和numpy數組(5)-二維數組的軸一樣,pandas DataFrame也有軸的概念,決定了方法是對行應用還是對列應用:

以下面這個數據為例說明:

這個數據是5個車站10天內的客流數據:

ridership_df = pd.DataFrame(
    data=[[   0,    0,    2,    5,    0],
          [1478, 3877, 3674, 2328, 2539],
          [1613, 4088, 3991, 6461, 2691],
          [1560, 3392, 3826, 4787, 2613],
          [1608, 4802, 3932, 4477, 2705],
          [
 
1576, 3933, 3909, 4979, 2685],
          [  95,  229,  255,  496,  201],
          [   2,    0,    1,   27,    0],
          [1438, 3785, 3589, 4174, 2215],
          [1342, 4043, 4009, 4665, 3033]],
    index=[‘05-01-11‘, ‘05-02-11‘, ‘05-03-11‘, ‘05-04-11‘, ‘05-05-11‘,
           ‘05-06-11‘, ‘05-07-11‘, ‘05-08-11‘, ‘05-09-11
 
‘, ‘05-10-11‘],
    columns=[‘R003‘, ‘R004‘, ‘R005‘, ‘R006‘, ‘R007‘]
)

          R003  R004  R005  R006  R007
05-01-11     0     0     2     5     0
05-02-11  1478  3877  3674  2328  2539
05-03-11  1613  4088  3991  6461  2691
05-04-11  1560  3392  3826  4787  2613
05-05-11  1608  4802  3932  4477  2705
05-06-11  1576  3933  3909  4979  2685
05-07-11    95   229   255   496   201
05-08-11     2     0     1    27     0
 
05-09-11  1438  3785  3589  4174  2215
05-10-11  1342  4043  4009  4665  3033

這個數據裏,行表示每一天裏各個站的客流,列表示每一個站裏各天的客流

如果要計算每天各個站的平均客流:

print(ridership_df.mean(axis=1))

or:

print(ridership_df.mean(axis=‘columns‘))

05-01-11       1.4
05-02-11    2779.2
05-03-11    3768.8
05-04-11    3235.6
05-05-11    3504.8
05-06-11    3416.4
05-07-11     255.2
05-08-11       6.0
05-09-11    3040.2
05-10-11    3418.4
dtype: float64

如果要計算每個站各天的平均客流:

print(ridership_df.mean(axis=0))

or:

print(ridership_df.mean(axis=‘index‘))

R003    1071.2
R004    2814.9
R005    2718.8
R006    3239.9
R007    1868.2
dtype: float64

*總結:

axis=0或者axis=‘index‘,計算列

axis=1或者axis=‘columns‘,計算行

pandas DataFrame(3)-軸