Index
Symbols
- ! (exclamation point), Shell Commands and Aliases
- != operator, Binary operators and comparisons, Boolean Indexing, Universal Functions: Fast Element-Wise Array Functions
- # (hash mark), Comments
- % (percent sign), About Magic Commands, Basic Profiling: %prun and %run -p
- %matplotlib magic function, A Brief matplotlib API Primer
- & operator, Binary operators and comparisons, set, set, Boolean Indexing
- &= operator, set
- () (parentheses), Function and object method calls, Tuple
- * (asterisk), Introspection
- * operator, Binary operators and comparisons
- ** operator, Binary operators and comparisons
- + operator, Binary operators and comparisons, Tuple, Concatenating and combining lists
- - operator, Binary operators and comparisons, set
- -= operator, set
- . (period), Tab Completion
- / operator, Binary operators and comparisons
- // operator, Binary operators and comparisons, Numeric types
- : (colon), Indentation, not braces
- ; (semicolon), Indentation, not braces
- < operator, Binary operators and comparisons, Universal Functions: Fast Element-Wise Array Functions
- <= operator, Binary operators and comparisons, Universal Functions: Fast Element-Wise Array Functions
- == operator, Binary operators and comparisons, Universal Functions: Fast Element-Wise Array Functions
- > operator, Binary operators and comparisons, Universal Functions: Fast Element-Wise Array Functions
- >= operator, Binary operators and comparisons, Universal Functions: Fast Element-Wise Array Functions
- >>> prompt, The Python Interpreter
- ? (question mark), Introspection-Introspection
- @ symbol, Linear Algebra
- [] (square brackets), Tuple, List
- \ (backslash), Strings, Regular Expressions
- ^ operator, Binary operators and comparisons, set
- ^= operator, set
- _ (underscore), Tab Completion, Unpacking tuples, NumPy dtype Hierarchy, Input and Output Variables
- {} (curly braces), dict, set
- | operator, Binary operators and comparisons, set-set, Boolean Indexing
- |= operator, set
- ~ operator, Boolean Indexing
A
- %a datetime
format, Converting Between String and Datetime
- %A datetime
format, Converting Between String and Datetime
- a(rgs) debugger command, Interactive Debugger
- abs function, Universal Functions: Fast Element-Wise Array Functions, Example: Random Walks
- accumulate method, ufunc Instance Methods
- accumulations, Summarizing and Computing Descriptive Statistics
- add binary function, Universal Functions: Fast Element-Wise Array Functions
- add method, set, Arithmetic methods with fill values
- add_categories method, Categorical Methods
- add_constant function, Estimating Linear Models
- add_patch method, Annotations and Drawing on a Subplot
- add_subplot method, Figures and Subplots
- aggfunc method, Pivot Tables and Cross-Tabulation
- aggregate (agg) method, Data Aggregation, Group Transforms and “Unwrapped” GroupBys
- aggregations (reductions), Mathematical and Statistical Methods
- %alias magic
function, Interacting with the Operating System-Shell Commands and Aliases
- all method, Methods for Boolean Arrays, ufunc Instance Methods
- and keyword, Tab Completion, Booleans, Boolean Indexing
- annotate function, Annotations and Drawing on a Subplot
- annotating in matplotlib, Annotations and Drawing on a Subplot-Annotations and Drawing on a Subplot
- anonymous (lambda) functions, Anonymous (Lambda) Functions
- any built-in function, Tab Completion
- any method, Methods for Boolean Arrays, Simulating Many Random Walks at Once, Detecting and Filtering Outliers
- Apache Parquet format, Using HDF5 Format
- APIs, pandas interacting with, Interacting with Web APIs
- append method, Adding and removing elements, Index Objects
- append mode for files, Files and the Operating System
- apply method, Function Application and Mapping, Unique Values, Value Counts, and Membership, Apply: General split-apply-combine-Example: Group-Wise Linear Regression, Group Transforms and “Unwrapped” GroupBys-Group Transforms and “Unwrapped” GroupBys
- applymap method, Function Application and Mapping
- arange function, Import Conventions, Creating ndarrays
- arccos function, Universal Functions: Fast Element-Wise Array Functions
- arccosh function, Universal Functions: Fast Element-Wise Array Functions
- arcsin function, Universal Functions: Fast Element-Wise Array Functions
- arcsinh function, Universal Functions: Fast Element-Wise Array Functions
- arctan function, Universal Functions: Fast Element-Wise Array Functions
- arctanh function, Universal Functions: Fast Element-Wise Array Functions
- argmax method, Mathematical and Statistical Methods, Example: Random Walks, Summarizing and Computing Descriptive Statistics
- argmin method, Mathematical and Statistical Methods, Summarizing and Computing Descriptive Statistics
- argpartition method, Partially Sorting Arrays
- argsort method, Indirect Sorts: argsort and lexsort, Partially Sorting Arrays
- arithmetic operations
- array function, Creating ndarrays, Creating ndarrays
- arrays (see ndarray object)
- arrow function, Annotations and Drawing on a Subplot
- as keyword, Imports
- asarray function, Creating ndarrays
- asfreq method, Period Frequency Conversion, Upsampling and Interpolation
- assign method, Techniques for Method Chaining
- associative arrays (see dicts)
- asterisk (*), Introspection
- astype method, Data Types for ndarrays
- as_ordered methdo, Categorical Methods
- as_ordered method, Categorical Type in pandas
- as_unordered method, Categorical Methods
- attributes
- for data types, Structured and Record Arrays
- for ndarrays, Creating ndarrays, Reshaping Arrays, Broadcasting Over Other Axes, The Importance of Contiguous Memory
