如何在dataframe中将第二列除以第一列？

Question

     DP 1       DP 2        DP 3       DP 4        DP 5         DP 6        DP 7        DP 8       DP 9        DP 10
 3,57,848    11,24,788   17,35,330   22,18,270   27,45,596   33,19,994   34,66,336   36,06,286   38,33,515   39,01,463 
 3,52,118    12,36,139   21,70,033   33,53,322   37,99,067   41,20,063   46,47,867   49,14,039   53,39,085  
 2,90,507    12,92,306   22,18,525   32,35,179   39,85,995   41,32,918   46,28,910   49,09,315      
 3,10,608    14,18,858   21,95,047   37,57,447   40,29,929   43,81,982   45,88,268          
 4,43,160    11,36,350   21,28,333   28,97,821   34,02,672   38,73,311              
 3,96,132    13,33,217   21,80,715   29,85,752   36,91,712                  
 4,40,832    12,88,463   24,19,861   34,83,130                      
 3,59,480    14,21,128   28,64,498                          
 3,76,686    13,63,294                              
 3,44,014                                   

我有一个三角形数据帧（df1），我想计算包含结果的新数据帧（df2）：第二列（df2）/第一列（df2）和第三列（df2）/第二列（df2），依此类推

我试着这样做（我知道这是错误的）

for colname, col in df1.iteritems():
            df1[colname7] = df1['second_column']/df1['first_column']

我希望df2是这样的：

  DP 1   DP 2    DP 3    DP 4    DP 5    DP 6    DP 7    DP 8    DP 9   DP 10
 3.14    1.54    1.28    1.24    1.21    1.04    1.04    1.06    1.02    -   
 3.51    1.76    1.55    1.13    1.08    1.13    1.06    1.09    -      
 4.45    1.72    1.46    1.23    1.04    1.12    1.06    -          
 4.57    1.55    1.71    1.07    1.09    1.05    -              
 2.56    1.87    1.36    1.17    1.14    -                  
 3.37    1.64    1.37    1.24    -                      
 2.92    1.88    1.44    -                          
 3.95    2.02    -                              
 3.62    -      

                        

谢谢你抽出时间

Answer 1

首先，您需要删除逗号并将数据帧转换为浮点类型：

df2 = df1.replace(',', '', regex = True).astype(float)

然后，您可以通过移动列一次来直接划分：

df2 = df2.shift(-1, axis = 1).div(df2)

输出

df2
       DP 1      DP 2      DP 3      DP 4      DP 5      DP 6      DP 7      DP 8      DP 9  DP 10
0  3.143200  1.542806  1.278299  1.237719  1.209207  1.044079  1.040374  1.063009  1.017725    NaN
1  3.510582  1.755493  1.545286  1.132926  1.084493  1.128106  1.057268  1.086496       NaN    NaN
2  4.448450  1.716718  1.458257  1.232079  1.036860  1.120010  1.060577       NaN       NaN    NaN
3  4.568002  1.547052  1.711784  1.072518  1.087360  1.047076       NaN       NaN       NaN    NaN
4  2.564198  1.872956  1.361545  1.174217  1.138315       NaN       NaN       NaN       NaN    NaN
5  3.365588  1.635679  1.369162  1.236443       NaN       NaN       NaN       NaN       NaN    NaN
6  2.922798  1.878099  1.439393       NaN       NaN       NaN       NaN       NaN       NaN    NaN
7  3.953288  2.015651       NaN       NaN       NaN       NaN       NaN       NaN       NaN    NaN
8  3.619179       NaN       NaN       NaN       NaN       NaN       NaN       NaN       NaN    NaN
9       NaN       NaN       NaN       NaN       NaN       NaN       NaN       NaN       NaN    NaN

---

（可选）您可以使用以下选项进行取舍：

df2 = df2.round(2)