Pandas is an open-source library built for Python language. It offers various data structures and operations for manipulating numerical data and time series.
Here, let’s use some methods provided by pandas to extract the minute’s value from a timestamp.
Method 1: Use of pandas.Timestamp.minute attribute.
This attribute of pandas can be used to extract the minutes from a given timestamp object.
Example1:
Let’s first create a timestamp object below:
Python3
# import pandas libraryimport pandas as pd # create a Timestamp object time_stamp = pd.Timestamp(2020, 7, 20, 12, 41, 32, 15) # view the created time_stampprint(time_stamp) |
Output:
In the above-created timestamp object, the minute’s value is “41”. Let’s extract this value using the Timestamp.minute attribute.
Python3
# display the value of minute from# the created timestamp objectprint(time_stamp.minute) |
Output:
Example 2:
Create a timestamp object:
Python3
# import pandas libraryimport pandas as pd # create a Timestamp object time_stamp = pd.Timestamp(2020, 7, 20) # view the created time_stampprint(time_stamp) |
Output:
In the above-created timestamp object, the minute’s value is “0”. Let’s extract this value using the Timestamp.minute attribute.
Python3
# display the value of minute from# the created timestamp objectprint(time_stamp.minute) |
Output:
Method 2: Use of Series.dt.minute attribute.
Now, consider the example of a pandas dataframe with one of the columns containing timestamps. In this case, we would first use the Series.dt method to access the values of the series as a DateTime object and then use the minute attribute to extract the minutes from the datetimes object.
Example 1:
First, create a pandas dataframe:
Python3
# import pandas libraryimport pandas as pd # create a seriessr = pd.Series(['2020-7-20 12:41', '2020-7-20 12:42', '2020-7-20 12:43', '2020-7-20 12:44']) # convert the series to datetimesr = pd.to_datetime(sr) # create a pandas dataframe with a# column having timestampsdf = pd.DataFrame(dict(time_stamps = sr)) # view the created dataframeprint(df) |
Output:
Extracting the minute from each of the timestamp in the dataframe:
Python3
# extract minutes from time stamps and# add them as a separate columndf['minutes_from_timestamps'] = df['time_stamps'].dt.minute # view the updated dataframeprint(df) |
Output:
Example 2:
Create a pandas dataframe:
Python3
# import pandas libraryimport pandas as pd # create a seriessr = pd.Series(pd.date_range('2020-7-20 12:41', periods = 5, freq = 'min')) # create a pandas dataframe with a# column having timestampsdf = pd.DataFrame(dict(time_stamps=sr)) # view the created dataframeprint(df) |
Output:
Extracting the minute from each of the timestamp in the dataframe:
Python3
# extract minutes from time stamps and# add them as a separate columndf['minutes_from_timestamps'] = df['time_stamps'].dt.minute # view the updated dataframeprint(df) |
Output:
