
Data Structure
Networking
RDBMS
Operating System
Java
MS Excel
iOS
HTML
CSS
Android
Python
C Programming
C++
C#
MongoDB
MySQL
Javascript
PHP
- Selected Reading
- UPSC IAS Exams Notes
- Developer's Best Practices
- Questions and Answers
- Effective Resume Writing
- HR Interview Questions
- Computer Glossary
- Who is Who
Retrieve Rows of a Series Object by Regular Expression in Pandas
By using the regex parameter we can apply the regular expression to the filter() method and this helps to retrieve the rows of the series object. The basic working of series.filter() method in pandas series constructor is used to subset the rows of a series object based on the index labels.
The parameter regex is used to define a search pattern (regular expression) that is used to retrieve the resultant rows.
Example 1
In this following example, we have created a series object using a list of integers and the index labels are created by using the pandas data range function.
# importing pandas package import pandas as pd # create date index index = pd.date_range('2021-08-1', periods=10, freq='10H30min40s') #creating pandas Series with date-time index series = pd.Series([1,2,3,4,5,6,7,8,9,10], index=index) print(series) print("Output: ") # Apply the filter method with regex print(series.filter(regex='40$'))
Explanation
Here, we filter out some rows in the pandas series object by specifying the search pattern using the regex parameter.
Output
The output is given below −
2021-08-01 00:00:00 1 2021-08-01 10:30:40 2 2021-08-01 21:01:20 3 2021-08-02 07:32:00 4 2021-08-02 18:02:40 5 2021-08-03 04:33:20 6 2021-08-03 15:04:00 7 2021-08-04 01:34:40 8 2021-08-04 12:05:20 9 2021-08-04 22:36:00 10 Freq: 37840S, dtype: int64 Output: 2021-08-01 10:30:40 2 2021-08-02 18:02:40 5 2021-08-04 01:34:40 8 Freq: 113520S, dtype: int64
We can notice the above output block, we have successfully filtered the rows of the series object which is having 40 sec in the index.
Example 2
Let’s take another series object to filter out rows whose index label name has a space in it.
# importing pandas package import pandas as pd Countrys = ['Brazil','Canada','New Zealand','Iceland', 'India', 'Sri Lanka', 'United States'] Capitals = [ 'Belmopan','Ottawa','Wellington','Reykjavik', 'New Delhi','Colombo', 'Washington D.C'] #creating pandas Series series = pd.Series(Capitals, index=Countrys) print(series) print("Output: ") # Apply the filter method with regex print(series.filter(regex='. .'))
Output
The output is mentioned below −
Brazil Belmopan Canada Ottawa New Zealand Wellington Iceland Reykjavik India New Delhi Sri Lanka Colombo United States Washington D.C dtype: object Output: New Zealand Wellington Sri Lanka Colombo United States Washington D.C dtype: object
In this above output, we have successfully filtered the few rows named “New Zealand”, “Sri Lanka”, “United States” from the series object.