Table Of Contents
- What’s New
- Installation
- Contributing to pandas
- Frequently Asked Questions (FAQ)
- Package overview
- 10 Minutes to pandas
- Tutorials
- Cookbook
- Intro to Data Structures
- Essential Basic Functionality
- Working with Text Data
- Options and Settings
- Indexing and Selecting Data
- MultiIndex / Advanced Indexing
- Computational tools
- Working with missing data
- Group By: split-apply-combine
- Merge, join, and concatenate
- Reshaping and Pivot Tables
- Time Series / Date functionality
- Time Deltas
- Categorical Data
- Visualization
- Style
- IO Tools (Text, CSV, HDF5, ...)
- Remote Data Access
- Enhancing Performance
- Sparse data structures
- Caveats and Gotchas
- rpy2 / R interface
- pandas Ecosystem
- Comparison with R / R libraries
- Comparison with SQL
- Comparison with SAS
- API Reference
- Input/Output
- General functions
- Series
- Constructor
- Attributes
- Conversion
- Indexing, iteration
- Binary operator functions
- pandas.Series.add
- pandas.Series.sub
- pandas.Series.mul
- pandas.Series.div
- pandas.Series.truediv
- pandas.Series.floordiv
- pandas.Series.mod
- pandas.Series.pow
- pandas.Series.radd
- pandas.Series.rsub
- pandas.Series.rmul
- pandas.Series.rdiv
- pandas.Series.rtruediv
- pandas.Series.rfloordiv
- pandas.Series.rmod
- pandas.Series.rpow
- pandas.Series.combine
- pandas.Series.combine_first
- pandas.Series.round
- pandas.Series.lt
- pandas.Series.gt
- pandas.Series.le
- pandas.Series.ge
- pandas.Series.ne
- pandas.Series.eq
- Function application, GroupBy
- Computations / Descriptive Stats
- Reindexing / Selection / Label manipulation
- Missing data handling
- Reshaping, sorting
- Combining / joining / merging
- Time series-related
- Datetimelike Properties
- String handling
- Categorical
- Plotting
- Serialization / IO / Conversion
- Sparse methods
- DataFrame
- Panel
- Panel4D
- Index
- CategoricalIndex
- DatetimeIndex
- TimedeltaIndex
- GroupBy
- Style
- General utility functions
- Internals
- Release Notes
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pandas.Series.round¶
- Series.round(decimals=0, out=None)¶
Return a with each element rounded to the given number of decimals.
Refer to numpy.around for full documentation.
See also
- numpy.around
- equivalent function