Python | Pandas Series.dt.microsecond Last Updated : 20 Mar, 2019 Comments Improve Suggest changes Like Article Like Report Series.dt can be used to access the values of the series as datetimelike and return several properties. Pandas Series.dt.microsecond attribute return a numpy array containing the microsecond of the datetime in the underlying data of the given series object. Syntax: Series.dt.microsecond Parameter : None Returns : numpy array Example #1: Use Series.dt.microsecond attribute to return the microsecond of the datetime in the underlying data of the given Series object. Python3 # importing pandas as pd import pandas as pd # Creating the Series sr = pd.Series(pd.date_range('2012-12-12 12:12', periods = 5, freq = '5U')) # Creating the index idx = ['Day 1', 'Day 2', 'Day 3', 'Day 4', 'Day 5'] # set the index sr.index = idx # Print the series print(sr) Output : Now we will use Series.dt.microsecond attribute to return the microsecond of the datetime in the underlying data of the given Series object. Python3 # return the microsecond result = sr.dt.microsecond # print the result print(result) Output : As we can see in the output, the Series.dt.microsecond attribute has successfully accessed and returned the microsecond of the datetime in the underlying data of the given series object. Example #2 : Use Series.dt.microsecond attribute to return the microsecond of the datetime in the underlying data of the given Series object. Python3 # importing pandas as pd import pandas as pd # Creating the Series sr = pd.Series(pd.date_range('2008-2-9 08:20:21', periods = 5, freq = '9U')) # Creating the index idx = ['Day 1', 'Day 2', 'Day 3', 'Day 4', 'Day 5'] # set the index sr.index = idx # Print the series print(sr) Output : Now we will use Series.dt.microsecond attribute to return the microsecond of the datetime in the underlying data of the given Series object. Python3 # return the microsecond result = sr.dt.microsecond # print the result print(result) Output : As we can see in the output, the Series.dt.microsecond attribute has successfully accessed and returned the microsecond of the datetime in the underlying data of the given series object. Comment S Shubham__Ranjan Follow 0 Improve S Shubham__Ranjan Follow 0 Improve Article Tags : Pandas Python-pandas Python pandas-series-datetime AI-ML-DS With Python Explore Pandas Tutorial 4 min read IntroductionPandas Introduction 3 min read How to Install Pandas in Python? 5 min read How To Use Jupyter Notebook - An Ultimate Guide 5 min read Creating ObjectsCreating a Pandas DataFrame 2 min read Python Pandas Series 5 min read Creating a Pandas Series 3 min read Viewing DataPandas Dataframe/Series.head() method - Python 3 min read Pandas Dataframe/Series.tail() method - Python 3 min read Pandas DataFrame describe() Method 4 min read Selection & SlicingDealing with Rows and Columns in Pandas DataFrame 5 min read Pandas Extracting rows using .loc[] - Python 3 min read Extracting rows using Pandas .iloc[] in Python 7 min read Indexing and Selecting Data with Pandas 4 min read Boolean Indexing in Pandas 6 min read Python | Pandas DataFrame.ix[ ] 2 min read Python | Pandas Series.str.slice() 3 min read How to take column-slices of DataFrame in Pandas? 2 min read OperationsPython | Pandas.apply() 4 min read Apply function to every row in a Pandas DataFrame 3 min read Python | Pandas Series.apply() 3 min read Pandas dataframe.aggregate() | Python 2 min read Pandas DataFrame mean() Method 2 min read Python | Pandas Series.mean() 2 min read Python | Pandas dataframe.mad() 2 min read Python | Pandas Series.mad() to calculate Mean Absolute Deviation of a Series 2 min read Python | Pandas dataframe.sem() 3 min read Python | Pandas Series.value_counts() 2 min read Pandas Index.value_counts()-Python 3 min read Applying Lambda functions to Pandas Dataframe 6 min read Manipulating DataAdding New Column to Existing DataFrame in Pandas 6 min read Python | Delete rows/columns from DataFrame using Pandas.drop() 4 min read Python | Pandas DataFrame.truncate 3 min read Python | Pandas Series.truncate() 2 min read Iterating over rows and columns in Pandas DataFrame 4 min read Pandas Dataframe.sort_values() 2 min read Python | Pandas Dataframe.sort_values() | Set-2 3 min read How to add one row in existing Pandas DataFrame? 4 min read Grouping DataPandas GroupBy 4 min read Grouping Rows in pandas 2 min read Combining Multiple Columns in Pandas groupby with Dictionary 2 min read Merging, Joining, Concatenating and ComparingPython | Pandas Merging, Joining and Concatenating 8 min read Python | Pandas Series.str.cat() to concatenate string 3 min read Python - Pandas dataframe.append() 4 min read Python | Pandas Series.append() 4 min read Pandas Index.append() - Python 2 min read Python | Pandas Series.combine() 3 min read Add a row at top in pandas DataFrame 1 min read Python | Pandas str.join() to join string/list elements with passed delimiter 2 min read Join two text columns into a single column in Pandas 2 min read How To Compare Two Dataframes with Pandas compare? 5 min read How to compare the elements of the two Pandas Series? 3 min read Working with Date and TimePython | Working with date and time using Pandas 8 min read Python | Pandas Timestamp.timestamp 3 min read Python | Pandas Timestamp.now 3 min read Python | Pandas Timestamp.isoformat 2 min read Python | Pandas Timestamp.date 2 min read Python | Pandas Timestamp.replace 3 min read Pandas.to_datetime()-Python 3 min read Python | pandas.date_range() method 4 min read Like