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
- DataFrame
- Panel
- Panel4D
- Index
- pandas.Index
- pandas.Index.T
- pandas.Index.asi8
- pandas.Index.base
- pandas.Index.data
- pandas.Index.dtype
- pandas.Index.dtype_str
- pandas.Index.flags
- pandas.Index.has_duplicates
- pandas.Index.hasnans
- pandas.Index.inferred_type
- pandas.Index.is_all_dates
- pandas.Index.is_monotonic
- pandas.Index.is_monotonic_decreasing
- pandas.Index.is_monotonic_increasing
- pandas.Index.is_unique
- pandas.Index.itemsize
- pandas.Index.name
- pandas.Index.names
- pandas.Index.nbytes
- pandas.Index.ndim
- pandas.Index.nlevels
- pandas.Index.shape
- pandas.Index.size
- pandas.Index.strides
- pandas.Index.values
- pandas.Index.all
- pandas.Index.any
- pandas.Index.append
- pandas.Index.argmax
- pandas.Index.argmin
- pandas.Index.argsort
- pandas.Index.asof
- pandas.Index.asof_locs
- pandas.Index.astype
- pandas.Index.copy
- pandas.Index.delete
- pandas.Index.difference
- pandas.Index.drop
- pandas.Index.drop_duplicates
- pandas.Index.dropna
- pandas.Index.duplicated
- pandas.Index.equals
- pandas.Index.factorize
- pandas.Index.fillna
- pandas.Index.format
- pandas.Index.get_duplicates
- pandas.Index.get_indexer
- pandas.Index.get_indexer_for
- pandas.Index.get_indexer_non_unique
- pandas.Index.get_level_values
- pandas.Index.get_loc
- pandas.Index.get_slice_bound
- pandas.Index.get_value
- pandas.Index.get_values
- pandas.Index.groupby
- pandas.Index.holds_integer
- pandas.Index.identical
- pandas.Index.insert
- pandas.Index.intersection
- pandas.Index.is
- pandas.Index.is_boolean
- pandas.Index.is_categorical
- pandas.Index.is_floating
- pandas.Index.is_integer
- pandas.Index.is_lexsorted_for_tuple
- pandas.Index.is_mixed
- pandas.Index.is_numeric
- pandas.Index.is_object
- pandas.Index.is_type_compatible
- pandas.Index.isin
- pandas.Index.item
- pandas.Index.join
- pandas.Index.map
- pandas.Index.max
- pandas.Index.memory_usage
- pandas.Index.min
- pandas.Index.nunique
- pandas.Index.order
- pandas.Index.putmask
- pandas.Index.ravel
- pandas.Index.reindex
- pandas.Index.rename
- pandas.Index.repeat
- pandas.Index.reshape
- pandas.Index.searchsorted
- pandas.Index.set_names
- pandas.Index.set_value
- pandas.Index.shift
- pandas.Index.slice_indexer
- pandas.Index.slice_locs
- pandas.Index.sort
- pandas.Index.sort_values
- pandas.Index.sortlevel
- pandas.Index.str
- pandas.Index.summary
- pandas.Index.sym_diff
- pandas.Index.symmetric_difference
- pandas.Index.take
- pandas.Index.to_datetime
- pandas.Index.to_native_types
- pandas.Index.to_series
- pandas.Index.tolist
- pandas.Index.transpose
- pandas.Index.union
- pandas.Index.unique
- pandas.Index.value_counts
- pandas.Index.view
- pandas.Index.where
- Attributes
- Modifying and Computations
- Conversion
- Sorting
- Time-specific operations
- Combining / joining / set operations
- Selecting
- pandas.Index
- CategoricalIndex
- MultiIndex
- DatetimeIndex
- TimedeltaIndex
- Window
- GroupBy
- Resampling
- Style
- General utility functions
- Internals
- Release Notes
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pandas.Index.is¶
-
Index.is_(other)[source]¶ More flexible, faster check like
isbut that works through viewsNote: this is not the same as
Index.identical(), which checks that metadata is also the same.Parameters: other : object
other object to compare against.
Returns: True if both have same underlying data, False otherwise : bool