3, 3, 3, 2, 3, 2, 3, 2, 3, 2, 3, 3, 3, 3, 3, 3, 1, 2, 3, 3, 2, 3, 3, 2, 3, 2, 3, 2, 2, 2, 3, 2, 3, 1, 3, 3, 1, 3, 3, 3, 3, 3, 1, 3, 3, 1, 3, 3, 3, 3, 2, 3, 3, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 1, 3, 3, 3, 3, 3, 2, 3, 3, 1, 1, 1, 3, 3, 3, 3, 3, 3, 2, 3, 3, 2, 3, 1, 3, 1, 2, 3, 2, 3, 3, 3, 3, 2, 3, 3, 3, 3, 3, 3, 3, 2, 3, 2, 3, 1, 3, 3, 1, 3, 3, 2, 3, 3, 3, 2, 3, 3, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 2, 3, 3, 1, 2, 3, 1, 3, 1, 2, 3, 3, 3, 2, 1, 2, 3, 2, 3, 3, 2, 2, 3, 1, 1, 3, 3, 3, 3, 1, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 2, 2, 1, 3, 3, 1, 3, 1, 3, 3, 3, 3, 3, 2, 3, 2, 3, 3, 3, 3, 3, 3, 3, 2, 3, 1, 3, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 1, 1, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 2, 2, 2, 3, 2, 3, 3, 2, 2, 3, 3, 2, 3, 3, 2, 1, 2, 3, 3, 3, 3, 3, 3, 2, 3, 3, 2, 3, 1, 3, 3, 3, 2, 3, 2, 1, 3, 2, 3, 1, 2, 3, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 1, 3, 3, 1, 2, 3, 3, 3, 3, 3, 3, 1, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 2, 2, 3, 1, 2, 3, 3, 1, 3, 2, 3, 3, 3, 2, 3, 3, 1, 3, 3, 3, 2, 3, 3, 3, 2, 3, 3, 3, 3, 3, 3]]}

有人提供了以下代码,它遍历键和值列表,并计算1,2和3的频率。为了在绘制这些数据时让我的生活更轻松,我想把它放在一个数据框中,所以,按照我在这篇文章中找到的例子,“Getting List of List to Pandas Data Frame”我使用了以下代码:

from pandas import DataFrame

keys=[]
values=[]

for key, value in data.iteritems():
    keys.append(key)
    one = 0
    two = 0
    three = 0
    for x in value[0]:
        if x == 1:
            one+=1
        elif x == 2:
            two+=1
        elif x == 3:
            three+=1
    values.append([one,two,three])

print keys
print values

理想情况下,我的数据框将'hat1''hat21'作为列(按照正确的顺序排列),并且在行中它将包含1个,2个和3个相应的计数'帽子'。例如(忽略数字),如果只有三个帽子,下面是我想象的。

      'hat1'    'hat2'    'hat3'
1       27        10        56
2       4         6         254
3       1         1          1

然而,当我使用代码df = DataFrame(values)时,数据框似乎是转置的,我不太清楚如何获取相应的标题,因为当我尝试使用键作为我的标题时,我得到了一个错误说AssertionError: 21 columns passed, passed data had 3 columns

      0    1    2
0    27   10   56
1     4    6  254
2     1    1    1
3     3  480    1
4   252    1    1
5     6   17   10
6     3    2  142
7     6  211    3
8   313    5   12
9     1  193    5
10  243   20   22
11   58   31   93
12    5  190   65
13   80   81  120
14  122   54   18
15  156  154   17
16   76   76   88
17   10   55    8
18  280   26   62
19   19   42   21
20   54   82  310

感谢您的帮助。

1 个答案:

答案 0 :(得分:2)

您可以使用转置计数轻松实现您想要的效果,例如:

import pandas as pd

# use .transpose or .T can transpose your dataframe
df = pd.DataFrame(data).T
# then I simply use list comprehension and count element 1,2,3 in it
# and assign to new column, that's it
df[1] = [d.count(1) for d in df[0]]
df[2] = [d.count(2) for d in df[0]]
df[3] = [d.count(3) for d in df[0]]

结果:

df.head(10)

                                                       0    1    2    3
hat1                                           [1, 2, 3]    1    1    1
hat10  [1, 2, 3, 2, 3, 2, 3, 3, 3, 3, 3, 3, 3, 2, 3, ...  243   20   22
hat11  [1, 2, 3, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, ...    1  193    5
hat12  [1, 2, 3, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, ...    5  190   65
hat13  [1, 2, 3, 2, 1, 2, 1, 3, 2, 1, 1, 2, 1, 1, 2, ...   58   31   93
hat14  [1, 2, 3, 1, 2, 1, 2, 3, 1, 1, 1, 3, 3, 1, 2, ...  122   54   18
hat15  [1, 2, 3, 1, 1, 2, 3, 3, 2, 3, 3, 3, 3, 2, 3, ...   80   81  120
hat16  [1, 2, 3, 1, 1, 1, 1, 2, 3, 1, 2, 2, 2, 2, 2, ...   76   76   88
hat17  [1, 2, 3, 1, 1, 1, 3, 2, 2, 1, 2, 2, 2, 1, 2, ...  156  154   17
hat18  [1, 2, 3, 1, 1, 1, 1, 3, 1, 1, 1, 3, 1, 1, 1, ...  280   26   62

最后转置回来并为替换列分配数据框:

df = df[[1,2,3]].T

print df
   hat1  hat10  hat11  hat12  hat13  hat14  hat15  hat16  hat17  hat18  ...   1     1    243      1      5     58    122     80     76    156    280  ...    
2     1     20    193    190     31     54     81     76    154     26  ...    
3     1     22      5     65     93     18    120     88     17     62  ...    

   hat2  hat20  hat21  hat3  hat4  hat5  hat6  hat7  hat8  hat9  
1   252     10     54     3     3     6   313     6     4    27  
2     1     55     82   480     2    17     5   211     6    10  
3     1      8    310     1   142    10    12     3   254    56