用最简单的索引possib在python pandas中转置一列

Question

我有以下数据（data_current）：

import pandas as pd
import numpy as np

data_current=pd.DataFrame({'medicine':['green tea','fried tomatoes','meditation','meditation'],'disease':['acne','hypertension', 'cancer','lupus']})
data_current

我想做的是将其中一个列进行转置，这样，我就不用用同一种药物和不同疾病的多行，而是用一行表示每种药物，用几列表示疾病。保持索引尽可能简单也很重要，即0，1，2。。。i、 我不想将“药品”指定为索引列，因为我将在其他键上合并它。 所以，我需要data_needed

data_needed=pd.DataFrame({'medicine':['green tea','fried tomatoes','meditation'],'disease_1':['acne','hypertension','cancer'], 'disease_2':['np.nan','np.nan','lupus']})
data_needed

Answer 1

我想你需要一个透视表。检查此链接以获取详细信息-->；http://pandas.pydata.org/pandas-docs/stable/reshaping.html

你认为这个输出可以接受吗？

data_current.pivot(index='medicine', columns='disease', values='disease')

Answer 2

这里有一个实现输出

首先，groupby在medicine上，得到diseaseas列表

In [368]: md = (data_current.groupby('medicine')
                            .apply(lambda x: x['disease'].tolist())
                            .reset_index())

In [369]: md
Out[369]:
         medicine                0
0  fried tomatoes   [hypertension]
1       green tea           [acne]
2      meditation  [cancer, lupus]

然后将列中的列表转换为单独的列

In [370]: dval = pd.DataFrame(md[0].tolist(), )

In [371]: dval
Out[371]:
              0      1
0  hypertension   None
1          acne   None
2        cancer  lupus

现在，你可以用concat--md和dval

In [372]: md = md.drop(0, axis=1)

In [373]: data_final = pd.concat([md, dval], axis=1)

然后，根据需要重命名列。

In [374]: data_final.columns = ['medicine', 'disease_1', 'disease_2']

In [375]: data_final
Out[375]:
         medicine     disease_1 disease_2
0  fried tomatoes  hypertension      None
1       green tea          acne      None
2      meditation        cancer     lupus

Answer 3

dc = data_current
dc['disease_header'] = dc.diseases.replace(
                       dict(zip(diseases, 
                                map(lambda v: 'diseases_%d' %v, range(len(diseases))
                           )))

这将给我们：

In [548]: dc
Out[548]: 
        disease        medicine disease_header
0          acne       green tea     diseases_0
1  hypertension  fried tomatoes     diseases_1
2        cancer      meditation     diseases_2
3         lupus      meditation     diseases_3

最后，我们可以：

    In [547]: dc.pivot(columns='disease_header', index='medicine', values='disease').reset_index()
Out[547]: 
disease_header        medicine diseases_0    diseases_1 diseases_2 diseases_3
0               fried tomatoes        NaN  hypertension        NaN        NaN
1                    green tea       acne           NaN        NaN        NaN
2                   meditation        NaN           NaN     cancer      lupus