使用列方法向pandas DataFrame添加一行

Question

我有一个pandas DataFrame,包含一些随时间推移的传感器读数,如下所示:

       diode1  diode2  diode3  diode4
Time
0.530       7       0      10      16
1.218      17       7      14      19
1.895      13       8      16      17
2.570       8       2      16      17
3.240      14       8      17      19
3.910      13       6      17      18
4.594      13       5      16      19
5.265       9       0      12      16
5.948      12       3      16      17
6.632      10       2      15      17

我编写了代码,用每列的方法添加另一行:

# List of the averages for the test. 
averages = [df[key].describe()['mean'] for key in df]
indexes = df.index.tolist()
indexes.append('mean')
df.reindex(indexes)
# Adding the mean row to the bottom of the DataFrame

i = 0
for key in df:
    df.set_value('mean', key, averages[i])
    i += 1

这给了我想要的结果,这是一个像这样的DataFrame:

       diode1  diode2  diode3  diode4
Time
0.53      7.0     0.0    10.0    16.0
1.218    17.0     7.0    14.0    19.0
1.895    13.0     8.0    16.0    17.0
2.57      8.0     2.0    16.0    17.0
3.24     14.0     8.0    17.0    19.0
3.91     13.0     6.0    17.0    18.0
4.594    13.0     5.0    16.0    19.0
5.265     9.0     0.0    12.0    16.0
5.948    12.0     3.0    16.0    17.0
6.632    10.0     2.0    15.0    17.0
mean     11.6     4.1    14.9    17.5

但是,我确信这不是添加行的最有效方法.我尝试使用append作为熊猫系列保存的方法,但结果是这样的:

    diode1  diode2  diode3  diode4                     mean
0      7.0     0.0    10.0    14.0                      NaN
1      9.0     0.0    10.0    15.0                      NaN
2     10.0     5.0    14.0    20.0                      NaN
3      6.0     0.0     7.0    14.0                      NaN
4      7.0     0.0    10.0    15.0                      NaN
5      7.0     0.0     8.0    14.0                      NaN
6      7.0     0.0    11.0    14.0                      NaN
7      7.0     0.0     2.0    11.0                      NaN
8      2.0     0.0     4.0    12.0                      NaN
9      4.0     0.0     0.0     6.0                      NaN
10     NaN     NaN     NaN     NaN  [11.6, 4.1, 14.9, 17.5]

我想知道是否有更有效的方法来添加一个索引'mean'的行和每个列的平均值到pandas DataFrame的底部.

Answer 1

使用loc了与放大设置:

df.loc['mean'] = df.mean()

结果输出:

       diode1  diode2  diode3  diode4
Time                                 
0.53      7.0     0.0    10.0    16.0
1.218    17.0     7.0    14.0    19.0
1.895    13.0     8.0    16.0    17.0
2.57      8.0     2.0    16.0    17.0
3.24     14.0     8.0    17.0    19.0
3.91     13.0     6.0    17.0    18.0
4.594    13.0     5.0    16.0    19.0
5.265     9.0     0.0    12.0    16.0
5.948    12.0     3.0    16.0    17.0
6.632    10.0     2.0    15.0    17.0
mean     11.6     4.1    14.9    17.5