- Trending Categories
- Data Structure
- Networking
- RDBMS
- Operating System
- Java
- MS Excel
- iOS
- HTML
- CSS
- Android
- Python
- C Programming
- C++
- C#
- MongoDB
- MySQL
- Javascript
- PHP
- Physics
- Chemistry
- Biology
- Mathematics
- English
- Economics
- Psychology
- Social Studies
- Fashion Studies
- Legal Studies

- Selected Reading
- UPSC IAS Exams Notes
- Developer's Best Practices
- Questions and Answers
- Effective Resume Writing
- HR Interview Questions
- Computer Glossary
- Who is Who

# How does the pandas series.divmod() method work?n

The divmod() method in the pandas series constructor is used to perform integer division and modulo of two series objects. We can calculate the divmod() of one series with a scalar value. And we can perform element-wise divmod() operation.

The method returns a python tuple with two series objects, the first series of the tuple is representing the integer division results, and the second series object of the tuple representing the modulo division results.

The method performs an element-wise division operation of two series objects. There is a parameter called fill_value, which is used to fill the specified values in the place of missing values while executing the divmod() method, by default it will fill missing values with Nan.

## Example 1

# import pandas packages import pandas as pd # Creating Series objects series1 = pd.Series([96, 75, 23, 17, 30], index=['A', 'B', 'C', 'D', 'E']) print('First series object:',series1) series2 = pd.Series([8, 6, 4, 5, 3], index=['A', 'B', 'C', 'D', 'F']) print('second series object:',series2) print("Divmod of Series1 and Series2:", series1.divmod(series2))

## Explanation

In this example, we will divide two series objects by using the divmod() method without changing any default parameter values.

## Output

First series object: A 96 B 75 C 23 D 17 E 30 dtype: int64 second series object: A 8 B 6 C 4 D 5 F 3 dtype: int64 Divmod of Series1 and Series2: (A 12.0 B 12.0 C 5.0 D 3.0 E NaN F NaN dtype: float64, A 0.0 B 3.0 C 3.0 D 2.0 E NaN F NaN dtype: float64)

In the above output block, we can see the tuple of two series objects. The First object represents the integer division values and the second one represents the modulo values of the divmod() method on two series objects.

## Example 2

# import pandas packages import pandas as pd # Creating Series objects series1 = pd.Series([36, 85, 4, 13, 34], index=['A', 'B', 'C', 'D', 'E']) print('First series object:',series1) series2 = pd.Series([7, 8, 1, 6, 8], index=['A', 'B', 'C', 'D', 'F']) print('second series object:',series2) print("Divmod of Series1 and Series2:", series1.divmod(series2, fill_value=10))

## Explanation

Initially, we have created two pandas Series with labeled indexes. After that, we applied the divmod() method with the fill_value parameter.

## Output

First series object: A 36 B 85 C 4 D 13 E 34 dtype: int64 second series object: A 7 B 8 C 1 D 6 F 8 dtype: int64 Divmod of Series1 and Series2: (A 5.0 B 10.0 C 4.0 D 2.0 E 3.0 F 1.0 dtype: float64, A 1.0 B 5.0 C 0.0 D 1.0 E 4.0 F 2.0 dtype: float64)

In the above output block, we can see the tuple of two series objects. While executing divmod() method the Nan values are replaced with 10, which is defined by the fill_value parameter.

- Related Articles
- How does the pandas Series idxmax() method work?
- How does the pandas Series idxmin() method work?
- How does pandas series astype() method work?
- How does pandas series combine() method work?
- How does pandas series combine_first() method work?
- How does pandas series div() method work?
- How does pandas series argsort work?
- How does the pandas series.ffill() method work?
- How does the pandas series.expanding() method work?
- How does the pandas series.first_valid_index() method work?
- How does the pandas series.gt() method work if the series object contains string-type elements?
- How does the series.copy() method work in Pandas?
- How does the series.corr() method work in pandas?
- How does the series.cummax() method work in Pandas?
- How does the series.cumprod() method work in Pandas?
- How does the series.cumsum() method work in Pandas?