Python pandas finding data in between time

Question

I am using crime statistics (in a data frame)and I am trying to find when most crimes occur between 12 am-8am,8am-4pm, and 4pm-12pm. I have already converted the column to DateTime. the code I used is:

#first attempt
df_15['FIRST_OCCURRENCE_DATE']=pd.date_range('01/01/2015',periods=10000,freq='H')
df_15[(df_15['FIRST_OCCURrENCE_DATE'] > '2015-1-1 00:00:00') & (df_15['FIRST_OCCURRENCE_DATE'] <= '2015-12-31 08:00:00')]

#second attempt
df_15 = df_15.set_index(df_15['FIRST_OCCURRENCE_DATE'])
df_15.loc['2015-01-01 00:00:00':'2015-12-31 00:00:00']

#third attempt
date_rng = pd.date_range(start='00:00:00', end='08:00:00',freq='H')
date_rng1 = pd.DataFrame(date_rng)
date_rng1.head(30)

#fourth attempt
df_15.FIRST_OCCURRENCE_DATE.dt.hour
ts = pd.to_datetime('12/31/2015 08:00:00')
df_15.loc[df_15.FIRST_OCCURRENCE_DATE <= ts,:].head()

The results I get are time entries that go outside of 08:00:00.

PS. all the data is from the same year

I would like to get a total count of crimes that happened in each time interval. For example 12,000 between 12am(00:00:00)-8am(08:00:00). 10,000 from 8am-4pm — S. Caruso
– S. Caruso, Commented Oct 9, 2018 at 23:08

cs95 · Accepted Answer · 2018-10-09 23:34:46Z

2

Looks like you can just do a little arithmetic and count:

(df_15['FIRST_OCCURrENCE_DATE'].dt.hour // 8).value_counts()

There are a lot of ways to solve this problem but this is likely the simplest. Extract the hour of day from each date, find which time slot it belongs to. Floor-divide by 8 to get 0 (12AM-8AM), 1 (8AM-4PM), or 2 (4PM-12AM) for each, and just count these occurrences.

edited Oct 9, 2018 at 23:34

answered Oct 9, 2018 at 23:10

cs95

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2 Comments

S. Caruso Over a year ago

I tried that and I got a syntax error: df_15['FIRST_OCCURRENCE_DATE'].dt.hour//8).value_counts() ^ when i removed the ) it showed a syntaxerror:value_counts

cs95 Over a year ago

@S.Caruso Sorry, that was a copy-paste error. Can you try again please

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