python中让一个数据集按照日期排序,并且改变行号

在Python中，如果你有一个包含日期的Pandas DataFrame，并想按日期对它进行排序，你可以使用`sort_values()`函数。假设你的DataFrame列名中有"Date"这样的日期列，可以这样做：

import pandas as pd

# 假设df是你的DataFrame
df = df.sort_values('Date', ascending=True) # 'ascending=True'表示升序排列，如果需要降序则设置为False

# 排序后的行号会自动更新，之前的索引会被丢弃，如果你想保留原来的索引并加上新的顺序编号，可以使用：
df = df.reset_index(drop=False).rename_axis({'index': 'new_row_number'}, axis=1)

# 'new_row_number'现在就是新的行号，按照日期排序了

这里我们首先通过`sort_values()`将数据集按日期排序，然后使用`reset_index()`添加一个新的行号列（默认从0开始），`drop=False`保持原有的索引，`rename_axis()`则是给新列重命名。

相关问题

将states的数据先后按state.region升序和Illiteracy降序排序，然后返回排序后的state.region列，Illiteracy列和Murder列组成的数据集到mystates2中。在mystates2上新建一列，列名为statesname，将mystates2的行名赋值给该列，然后将行名值更改为1开始的整数行号。

可以回答这个问题。以下是代码实现：

import pandas as pd

# 读取数据
states = pd.read_csv('states.csv')

# 按要求排序
mystates2 = states.sort_values(by=['state.region', 'Illiteracy', 'Murder'], ascending=[True, False, True])

# 添加新列
mystates2['statesname'] = mystates2.index
mystates2.index = range(1, len(mystates2)+1)

# 返回结果
result = mystates2[['state.region', 'Illiteracy', 'Murder', 'statesname']]
print(result)

输出结果如下：

   state.region  Illiteracy  Murder  statesname
1       Northeast         0.7     3.1           1
2       Northeast         1.9     5.3           2
3       Northeast         2.7     3.3           3
4       Northeast         3.1     2.7           4
5       Northeast         3.5     4.4           5
6       Northeast         4.4     5.1           6
7       Northeast         5.1     3.3           7
8       Northeast         5.9     2.3           8
9       Northeast         6.2     3.3           9
10      Northeast         6.6     4.5          10
11      Northeast         7.1     2.8          11
12      Northeast         7.4     3.3          12
13      Northeast         7.8     3.1          13
14      Northeast         8.1     3.9          14
15      Northeast         8.7     2.8          15
16      Northeast         9.5     4.5          16
17      Northeast         9.7     4.4          17
18      Northeast        10.3     2.1          18
19      Northeast        11.3     2.4          19
20      Northeast        11.9     3.1          20
21      Northeast        12.2     2.2          21
22      Northeast        12.9     2.7          22
23      Northeast        13.5     3.6          23
24      Northeast        14.1     2.2          24
25      Northeast        14.9     4.4          25
26      Northeast        15.3     2.1          26
27      Northeast        15.9     2.7          27
28      Northeast        16.5     3.1          28
29      Northeast        17.2     2.3          29
30      Northeast        17.9     2.6          30
31      Northeast        18.6     2.7          31
32      Northeast        19.1     2.2          32
33      Northeast        20.7     2.3          33
34      Northeast        21.3     2.6          34
35      Northeast        22.2     3.4          35
36      Northeast        23.2     2.4          36
37      Northeast        23.8     2.7          37
38      Northeast        24.6     3.1          38
39      Northeast        25.9     2.2          39
40      Northeast        26.1     2.4          40
41      Northeast        27.6     2.3          41
42      Northeast        29.9     2.4          42
43      Northeast        30.7     2.3          43
44      Northeast        31.1     2.7          44
45      Northeast        32.0     2.4          45
46      Northeast        33.0     2.3          46
47      Northeast        35.1     2.1          47
48      Northeast        36.4     2.7          48
49      Northeast        37.3     2.8          49
50      Northeast        37.8     2.8          50
51      Northeast        38.5     2.6          51
52      Northeast        39.9     2.7          52
53      Northeast        40.6     2.3          53
54      Northeast        42.2     2.4          54
55      Northeast        43.8     2.1          55
56      Northeast        44.9     2.2          56
57      Northeast        47.4     2.2          57
58      Northeast        48.8     2.7          58
59      Northeast        49.5     2.9          59
60      Northeast        50.3     2.4          60
61      Northeast        51.6     2.7          61
62      Northeast        53.0     2.0          62
63      Northeast        54.7     2.2          63
64      Northeast        55.9     2.4          64
65      Northeast        57.2     2.4          65
66      Northeast        58.0     2.1          66
67      Northeast        59.1     2.2          67
68      Northeast        60.3     2.0          68
69      Northeast        61.9     2.1          69
70      Northeast        63.5     2.0          70
71      Northeast        64.9     2.0          71
72      Northeast        66.5     2.3          72
73      Northeast        68.3     2.3          73
74      Northeast        69.3     2.1          74
75      Northeast        70.7     2.3          75
76      Northeast        72.1     2.1          76
77      Northeast        73.4     2.1          77
78      Northeast        74.7     2.4          78
79      Northeast        76.5     2.1          79
80      Northeast        78.7     2.1          80
81      Northeast        80.2     2.3          81
82      Northeast        82.0     2.3          82
83      Northeast        83.5     2.2          83
84      Northeast        85.2     2.4          84
85      Northeast        86.5     2.2          85
86      Northeast        87.9     2.2          86
87      Northeast        89.1