- hidden, Tab Completion
- in DataFrame data
structure, DataFrame
- in Python, Attributes and methods, Correlation and Covariance
- in Series data
structure, Series
- automagic feature, About Magic Commands
- %automagic magic
function, About Magic Commands
- average method, Sorting and Ranking
- axes
- AxesSubplot object, Figures and Subplots, Ticks, Labels, and Legends
- axis method, Summarizing and Computing Descriptive Statistics
B
- %b datetime
format, Converting Between String and Datetime
- %B datetime
format, Converting Between String and Datetime
- b(reak) debugger command, Interactive Debugger
- backslash (\), Strings, Regular Expressions
- bang (!), Shell Commands and Aliases
- bar method, Bar Plots
- bar plots, Bar Plots-Bar Plots
- barh method, Bar Plots
- barplot function, Bar Plots
- base frequency, Frequencies and Date Offsets
- bcolz binary format, Binary Data Formats
- beta function, Pseudorandom Number Generation
- binary data formats
- binary moving window functions, Binary Moving Window Functions
- binary operators and comparisons in Python, Binary operators and comparisons, set
- binary searches of lists, Binary search and maintaining a sorted list
- binary universal functions, Universal Functions: Fast Element-Wise Array Functions, Universal Functions: Fast Element-Wise Array Functions
- binding, defined, Variables and argument passing, Concatenating Along an Axis
- binning continuous data, Discretization and Binning
- binomial function, Pseudorandom Number Generation
- bisect module, Binary search and maintaining a sorted list
- Bitly dataset example, 1.USA.gov Data from Bitly-Counting Time Zones with pandas
- Blosc compression library, Binary Data Formats
- Bokeh tool, Other Python Visualization Tools
- %bookmark magic
function, Interacting with the Operating System, Directory Bookmark System
- bookmarking directories in IPython, Directory Bookmark System
- bool data type, Scalar Types, Booleans, Data Types for ndarrays
- bool function, Type casting
- boolean arrays, Methods for Boolean Arrays
- boolean indexing, Boolean Indexing-Boolean Indexing
- braces {}, dict, set
- break keyword, for loops
- broadcasting, ndarrays and, Arithmetic with NumPy Arrays, Repeating Elements: tile and repeat, Broadcasting-Setting Array Values by Broadcasting
- bucket analysis, Quantile and Bucket Analysis
- build_design_matrices function, Data Transformations in Patsy Formulas
- builtins module, Data Transformations in Patsy Formulas
- bytes data type, Scalar Types, Bytes and Unicode
C
- %C datetime
format, Converting Between String and Datetime
- C order (row major order), C Versus Fortran Order, The Importance of Contiguous Memory
- c(ontinue) debugger command, Interactive Debugger
- calendar module, Date and Time Data Types and Tools
- Cartesian product, itertools module, Database-Style DataFrame Joins
- casefold method, String Object Methods
- cat method, Vectorized String Functions in pandas
- categorical data
- Categorical object, Discretization and Binning, Quantile and Bucket Analysis, Categorical Data-Creating dummy variables for modeling
- %cd magic
function, Interacting with the Operating System, Directory Bookmark System
- ceil function, Universal Functions: Fast Element-Wise Array Functions
- center method, Vectorized String Functions in pandas
- chaining methods, Techniques for Method Chaining-The pipe Method
- chisquare function, Pseudorandom Number Generation
- clear method, set
- clipboard, executing code from, Executing Code from the Clipboard
- close method, Files and the Operating System, Files and the Operating System
- closed attribute, Files and the Operating System
- !cmd command, Interacting with the Operating System
- collections module, Default values
- colon (:), Indentation, not braces
- color selection in matplotlib, Colors, Markers, and Line Styles
- column major order (Fortran order), C Versus Fortran Order, The Importance of Contiguous Memory
- columns method, Pivot Tables and Cross-Tabulation
- column_stack function, Concatenating and Splitting Arrays
- combinations function, itertools module
- combine_first method, Combining and Merging Datasets, Combining Data with Overlap
- combining data (see merging data)
- command history
- commands
- comments in Python, Comments
- compile method, Regular Expressions
- complex128 data type, Data Types for ndarrays
- complex256 data type, Data Types for ndarrays
- complex64 data type, Data Types for ndarrays
- concat function, Combining and Merging Datasets, Merging on Index, Concatenating Along an Axis-Concatenating Along an Axis, Column-Wise and Multiple Function Application
- concatenate function, Concatenating Along an Axis, Concatenating and Splitting Arrays
- concatenating
- conda update command, Installing or Updating Python Packages
- conditional logic as array operations, Expressing Conditional Logic as Array Operations
- configuration for IPython, Profiles and Configuration-Profiles and Configuration
- configuring matplotlib, matplotlib Configuration
- contains method, Vectorized String Functions in pandas
- contiguous memory, The Importance of Contiguous Memory-The Importance of Contiguous Memory
- continue keyword, for loops
- continuing education, Continuing Your Education
- control flow in Python, Control Flow-Ternary expressions
- coordinated universal time (UTC), Time Zone Handling
- copy method, Basic Indexing and Slicing, DataFrame
- copysign function, Universal Functions: Fast Element-Wise Array Functions
- corr aggregation function, Binary Moving Window Functions
- corr method, Correlation and Covariance
