本文介绍了如何使用pymongo在mongodb中将整个列从字符串类型转换为日期类型的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!
问题描述
我的数据包含100万行.示例如下:
My data consist of 1million rows. A sample look like this:
_id:object("603678958a6eade21c0790b8")
id1:3758
date2:2010-01-01
time3:00:05:00
date4 :2009-12-31
time5:19:05:00
id6 :2
id7:-79.09
id8:35.97
id9:5.5
id10:0
id11:-99999
id12 :0
id13 :-9999
c14:"U"
id15:0
id16:99
id17:0
id18:-99
id19:-9999
id20:33
id21:0
id22:-99
id23:0
问题是date2和date4的格式是我想要的,但是它们是字符串,我想将它们转换为日期.我使用的代码如下所示:
The thing is that date2 and date4 are in the form that i want but they are string and i want to convert them to date.The code i have used look like this:
df['date4'] = df['date4'].astype('datetime64[ns]')
df['date2'] = df['date2'].astype('datetime64[ns]')
df['time3'] = df['time3'].apply(lambda x:datetime.datetime.strptime(x[0]+x[1]+":"+x[2]+x[3], '%H:%M'))
df['time5'] = df['time5'].apply( lambda x: datetime.datetime.strptime(x[0] + x[1] + ":" + x[2] + x[3], '%H:%M'))
df['date2'] = df['date2'].apply(lambda x: arrow.get(x).format("YYYY-MM-DD"))
df['date4'] = df['date4'].apply(lambda x: arrow.get(x).format("YYYY-MM-DD"))
df['time3'] = df['time3'].apply(lambda x: arrow.get(x).format("HH:mm:ss"))
df['time5'] = df['time5'].apply(lambda x: arrow.get(x).format("HH:mm:ss"))
在插入之前或之后是否需要转换它们?有人知道我该怎么做吗?
Do i need to convert them before inserting or after?Does anyone know how i can do that?
推荐答案
如果是我,我想将date2/time3合并为一列,将date4/time5合并为一列,如:
If it were me, I'd want to combine date2/time3 into one column, and date4/time5, as in:
df['date2'] = (df['date2']+'T'+df['time3']).astype('datetime64')
df['date4'] = (df['date4']+'T'+df['time5']).astype('datetime64')
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