如何在 df 列值上方添加 sum() 值？

Question

Supposed I have a df as below, how to add a sum() value in below DataFrame?

df.columns=['value_a','value_b','name','up_or_down','difference']
df
                               value_a        value_b       name       up_or_down  difference
project_name
# sum                                27.56              25.04         sum          down -1.31     
2021-project11                      0.43               0.48        2021-project11            up        0.05
2021-project1                        0.62               0.56          2021-project1            down       -0.06
2021-project2                       0.51               0.47       2021-project2           down       -0.04
2021-porject3                       0.37               0.34         2021-porject3            down       -0.03
2021-porject4                       0.64               0.61         2021-porject4            down       -0.03
2021-project5                        0.32               0.25          2021-project5            down       -0.07
2021-project6                       0.75               0.81         2021-project6            up        0.06
2021-project7                      0.60               0.60        2021-project7            down        0.00
2021-project8                       0.85               0.74         2021-project8            down       -0.11
2021-project10                      0.67               0.67        2021-project10            down        0.00
2021-project9                     0.73               0.73        2021-project9           down        0.00
2021-project11                   0.54               0.54      2021-project11           down        0.00
2021-project12                 0.40               0.40    2021-project12           down        0.00
2021-project13                      0.76               0.77        2021-project13            up        0.01
2021-project14                     1.16               1.28        2021-project14           up        0.12
2021-project15                     1.01               0.94        2021-project15           down       -0.07
2021-project16                      1.23               1.24        2021-project16            up        0.01
2022-project17                       0.40               0.36          2022-project17           down       -0.04
2022-project_11                      0.40               0.40        2022-project_11            down        0.00
2022-project4                        1.01               0.80          2022-project4            down       -0.21
2022-project1                        0.65               0.67          2022-project1            up        0.02
2022-project2                    0.75               0.57       2022-project2           down       -0.18
2022-porject3                       0.32               0.32         2022-porject3            down        0.00
2022-project18                       0.91               0.56         2022-project18            down       -0.35
2022-project5                        0.84               0.89          2022-project5            up        0.05
2022-project19                      0.61               0.48        2022-project19            down       -0.13
2022-project6                       0.77               0.80         2022-project6            up        0.03
2022-project20                      0.63               0.54         2022-project20           down       -0.09
2022-project8                       0.59               0.55         2022-project8            down       -0.04
2022-project21                       0.58               0.54         2022-project21            down       -0.04
2022-project10                      0.76               0.76        2022-project10            down        0.00
2022-project9                     0.70               0.71        2022-project9           up        0.01
2022-project22                    0.62               0.56      2022-project22            down       -0.06
2022-project23               2.03               1.74  2022-project23           down       -0.29
2022-project12                 0.39               0.39    2022-project12           down        0.00
2022-project24                      1.35               1.55         2022-project24           up        0.20
project25                         0.45               0.42           project25            down       -0.03
project26                         0.53                NaN         project26              down         NaN
project27                           0.68                NaN           project27              down         NaN

I tried

df.sum().columns=['value_a_sun','value_b_sum','difference_sum']

And I would like to add below sum value in the above column value,

 sum                                27.56              25.04         sum          down -1.31     

But I got AttributeError: 'Series' object has no attribute 'column' , how to fix this? Thanks so much for any advice.

Answer 1

Filter columns names in subset by [] before sum and assign for new row in DataFrame.loc :

df.loc['sum'] = df[['value_a_sun','value_b_sum','difference_sum']].sum()

For first line:

df1 = df[['value_a_sun','value_b_sum','difference_sum']].sum().to_frame().T

df = pd.concat([df1, df], ignore_index=True)