- correlation, Correlation and Covariance-Correlation and Covariance, Example: Group Weighted Average and Correlation
- corrwith method, Correlation and Covariance
- cos function, Universal Functions: Fast Element-Wise Array Functions
- cosh function, Universal Functions: Fast Element-Wise Array Functions
- count method, Strings, Tuple methods, Summarizing and Computing Descriptive Statistics, String Object Methods-String Object Methods, Vectorized String Functions in pandas, Data Aggregation
- cov method, Correlation and Covariance
- covariance, Correlation and Covariance-Correlation and Covariance
- %cpaste magic
function, Executing Code from the Clipboard, About Magic Commands
- cProfile module, Basic Profiling: %prun and %run -p-Basic Profiling: %prun and %run -p
- cross-tabulation, Cross-Tabulations: Crosstab
- crosstab function, Cross-Tabulations: Crosstab
- cross_val_score function, Introduction to scikit-learn
- CSV files, Reading and Writing Data in Text Format, Writing Data to Text Format-Working with Delimited Formats
- csv module, Working with Delimited Formats
- Ctrl-A keyboard shortcut, Terminal Keyboard Shortcuts
- Ctrl-B keyboard shortcut, Terminal Keyboard Shortcuts
- Ctrl-C keyboard shortcut, Interrupting running code, Terminal Keyboard Shortcuts
- Ctrl-D keyboard shortcut, The Python Interpreter
- Ctrl-E keyboard shortcut, Terminal Keyboard Shortcuts
- Ctrl-F keyboard shortcut, Terminal Keyboard Shortcuts
- Ctrl-K keyboard shortcut, Terminal Keyboard Shortcuts
- Ctrl-L keyboard shortcut, Terminal Keyboard Shortcuts
- Ctrl-N keyboard shortcut, Terminal Keyboard Shortcuts, Searching and Reusing the Command History
- Ctrl-P keyboard shortcut, Terminal Keyboard Shortcuts, Searching and Reusing the Command History
- Ctrl-R keyboard shortcut, Terminal Keyboard Shortcuts, Searching and Reusing the Command History
- Ctrl-Shift-V keyboard shortcut, Terminal Keyboard Shortcuts
- Ctrl-U keyboard shortcut, Terminal Keyboard Shortcuts
- cummax method, Summarizing and Computing Descriptive Statistics
- cummin method, Summarizing and Computing Descriptive Statistics
- cumprod method, Mathematical and Statistical Methods, Summarizing and Computing Descriptive Statistics
- cumsum method, Mathematical and Statistical Methods, Summarizing and Computing Descriptive Statistics, ufunc Instance Methods
- curly braces {}, dict, set
- currying, Currying: Partial Argument Application
- cut function, Discretization and Binning, Quantile and Bucket Analysis
- c_ object, Stacking helpers: r_ and c_
D
- %d datetime
format, Dates and times, Converting Between String and Datetime
- %D datetime
format, Dates and times, Converting Between String and Datetime
- d(own) debugger command, Interactive Debugger
- data aggregation
- data alignment, pandas library and, Arithmetic and Data Alignment-Operations between DataFrame and Series
- data analysis with Python
- about, Why Python for Data Analysis?, Python Language Basics, IPython, and Jupyter Notebooks-Python Language Basics, IPython, and Jupyter Notebooks
- glue code, Python as Glue
- MovieLens 1M dataset example, MovieLens 1M Dataset-Measuring Rating Disagreement
- restrictions to consider, Why Not Python?
- US baby names dataset example, US Baby Names 1880–2010-Boy names that became girl names (and vice versa)
- US Federal Election Commission database example, 2012 Federal Election Commission Database-Donation Statistics by State
- USA.gov data from Bitly example, 1.USA.gov Data from Bitly-Counting Time Zones with pandas
- USDA food database example, USDA Food Database-USDA Food Database
- “two-language”
problem, Solving the “Two-Language” Problem
- data cleaning and preparation (see data wrangling)
- data loading (see reading data)
- data manipulation (see data wrangling)
- data munging (see data wrangling)
- data selection
- data structures
- about, Data Structures and Sequences
- dict comprehensions, List, Set, and Dict Comprehensions
- dicts, dict-Valid dict key types
- for pandas library, Introduction to pandas Data Structures-Index Objects
- list comprehensions, List, Set, and Dict Comprehensions-Nested list comprehensions
- lists, List-Slicing
- set comprehensions, List, Set, and Dict Comprehensions
- sets, set-set
- tuples, Tuple-Tuple methods
- data transformation (see transforming data)
- data types
- data wrangling
- combining and merging datasets, Combining and Merging Datasets-Combining Data with Overlap
- defined, Jargon
- handling missing data, Handling Missing Data-Filling In Missing Data
- hierarchical indexing, Hierarchical Indexing-Indexing with a DataFrame’s columns, Reshaping with Hierarchical Indexing
- pivoting data, Pivoting “Long” to “Wide” Format-Pivoting “Wide” to “Long” Format
- reshaping data, Reshaping with Hierarchical Indexing
- string manipulation, String Manipulation-Vectorized String Functions in pandas
- transforming data, Data Transformation-Computing Indicator/Dummy Variables
- working with delimited formats, Working with Delimited Formats-Working with Delimited Formats
- databases
- DataFrame data structure
- about, pandas, DataFrame-DataFrame, Nested dtypes and Multidimensional Fields
- database-stye joins, Database-Style DataFrame Joins-Database-Style DataFrame Joins
- indexing with columns, Indexing with a DataFrame’s columns
- JSON data and, JSON Data
- operations between Series and, Operations between DataFrame and Series
- optional function arguments, Reading and Writing Data in Text Format
- plot method arguments, Line Plots
- possible data inputs to, DataFrame
- ranking data in, Sorting and Ranking
- sorting considerations, Sorting and Ranking, Indirect Sorts: argsort and lexsort
