Python - Retrieving last 30 days data from dataframe pandas
The other two answers (currently) assume the date is the index, but in python3 at least, you can solve this with just simple masking (.query(..) doesn't work).
df[df["Date"] >= (pd.to_datetime('8/24/2015') - pd.Timedelta(days=30))]
You can use DataFrame.last_valid_index() to find the label of the last line, and then subtract DateOffset(30, 'D') to go back 30 days:
df[df.last_valid_index()-pandas.DateOffset(30, 'D'):]
Date lastdayfrom is used for selecting last 30 days of DataFrame by function loc.
lastdayfrom = pd.to_datetime('8/24/2015')
print lastdayfrom
#2015-08-24 00:00:00
print df
# Error_Description Date Weekend Type
#0 N17739 Limit switch X- 2015-05-01 2015-05-03 Critical
#1 N17739 Limit switch Y- 2015-05-01 2015-05-03 Critical
#2 N938 Key non-functional 2015-05-01 2015-05-03 Non-Critical
#3 P124 Magazine is running 2015-05-01 2015-05-03 Non-Critical
#4 N17738 Limit switch Z+ 2015-02-01 2015-05-03 Critical
#5 N938 Key non-functional 2015-07-25 2015-05-03 Non-Critical
#6 P873 ENCLOSURE DOOR 2015-07-24 2015-08-30 Non-Critical
#7 N3065 Reset M114 2015-07-21 2015-08-21 Non-Critical
#8 N3065 Reset M114, 2015-08-22 2015-08-22 Non-Critical
#9 N2853 Synchronization 2015-08-23 2015-08-30 Critical
#10 P152 ENCLOSURE 2015-08-24 2015-08-30 Non-Critical
#11 N6236 has stopped 2015-08-24 2015-08-30 Critical
print df.dtypes
#Error_Description object
#Date datetime64[ns]
#Weekend datetime64[ns]
#Type object
#dtype: object
#set index from column Date
df = df.set_index('Date')
#if datetimeindex isn't order, order it
df= df.sort_index()
#last 30 days of date lastday
df = df.loc[lastdayfrom - pd.Timedelta(days=30):lastdayfrom].reset_index()
print df
# Date Error_Description Weekend Type
#0 2015-07-25 N3065 Reset M114 2015-08-21 Non-Critical
#1 2015-08-22 N3065 Reset M114, 2015-08-22 Non-Critical
#2 2015-08-23 N2853 Synchronization 2015-08-30 Critical
#3 2015-08-24 P152 ENCLOSURE 2015-08-30 Non-Critical
#4 2015-08-24 N6236 has stopped 2015-08-30 Critical