Title: Group Pandas Data By Hour Of The Day
Slug: group_pandas_data_by_hour_of_the_day
Summary: Group data by hour of the day using pandas.
Date: 2016-12-21 12:00
Category: Python
Tags: Data Wrangling
Authors: Chris Albon

Preliminaries



In [1]:

    
# Import libraries
import pandas as pd
import numpy as np

Create Data



In [2]:

    
# Create a time series of 2000 elements, one very five minutes starting on 1/1/2000
time = pd.date_range('1/1/2000', periods=2000, freq='5min')

# Create a pandas series with a random values between 0 and 100, using 'time' as the index
series = pd.Series(np.random.randint(100, size=2000), index=time)

View Data



In [3]:

    
# View the first few rows of the data
series[0:10]









    Out[3]:





2000-01-01 00:00:00    40
2000-01-01 00:05:00    13
2000-01-01 00:10:00    99
2000-01-01 00:15:00    72
2000-01-01 00:20:00     4
2000-01-01 00:25:00    36
2000-01-01 00:30:00    24
2000-01-01 00:35:00    20
2000-01-01 00:40:00    83
2000-01-01 00:45:00    44
Freq: 5T, dtype: int64

Group Data By Time Of The Day



In [4]:

    
# Group the data by the index's hour value, then aggregate by the average
series.groupby(series.index.hour).mean()









    Out[4]:





0     50.380952
1     49.380952
2     49.904762
3     53.273810
4     47.178571
5     46.095238
6     49.047619
7     44.297619
8     53.119048
9     48.261905
10    45.166667
11    54.214286
12    50.714286
13    56.130952
14    50.916667
15    42.428571
16    46.880952
17    56.892857
18    54.071429
19    47.607143
20    50.940476
21    50.511905
22    44.550000
23    50.250000
dtype: float64