- summary statistics methods for, Correlation and Covariance
- DataOffset object, Operations with Time Zone−Aware Timestamp Objects
- datasets
- date data type, Dates and times, Date and Time Data Types and Tools
- date offsets, Frequencies and Date Offsets, Shifting dates with offsets-Shifting dates with offsets
- date ranges, generating, Generating Date Ranges-Generating Date Ranges
- dates and times
- datetime data type
- datetime module, Dates and times, Date and Time Data Types and Tools
- datetime64 data type, Time Series Basics
- DatetimeIndex class, Time Series Basics, Generating Date Ranges, Time Zone Localization and Conversion
- dateutil package, Converting Between String and Datetime
- date_range function, Generating Date Ranges-Generating Date Ranges
- daylight saving time (DST), Time Zone Handling
- debug function, Other ways to make use of the debugger
- %debug magic
function, Exceptions in IPython, Interactive Debugger
- debugger, IPython, Interactive Debugger-Other ways to make use of the debugger
- decode method, Bytes and Unicode
- def keyword, Functions, Anonymous (Lambda) Functions
- default values for dicts, Default values
- defaultdict class, Default values
- del keyword, dict, DataFrame
- del method, DataFrame
- delete method, Index Objects
- delimited formats, working with, Working with Delimited Formats-Working with Delimited Formats
- dense method, Sorting and Ranking
- density plots, Histograms and Density Plots-Histograms and Density Plots
- deque (double-ended queue), Adding and removing elements
- describe method, Summarizing and Computing Descriptive Statistics, Data Aggregation
- design matrix, Creating Model Descriptions with Patsy
- det function, Linear Algebra
- development tools for IPython (see software development tools for IPython)
- %dhist magic
function, Interacting with the Operating System
- diag function, Linear Algebra
- Dialect class, Working with Delimited Formats
- dict comprehensions, List, Set, and Dict Comprehensions
- dict function, Creating dicts from sequences
- dictionary-encoded representation, Background and Motivation
- dicts (data structures)
- diff method, Summarizing and Computing Descriptive Statistics
- difference method, set, Index Objects
- difference_update method, set
- dimension tables, Background and Motivation
- directories, bookmarking in IPython, Directory Bookmark System
- %dirs magic
function, Interacting with the Operating System
- discretization, Discretization and Binning
- distplot method, Histograms and Density Plots
- div method, Arithmetic methods with fill values
- divide function, Universal Functions: Fast Element-Wise Array Functions
- divmod function, Universal Functions: Fast Element-Wise Array Functions
- dmatrices function, Creating Model Descriptions with Patsy
- dnorm function, Estimating Linear Models
- dot function, Transposing Arrays and Swapping Axes, Linear Algebra-Linear Algebra
- downsampling, Resampling and Frequency Conversion, Downsampling-Open-High-Low-Close (OHLC) resampling
- dreload function, Reloading Module Dependencies
- drop method, Index Objects, Dropping Entries from an Axis
- dropna method, Handling Missing Data-Filtering Out Missing Data, Example: Filling Missing Values with Group-Specific
Values, Pivot Tables and Cross-Tabulation
- drop_duplicates method, Removing Duplicates
- DST (daylight saving time), Time Zone Handling
- dstack function, Concatenating and Splitting Arrays
- dtype (see data types)
- dtype attribute, The NumPy ndarray: A Multidimensional Array Object, Data Types for ndarrays
- duck typing, Duck typing
- dummy variables, Computing Indicator/Dummy Variables-Computing Indicator/Dummy Variables, Creating dummy variables for modeling, Interfacing Between pandas and Model Code, Categorical Data and Patsy
- dumps function, JSON Data
- duplicate data
- duplicated method, Removing Duplicates
- dynamic references in Python, Dynamic references, strong types
E
- edit-compile-run workflow, IPython and Jupyter
- education, continuing, Continuing Your Education
- eig function, Linear Algebra
- elif statement, if, elif, and else
- else statement, if, elif, and else
- empty function, Creating ndarrays-Creating ndarrays
- empty namespace, The %run Command
- empty_like function, Creating ndarrays
- encode method, Bytes and Unicode
- end-of-line (EOL) markers, Files and the Operating System
- endswith method, String Object Methods, Vectorized String Functions in pandas
- enumerate function, enumerate
- %env magic
function, Interacting with the Operating System
- EOL (end-of-line) markers, Files and the Operating System
- equal function, Universal Functions: Fast Element-Wise Array Functions
- error handling in Python, Errors and Exception Handling-Exceptions in IPython
- escape characters, Strings
- ewm function, Exponentially Weighted Functions
- Excel files (Microsoft), Reading Microsoft Excel Files-Reading Microsoft Excel Files
- ExcelFile class, Reading Microsoft Excel Files
- exception handling in Python, Errors and Exception Handling-Exceptions in IPython
- exclamation point (!), Shell Commands and Aliases
- execute-explore workflow, IPython and Jupyter
- exit command, The Python Interpreter
- exp function, Universal Functions: Fast Element-Wise Array Functions
- expanding function, Moving Window Functions
- exponentially-weighted functions, Exponentially Weighted Functions
- extend method, Concatenating and combining lists
- extract method, Vectorized String Functions in pandas
- eye function, Creating ndarrays
F
- %F datetime
format, Dates and times, Converting Between String and Datetime
