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
- Function application, GroupBy & Window
- Computations / Descriptive Stats
- pandas.Series.abs
- pandas.Series.all
- pandas.Series.any
- pandas.Series.autocorr
- pandas.Series.between
- pandas.Series.clip
- pandas.Series.clip_lower
- pandas.Series.clip_upper
- pandas.Series.corr
- pandas.Series.count
- pandas.Series.cov
- pandas.Series.cummax
- pandas.Series.cummin
- pandas.Series.cumprod
- pandas.Series.cumsum
- pandas.Series.describe
- pandas.Series.diff
- pandas.Series.factorize
- pandas.Series.kurt
- pandas.Series.mad
- pandas.Series.max
- pandas.Series.mean
- pandas.Series.median
- pandas.Series.min
- pandas.Series.mode
- pandas.Series.nlargest
- pandas.Series.nsmallest
- pandas.Series.pct_change
- pandas.Series.prod
- pandas.Series.quantile
- pandas.Series.rank
- pandas.Series.sem
- pandas.Series.skew
- pandas.Series.std
- pandas.Series.sum
- pandas.Series.var
- pandas.Series.unique
- pandas.Series.nunique
- pandas.Series.is_unique
- pandas.Series.value_counts
- 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
- MultiIndex
- DatetimeIndex
- TimedeltaIndex
- Window
- GroupBy
- Resampling
- Style
- General utility functions
- Internals
- Release Notes
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pandas.Series.factorize¶
- Series.factorize(sort=False, na_sentinel=-1)¶
Encode the object as an enumerated type or categorical variable
Parameters: sort : boolean, default False
Sort by values
na_sentinel: int, default -1
Value to mark “not found”
Returns: labels : the indexer to the original array
uniques : the unique Index