pandas DataFrame 行列索引及值的获取的方法

import pandas as pd

df = pd.DataFrame({'A': [0, 1, 2], 'B': [3, 4, 5]})
print df

# 结果:
  A B
0 0 3
1 1 4
2 2 5

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

print(ridership_df['R003'])

# 结果:
05-01-11    0
05-02-11  1478
05-03-11  1613
05-04-11  1560
05-05-11  1608
05-06-11  1576
05-07-11   95
05-08-11    2
05-09-11  1438
05-10-11  1342
Name: R003, dtype: int64

print(ridership_df.loc['05-01-11'])
# 或者
print(ridership_df.iloc[0])


# 结果:
R003  0
R004  0
R005  2
R006  5
R007  0
Name: 05-01-11, dtype: int64

print(ridership_df.loc['05-05-11','R003'])
# 或者
print(ridership_df.iloc[4,0])

# 结果:
1608

print(ridership_df.values)

# 结果:
[[  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]]

def mean_riders_for_max_station(ridership):
  max_index = ridership.iloc[0].argmax()
  mean_for_max = ridership[max_index].mean()
  overall_mean = ridership.values.mean()
  return (overall_mean, mean_for_max)

print mean_riders_for_max_station(ridership_df)

# 结果:
(2342.6, 3239.9)