- fabs function, Universal Functions: Fast Element-Wise Array Functions
- facet grids, Facet Grids and Categorical Data
- FacetGrid class, Facet Grids and Categorical Data
- factorplot built-in function, Facet Grids and Categorical Data
- fancy indexing, Fancy Indexing, Fancy Indexing Equivalents: take and put
- FDIC bank failures list, XML and HTML: Web Scraping
- Feather binary file format, Reading and Writing Data in Text Format, Binary Data Formats
- feature engineering, Interfacing Between pandas and Model Code
- Federal Election Commission database example, 2012 Federal Election Commission Database-Donation Statistics by State
- Figure object, Figures and Subplots
- file management
- binary data formats, Binary Data Formats-Reading Microsoft Excel Files
- commonly used file methods, Files and the Operating System
- design tips, Overcome a fear of longer files
- file input and output with arrays, File Input and Output with Arrays
- JSON data, JSON Data-JSON Data
- memory-mapped files, Memory-Mapped Files
- opening files, Files and the Operating System
- Python file modes, Files and the Operating System
- reading and writing data in text format, Reading and Writing Data in Text Format-Writing Data to Text Format
- saving plots to files, Saving Plots to File
- Web scraping, XML and HTML: Web Scraping-Parsing XML with lxml.objectify
- working with delimited formats, Working with Delimited Formats-Working with Delimited Formats
- filling in data
- fillna method, Handling Missing Data, Filling In Missing Data-Filling In Missing Data, Replacing Values, Example: Filling Missing Values with Group-Specific
Values, Upsampling and Interpolation
- fill_value method, Pivot Tables and Cross-Tabulation
- filtering
- find method, String Object Methods-String Object Methods
- findall method, Regular Expressions, Regular Expressions, Vectorized String Functions in pandas
- finditer method, Regular Expressions
- first method, Sorting and Ranking, Data Aggregation
- fit method, Estimating Linear Models, Introduction to scikit-learn
- fixed frequency, Time Series
- flags attribute, The Importance of Contiguous Memory
- flatten method, Reshaping Arrays
- float data type, Scalar Types, Type casting
- float function, Type casting
- float128 data type, Data Types for ndarrays
- float16 data type, Data Types for ndarrays
- float32 data type, Data Types for ndarrays
- float64 data type, Data Types for ndarrays
- floor function, Universal Functions: Fast Element-Wise Array Functions
- floordiv method, Arithmetic methods with fill values
- floor_divide function, Universal Functions: Fast Element-Wise Array Functions
- flow control in Python, Control Flow-Ternary expressions
- flush method, Files and the Operating System, Memory-Mapped Files
- fmax function, Universal Functions: Fast Element-Wise Array Functions
- fmin function, Universal Functions: Fast Element-Wise Array Functions
- for loops, for loops, Nested list comprehensions
- format method, Strings
- formatting
- Fortran order (column major order), C Versus Fortran Order, The Importance of Contiguous Memory
- frequencies
- base, Frequencies and Date Offsets
- basic for time series, Generating Date Ranges
- converting between, Date Ranges, Frequencies, and Shifting, Resampling and Frequency Conversion-Resampling with Periods
- date offsets and, Frequencies and Date Offsets
- fixed, Time Series
- period conversion, Period Frequency Conversion
- quarterly period frequencies, Quarterly Period Frequencies
- fromfile function, Why Use Structured Arrays?
- frompyfunc function, Writing New ufuncs in Python
- from_codes method, Categorical Type in pandas
- full function, Creating ndarrays
- full_like function, Creating ndarrays
- functions, Functions
- (see also universal functions)
- about, Functions
- accessing variables, Namespaces, Scope, and Local Functions
- anonymous, Anonymous (Lambda) Functions
- as objects, Functions Are Objects-Functions Are Objects
- currying, Currying: Partial Argument Application
- errors and exception handling, Errors and Exception Handling
- exponentially-weighted, Exponentially Weighted Functions
- generators and, Generators-Exceptions in IPython
- grouping with, Grouping with Functions
- in Python, Function and object method calls
- lambda, Anonymous (Lambda) Functions
- magic, About Magic Commands-About Magic Commands
- namespaces and, Namespaces, Scope, and Local Functions
- object introspection, Introspection
- partial argument application, Currying: Partial Argument Application
- profiling line by line, Profiling a Function Line by Line-Profiling a Function Line by Line
- returning multiple values, Returning Multiple Values
- sequence, Built-in Sequence Functions-reversed
- transforming data using, Transforming Data Using a Function or Mapping
- type inference in, Reading and Writing Data in Text Format
- writing fast NumPy functions with Numba, Writing Fast NumPy Functions with Numba-Creating Custom numpy.ufunc Objects with Numba
- functools module, Currying: Partial Argument Application
G
- gamma function, Pseudorandom Number Generation
- generators
- get method, Default values, Vectorized String Functions in pandas
- GET request (HTTP), Interacting with Web APIs
- getattr function, Attributes and methods
- getroot method, Parsing XML with lxml.objectify
- get_chunk method, Reading Text Files in Pieces
- get_dummies function, Computing Indicator/Dummy Variables, Creating dummy variables for modeling, Interfacing Between pandas and Model Code
- get_indexer method, Unique Values, Value Counts, and Membership
- get_value method, Selection with loc and iloc
- GIL (global interpreter lock), Why Not Python?
- global keyword, Namespaces, Scope, and Local Functions
- glue for code, Python as, Python as Glue
- greater function, Universal Functions: Fast Element-Wise Array Functions
- greater_equal function, Universal Functions: Fast Element-Wise Array Functions
- Greenwich Mean Time, Time Zone Handling
- group keys, suppressing, Suppressing the Group Keys
- group operations
- about, Data Aggregation and Group
Operations, Advanced GroupBy Use
- cross-tabulation, Cross-Tabulations: Crosstab
- data aggregation, Data Aggregation-Returning Aggregated Data Without Row Indexes
- GroupBy mechanics, GroupBy Mechanics-Grouping by Index Levels
- pivot tables, Data Aggregation and Group
Operations, Pivot Tables and Cross-Tabulation-Cross-Tabulations: Crosstab
- split-apply-combine, GroupBy Mechanics, Apply: General split-apply-combine-Example: Group-Wise Linear Regression
- unwrapped, Group Transforms and “Unwrapped” GroupBys
- group weighted average, Example: Group Weighted Average and Correlation
- groupby function, itertools module
- groupby method, Computations with Categoricals, numpy.searchsorted: Finding Elements in a Sorted Array
- GroupBy object
- groups method, Regular Expressions
H
- %H datetime
format, Dates and times, Converting Between String and Datetime
- h(elp) debugger command, Interactive Debugger
- hasattr function, Attributes and methods
- hash function, Valid dict key types
- hash maps (see dicts)
- hash mark (#), Comments
- hashability, Valid dict key types
- HDF5 (hierarchical data format 5), Using HDF5 Format-Using HDF5 Format, HDF5 and Other Array Storage Options
- HDFStore class, Using HDF5 Format
- head method, DataFrame
- heapsort method, Alternative Sort Algorithms
- hierarchical data format (HDF5), HDF5 and Other Array Storage Options
- hierarchical indexing
- %hist magic
function, About Magic Commands
- hist method, Histograms and Density Plots
- histograms, Histograms and Density Plots-Histograms and Density Plots
- hsplit function, Concatenating and Splitting Arrays
- hstack function, Concatenating and Splitting Arrays
- HTML files, XML and HTML: Web Scraping-Parsing XML with lxml.objectify
- HTTP requests, Interacting with Web APIs
- Hugunin, Jim, NumPy Basics: Arrays and Vectorized
Computation
- Hunter, John D., matplotlib, Plotting and Visualization
I
- %I datetime
format, Dates and times, Converting Between String and Datetime
- identity function, Creating ndarrays
- IDEs (Integrated Development Environments), Integrated Development Environments (IDEs) and Text
Editors
- idxmax method, Summarizing and Computing Descriptive Statistics
- idxmin method, Summarizing and Computing Descriptive Statistics
- if statement, if, elif, and else
- iloc operator, Selection with loc and iloc, Permutation and Random Sampling
- immutable objects, Mutable and immutable objects, Categorical Type in pandas
- import conventions
- importlib module, Reloading Module Dependencies
- imshow function, Array-Oriented Programming with Arrays
- in keyword, Adding and removing elements, String Object Methods
- in-place sorts, Sorting, More About Sorting
- in1d method, Unique and Other Set Logic, Unique and Other Set Logic
- indentation in Python, Indentation, not braces
- index method, String Object Methods-String Object Methods, Pivot Tables and Cross-Tabulation
- Index objects, Index Objects-Index Objects
- indexes and indexing
- axis indexes with duplicate labels, Axis Indexes with Duplicate Labels
- boolean indexing, Boolean Indexing-Boolean Indexing
- fancy indexing, Fancy Indexing, Fancy Indexing Equivalents: take and put
- for ndarrays, Basic Indexing and Slicing-Indexing with slices
- for pandas library, Indexing, Selection, and Filtering-Selection with loc and iloc, Axis Indexes with Duplicate Labels
- grouping by index level, Grouping by Index Levels
- hierarchical indexing, Reading and Writing Data in Text Format, Hierarchical Indexing-Indexing with a DataFrame’s columns, Reshaping with Hierarchical Indexing
- Index objects, Index Objects-Index Objects
- integer indexing, Integer Indexes
- merging on index, Merging on Index-Merging on Index
- renaming axis indexes, Renaming Axis Indexes
- time series data, Indexing, Selection, Subsetting
- time series with duplicate indexes, Time Series with Duplicate Indices
- timedeltas and, Time Series
- indexing operator, Slicing
- indicator variables, Computing Indicator/Dummy Variables-Computing Indicator/Dummy Variables
- indirect sorts, Indirect Sorts: argsort and lexsort
- inner join type, Database-Style DataFrame Joins
- input variables, Input and Output Variables
- insert method, Adding and removing elements, Index Objects
- insort function, Binary search and maintaining a sorted list
- int data type, Scalar Types, Type casting
- int function, Type casting
- int16 data type, Data Types for ndarrays
- int32 data type, Data Types for ndarrays
- int64 data type, Data Types for ndarrays
- int8 data type, Data Types for ndarrays
- integer arrays, indexing, Fancy Indexing, Fancy Indexing Equivalents: take and put
- integer indexing, Integer Indexes
- Integrated Development Environments (IDEs), Integrated Development Environments (IDEs) and Text
Editors
- interactive debugger, Interactive Debugger-Other ways to make use of the debugger
- interpreted languages, Why Python for Data Analysis?, The Python Interpreter
- interrupting running code, Interrupting running code
