Question

我有一个带有4列的pandas数据框，我想制作第五列，这是一个包含4列元素的列表例如：

import pandas as pd
import numpy as np
df = pd.DataFrame(np.random.randn(6,4),columns=list('ABCD'))

>>> df
          A         B         C         D
0 -0.095531  1.922726  0.333087  0.173920
1 -2.633423 -0.635973  1.059518 -1.129433
2 -1.579580  1.088753  0.462434 -0.349215
3 -0.129472  0.656815  0.191109 -0.631818
4 -1.977579 -0.559613  0.789966 -0.044518
5  0.706840 -2.005750  0.327085  1.106847

我希望附加一个列E，以便第一行看起来像

[A=-0.095531,B=1.922726,C=0.333087,D=0.173920]

我尝试df['E'] = list(df.values)但是生成了op [-0.095531,1.922726,0.333087,0.173920]。

Answer 1

我为所有列做了df ['A'] =“A =”+ df ['A']。astype（str）等等。然后df ['E'] = list（df.values）给出了所需的op

Answer 2

我认为以下内容可能有所帮助：

  df['E']=list(df.values)
  df


         A          B           C         D     E
0   0.879163    0.078845    -0.678123   1.985986    [0.879162590333, 0.0788449197234, -0.678123390...
1   2.583740    -0.604236   -1.530671   -0.338767   [2.58373987111, -0.604235978563, -1.5306710724...
2   -0.435389   -0.654454   -1.170191   -1.829236   [-0.435389198028, -0.65445422574, -1.170190542...
3   -0.009336   -0.582220   0.177863    -0.014115   [-0.00933610605622, -0.582219961202, 0.1778632...
4   -2.044836   0.519311    1.626044    -0.303060   [-2.0448364492, 0.51931139324, 1.62604416428, ...
5   -1.244811   0.253653    0.450925    -0.410422   [-1.24481148127, 0.253652735816, 0.45092490489...

Answer 3

不确定这有用！但是你走了。

df.assign(
    E=df.applymap(
        '{: 5.2f}'.format
    ).radd(df.columns.to_series() + '=').values.tolist()
)

          A         B         C         D                                     E
0 -0.095531  1.922726  0.333087  0.173920  [A=-0.10, B= 1.92, C= 0.33, D= 0.17]
1 -2.633423 -0.635973  1.059518 -1.129433  [A=-2.63, B=-0.64, C= 1.06, D=-1.13]
2 -1.579580  1.088753  0.462434 -0.349215  [A=-1.58, B= 1.09, C= 0.46, D=-0.35]
3 -0.129472  0.656815  0.191109 -0.631818  [A=-0.13, B= 0.66, C= 0.19, D=-0.63]
4 -1.977579 -0.559613  0.789966 -0.044518  [A=-1.98, B=-0.56, C= 0.79, D=-0.04]
5  0.706840 -2.005750  0.327085  1.106847  [A= 0.71, B=-2.01, C= 0.33, D= 1.11]

根据您的字面要求：

df.assign(
    E=df.astype(str).radd(df.columns.to_series() + '=').values.tolist())

          A         B         C         D                                                  E
0 -0.095531  1.922726  0.333087  0.173920   [A=-0.095531, B=1.922726, C=0.333087, D=0.17392]
1 -2.633423 -0.635973  1.059518 -1.129433  [A=-2.633423, B=-0.635973, C=1.059518, D=-1.12...
2 -1.579580  1.088753  0.462434 -0.349215  [A=-1.57958, B=1.088753, C=0.462434, D=-0.349215]
3 -0.129472  0.656815  0.191109 -0.631818  [A=-0.129472, B=0.656815, C=0.191109, D=-0.631...
4 -1.977579 -0.559613  0.789966 -0.044518  [A=-1.977579, B=-0.559613, C=0.789966, D=-0.04...
5  0.706840 -2.005750  0.327085  1.106847    [A=0.70684, B=-2.00575, C=0.327085, D=1.106847]

根据列名包含在pandas中的列值创建列表

3 个答案: