pandas 将熊猫日期时间列 yyyy-mm-dd 转换为 YYYMMDD
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convert pandas datetime column yyyy-mm-dd to YYYMMDD
提问by user3757265
I have a dateframe with datetime column in the format yyyy-mm-dd.
我有一个日期时间列的日期框，格式为 yyyy-mm-dd。
I would like to have it in interger format yyyymmdd . I keep throwing an error using this
我想以整数格式 yyyymmdd 使用它。我一直在用这个抛出错误
x=dates.apply(dt.datetime.strftime('%Y%m%d')).astype(int)
TypeError: descriptor 'strftime' requires a 'datetime.date' object but received a 'str'
This doesn't not work as i tried to pass an array. I know that if I pass just on element it will convert, but how do I do it more pythonic? I did try using lambda but that didn't work either.
这不起作用，因为我试图传递一个数组。我知道如果我只传递元素它会转换，但我如何做更pythonic？我确实尝试使用 lambda 但这也不起作用。
回答by Scott Boston
If your column is a string, you will need to first use `pd.to_datetime',
如果您的列是字符串，则需要先使用“pd.to_datetime”，
df['Date'] = pd.to_datetime(df['Date'])
Then, use .dtdatetime accessor with strftime:
然后，使用.dt日期时间访问器strftime：
df = pd.DataFrame({'Date':pd.date_range('2017-01-01', periods = 60, freq='D')})
df.Date.dt.strftime('%Y%m%d').astype(int)
Or use lambda function:
或者使用 lambda 函数：
df.Date.apply(lambda x: x.strftime('%Y%m%d')).astype(int)
Output:
输出：
0 20170101
1 20170102
2 20170103
3 20170104
4 20170105
5 20170106
6 20170107
7 20170108
8 20170109
9 20170110
10 20170111
11 20170112
12 20170113
13 20170114
14 20170115
15 20170116
16 20170117
17 20170118
18 20170119
19 20170120
20 20170121
21 20170122
22 20170123
23 20170124
24 20170125
25 20170126
26 20170127
27 20170128
28 20170129
29 20170130
30 20170131
31 20170201
32 20170202
33 20170203
34 20170204
35 20170205
36 20170206
37 20170207
38 20170208
39 20170209
40 20170210
41 20170211
42 20170212
43 20170213
44 20170214
45 20170215
46 20170216
47 20170217
48 20170218
49 20170219
50 20170220
51 20170221
52 20170222
53 20170223
54 20170224
55 20170225
56 20170226
57 20170227
58 20170228
59 20170301
Name: Date, dtype: int32
回答by YOBEN_S
You know what? I have a dirty way
你知道吗？我有一个肮脏的方式
df.Date.dt.year*10000+df.Date.dt.month*100+df.Date.dt.day
Out[498]:
0 20170101
1 20170102
2 20170103
3 20170104
4 20170105
5 20170106
6 20170107
7 20170108
8 20170109
9 20170110
10 20170111
11 20170112
12 20170113
13 20170114
14 20170115
15 20170116
16 20170117
17 20170118
18 20170119
19 20170120
20 20170121
21 20170122
22 20170123
23 20170124
24 20170125
25 20170126
26 20170127
27 20170128
28 20170129
29 20170130
30 20170131
31 20170201
32 20170202
33 20170203
34 20170204
35 20170205
36 20170206
37 20170207
38 20170208
39 20170209
40 20170210
41 20170211
42 20170212
43 20170213
44 20170214
45 20170215
46 20170216
47 20170217
48 20170218
49 20170219
50 20170220
51 20170221
52 20170222
53 20170223
54 20170224
55 20170225
56 20170226
57 20170227
58 20170228
59 20170301
Name: Date, dtype: int64