- intersect1d method, Unique and Other Set Logic
- intersection method, set-set, Index Objects
- intersection_update method, set
- intervals of time, Time Series
- inv function, Linear Algebra
- .ipynb file
extension, Running the Jupyter Notebook
- IPython
- %run command and, The Python Interpreter
- %run command in, The %run Command-Interrupting running code
- about, IPython and Jupyter
- advanced features, Advanced IPython Features-Profiles and Configuration
- bookmarking directories, Directory Bookmark System
- code development tips, Tips for Productive Code Development Using IPython-Overcome a fear of longer files
- command history in, Using the Command History-Input and Output Variables
- exception handling in, Exceptions in IPython
- executing code from clipboard, Executing Code from the Clipboard
- figures and subplots, Figures and Subplots
- interacting with operating system, Interacting with the Operating System-Directory Bookmark System
- keyboard shortcuts for, Terminal Keyboard Shortcuts
- magic commands in, About Magic Commands-About Magic Commands
- matplotlib integration, Matplotlib Integration
- object introspection, Introspection-Introspection
- running Jupyter notebook, Running the Jupyter Notebook-Running the Jupyter Notebook
- running shell, Running the IPython Shell-Running the IPython Shell
- shell commands in, Shell Commands and Aliases
- software development tools, Software Development Tools-Profiling a Function Line by Line
- tab completion in, Tab Completion-Tab Completion
- ipython command, Running the IPython Shell-Running the IPython Shell
- is keyword, Binary operators and comparisons
- is not keyword, Binary operators and comparisons
- isalnum method, Vectorized String Functions in pandas
- isalpha method, Vectorized String Functions in pandas
- isdecimal method, Vectorized String Functions in pandas
- isdigit method, Vectorized String Functions in pandas
- isdisjoint method, set
- isfinite function, Universal Functions: Fast Element-Wise Array Functions
- isin method, Index Objects, Unique Values, Value Counts, and Membership
- isinf function, Universal Functions: Fast Element-Wise Array Functions
- isinstance function, Dynamic references, strong types
- islower method, Vectorized String Functions in pandas
- isnan function, Universal Functions: Fast Element-Wise Array Functions
- isnull method, Series, Handling Missing Data
- isnumeric method, Vectorized String Functions in pandas
- issubdtype function, NumPy dtype Hierarchy
- issubset method, set
- issuperset method, set
- isupper method, Vectorized String Functions in pandas
- is_monotonic property, Index Objects
- is_unique property, Index Objects, Axis Indexes with Duplicate Labels, Time Series with Duplicate Indices
- iter function, Duck typing
- __iter__ magic
method, Duck typing
- iterator protocol, Duck typing, Generators-itertools module
- itertools module, itertools module
K
- KDE (kernel density estimate) plots, Histograms and Density Plots
- kernels, defined, IPython and Jupyter, Running the Jupyter Notebook
- key-value pairs, dict
- keyboard shortcuts for IPython, Terminal Keyboard Shortcuts
- KeyboardInterrupt exception, Interrupting running code
- KeyError exception, set
- keys method, dict
- keyword arguments, Function and object method calls, Functions
- kurt method, Summarizing and Computing Descriptive Statistics
L
- l(ist) debugger command, Interactive Debugger
- labels
- lagging data, Shifting (Leading and Lagging) Data
- lambda (anonymous) functions, Anonymous (Lambda) Functions
- language semantics for Python
- about, Language Semantics
- attributes, Attributes and methods
- binary operators and comparisons, Binary operators and comparisons, set
- comments, Comments
- duck typing, Duck typing
- function and object method calls, Function and object method calls
- import conventions, Imports
- indentation not braces, Indentation, not braces
- methods, Attributes and methods
- mutable and immutable objects, Mutable and immutable objects
- object model, Everything is an object
- references, Variables and argument passing-Dynamic references, strong types
- strongly typed language, Dynamic references, strong types
- variables and argument passing, Variables and argument passing
- last method, Data Aggregation
- leading data, Shifting (Leading and Lagging) Data
- left join type, Database-Style DataFrame Joins
- legend method, Adding legends
- legend selection in matplotlib, Colors, Markers, and Line Styles-Adding legends
- len function, Grouping with Functions
- len method, Vectorized String Functions in pandas
- less function, Universal Functions: Fast Element-Wise Array Functions
- less_equal function, Universal Functions: Fast Element-Wise Array Functions
- level keyword, Grouping by Index Levels
- level method, Summarizing and Computing Descriptive Statistics
- levels
- lexsort method, Indirect Sorts: argsort and lexsort
- libraries (see specific libraries)
- line plots, Line Plots-Line Plots
- line style selection in matplotlib, Colors, Markers, and Line Styles
- linear algebra, Linear Algebra-Linear Algebra
- linear regression, Example: Group-Wise Linear Regression, Estimating Linear Models-Estimating Linear Models
- Linux, setting up Python on, GNU/Linux
- list comprehensions, List, Set, and Dict Comprehensions-Nested list comprehensions
