import pandas as pd
 
# Create dates dataframe with frequency 
data = pd.date_range('1/1/2011', periods = 10, freq ='H')
 
data

# Create date and time with dataframe
data = pd.date_range('1/1/2011', periods = 10, freq ='H')
 
x = pd.datetime.now()
x.month, x.year

(9, 2018)

# Create date and time with dataframe
rng = pd.DataFrame()
rng['date'] = pd.date_range('1/1/2011', periods = 72, freq ='H')
 
# Print the dates in dd-mm-yy format
rng[:5]
 
# Create features for year, month, day, hour, and minute
rng['year'] = rng['date'].dt.year
rng['month'] = rng['date'].dt.month
rng['day'] = rng['date'].dt.day
rng['hour'] = rng['date'].dt.hour
rng['minute'] = rng['date'].dt.minute
 
# Print the dates divided into features
rng.head(3)

# Input present datetime using Timestamp
t = pandas.tslib.Timestamp.now()
t

Timestamp('2018-09-18 17:18:49.101496')

# Convert timestamp to datetime
t.to_datetime()

datetime.datetime(2018, 9, 18, 17, 18, 49, 101496)

# Directly access and print the features
t.year
t.month
t.day
t.hour
t.minute
t.second

2018
8
25
15
53

import pandas as pd
 
url = 'http://bit.ly/uforeports'
 
# read csv file
df = pd.read_csv(url)          
df.head()

# Convert the Time column to datetime format
df['Time'] = pd.to_datetime(df.Time)
 
df.head()

# shows the type of each column data
df.dtypes

City                       object
Colors Reported            object
Shape Reported             object
State                      object
Time               datetime64[ns]
dtype: object

# Get hour detail from time data
df.Time.dt.hour.head()

0    22
1    20
2    14
3    13
4    19
Name: Time, dtype: int64

# Get name of each date
df.Time.dt.weekday_name.head()

0     Sunday
1     Monday
2     Sunday
3     Monday
4    Tuesday
Name: Time, dtype: object

# Get ordinal day of the year
df.Time.dt.dayofyear.head()

0    152
1    181
2     46
3    152
4    108
Name: Time, dtype: int64