x y xm ym mdb wat tile
43460 2095 623424.9213 -3891371.696 1 10324 38
43010 2599 638544.9213 -3877871.696 1 1 38
35871 2702 641634.9213 -3663701.696 1 0 50
43451 3296 659454.9213 -3891101.696 1 5951 38
40081 3330 660474.9213 -3790001.696 1 0 38
39084 3796 674454.9213 -3760091.696 1 0 50
6910 34119 1584144.921 -2794871.696 1 0 128
7040 29565 1447524.921 -2798771.696 1 0 127
7452 27335 1380624.921 -2811131.696 1 0 127
7976 34974 1609794.921 -2826851.696 1 0 128
答案 0 :(得分：0)
pandas让这很容易。
import pandas as pd
# Read in the csv file
df = pd.read_csv('input_file.csv')
>>> df
x y xm ym mdb wat tile
0 43460 2095 623424.9213 -3891371.696 1 10324 38
1 43010 2599 638544.9213 -3877871.696 1 1 38
2 35871 2702 641634.9213 -3663701.696 1 0 50
3 43451 3296 659454.9213 -3891101.696 1 5951 38
4 40081 3330 660474.9213 -3790001.696 1 0 38
5 39084 3796 674454.9213 -3760091.696 1 0 50
6 6910 34119 1584144.9210 -2794871.696 1 0 128
7 7040 29565 1447524.9210 -2798771.696 1 0 127
8 7452 27335 1380624.9210 -2811131.696 1 0 127
9 7976 34974 1609794.9210 -2826851.696 1 0 128
# Do the actual sort. I've chosen x and y for sorting here, arbitrarily as an example
df_sorted = df.sort(['x','y'], ascending=[1,0]) # This sorts column x ascending and y descending
>>> df_sorted
x y xm ym mdb wat tile
6 6910 34119 1584144.9210 -2794871.696 1 0 128
7 7040 29565 1447524.9210 -2798771.696 1 0 127
8 7452 27335 1380624.9210 -2811131.696 1 0 127
9 7976 34974 1609794.9210 -2826851.696 1 0 128
2 35871 2702 641634.9213 -3663701.696 1 0 50
5 39084 3796 674454.9213 -3760091.696 1 0 50
4 40081 3330 660474.9213 -3790001.696 1 0 38
1 43010 2599 638544.9213 -3877871.696 1 1 38
3 43451 3296 659454.9213 -3891101.696 1 5951 38
0 43460 2095 623424.9213 -3891371.696 1 10324 38
# Write output to csv if you want
df_sorted.to_csv('output_csv.csv', index=False)