pandas 过滤过去 x 天的熊猫数据框
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filter pandas dataframe for past x days
提问by Josh
I have a dataframe with a date column that I update daily. I'd like to create a copy of it with just the past 30 day's of data.
我有一个包含我每天更新的日期列的数据框。我想用过去 30 天的数据创建它的副本。
I tried the following syntax based on what I know about doing this in R:
我根据我对在 R 中执行此操作的了解尝试了以下语法：
df[df[date]>dt.date.today()-30]
The date column is not the index but I'm not opposed to making it so if that helps!
日期列不是索引，但我不反对这样做，如果有帮助的话！
Thanks!
谢谢！
回答by TurtleIzzy
Try this:
尝试这个：
import datetime
import pandas as pd
df[df.the_date_column > datetime.datetime.now() - pd.to_timedelta("30day")]
Update: Edited as suggested by Josh.
更新：按照 Josh 的建议进行编辑。
回答by piRSquared
consider the df
考虑 df
today = pd.datetime.today().date()
begin = today - pd.offsets.Day(90)
tidx = pd.date_range(begin, today)
df = pd.DataFrame(dict(A=np.arange(len(tidx))), tidx)
you can slice the last 30 days like this
你可以像这样切片过去 30 天
cut_off = today - pd.offsets.Day(29)
df[cut_off:]
A
2016-09-23 61
2016-09-24 62
2016-09-25 63
2016-09-26 64
2016-09-27 65
2016-09-28 66
2016-09-29 67
2016-09-30 68
2016-10-01 69
2016-10-02 70
2016-10-03 71
2016-10-04 72
2016-10-05 73
2016-10-06 74
2016-10-07 75
2016-10-08 76
2016-10-09 77
2016-10-10 78
2016-10-11 79
2016-10-12 80
2016-10-13 81
2016-10-14 82
2016-10-15 83
2016-10-16 84
2016-10-17 85
2016-10-18 86
2016-10-19 87
2016-10-20 88
2016-10-21 89
2016-10-22 90