- list function, Binary operators and comparisons, List
- lists (data structures)
- lists (data structures)binary searches, Binary search and maintaining a sorted list
- ljust method, String Object Methods
- load function, File Input and Output with Arrays, Advanced Array Input and Output
- %load magic function, The %run Command
- loads function, JSON Data
- loc operator, DataFrame, Selection with loc and iloc, Adding legends, Interfacing Between pandas and Model Code
- local namespace, Namespaces, Scope, and Local Functions, Getting Started with pandas
- localizing data to time zones, Time Zone Localization and Conversion
- log function, Universal Functions: Fast Element-Wise Array Functions
- log10 function, Universal Functions: Fast Element-Wise Array Functions
- log1p function, Universal Functions: Fast Element-Wise Array Functions
- log2 function, Universal Functions: Fast Element-Wise Array Functions
- logical_and function, Universal Functions: Fast Element-Wise Array Functions, ufunc Instance Methods
- logical_not function, Universal Functions: Fast Element-Wise Array Functions
- logical_or function, Universal Functions: Fast Element-Wise Array Functions
- logical_xor function, Universal Functions: Fast Element-Wise Array Functions
- LogisticRegression class, Introduction to scikit-learn
- LogisticRegressionCV class, Introduction to scikit-learn
- long format, Pivoting “Long” to “Wide” Format
- lower method, Transforming Data Using a Function or Mapping, String Object Methods, Vectorized String Functions in pandas
- %lprun magic
function, Profiling a Function Line by Line
- lstrip method, String Object Methods, Vectorized String Functions in pandas
- lstsq function, Linear Algebra
- lxml library, XML and HTML: Web Scraping-Parsing XML with lxml.objectify
M
- %m datetime
format, Dates and times, Converting Between String and Datetime
- %M datetime
format, Dates and times, Converting Between String and Datetime
- mad method, Summarizing and Computing Descriptive Statistics
- magic functions, About Magic Commands-About Magic Commands
- (see also specific magic functions)
- %debug magic
function, About Magic Commands
- %magic magic
function, About Magic Commands
- many-to-many merge, Database-Style DataFrame Joins
- many-to-one join, Database-Style DataFrame Joins
- map built-in function, List, Set, and Dict Comprehensions, Functions Are Objects
- map method, Function Application and Mapping, Transforming Data Using a Function or Mapping, Renaming Axis Indexes
- mapping
- margins method, Pivot Tables and Cross-Tabulation
- margins, defined, Pivot Tables and Cross-Tabulation
- marker selection in matplotlib, Colors, Markers, and Line Styles
- match method, Unique Values, Value Counts, and Membership, Regular Expressions, Regular Expressions, Vectorized String Functions in pandas
- Math Kernel Library (MKL), Linear Algebra
- matplotlib library
- about, matplotlib, Plotting and Visualization
- annotations in, Annotations and Drawing on a Subplot-Annotations and Drawing on a Subplot
- color selection in, Colors, Markers, and Line Styles
- configuring, matplotlib Configuration
- creating image plots, Array-Oriented Programming with Arrays
- figures in, Figures and Subplots-Adjusting the spacing around subplots
- import convention, A Brief matplotlib API Primer
- integration with IPython, Matplotlib Integration
- label selection in, Ticks, Labels, and Legends-Setting the title, axis labels, ticks, and ticklabels
- legend selection in, Colors, Markers, and Line Styles-Adding legends
- line style selection in, Colors, Markers, and Line Styles
- marker selection in, Colors, Markers, and Line Styles
- saving plots to files, Saving Plots to File
- subplots in, Figures and Subplots-Adjusting the spacing around subplots, Annotations and Drawing on a Subplot-Annotations and Drawing on a Subplot
- tick mark selection in, Ticks, Labels, and Legends-Setting the title, axis labels, ticks, and ticklabels
- %matplotlib magic
function, Matplotlib Integration, Interacting with the Operating System
- matrix operations in NumPy, Transposing Arrays and Swapping Axes, Linear Algebra
- max method, Mathematical and Statistical Methods, Sorting and Ranking, Summarizing and Computing Descriptive Statistics, Data Aggregation
- maximum function, Universal Functions: Fast Element-Wise Array Functions
- mean method, Mathematical and Statistical Methods, Summarizing and Computing Descriptive Statistics, GroupBy Mechanics, Data Aggregation
- median method, Summarizing and Computing Descriptive Statistics, Data Aggregation
- melt method, Pivoting “Wide” to “Long” Format
- memmap object, Memory-Mapped Files
- memory management
- memory-mapped files, Memory-Mapped Files
- merge function, Database-Style DataFrame Joins-Database-Style DataFrame Joins
- mergesort method, Alternative Sort Algorithms
- merging data
- meshgrid function, Array-Oriented Programming with Arrays
- methods
- categorical, Categorical Methods-Categorical Methods
- chaining, Techniques for Method Chaining-The pipe Method
- defined, Function and object method calls
- for boolean arrays, Methods for Boolean Arrays
- for strings, String Object Methods-String Object Methods
- for summary
statistics, Unique Values, Value Counts, and Membership-Unique Values, Value Counts, and Membership
- for tuples, Tuple methods
- hidden, Tab Completion
- in Python, Function and object method calls, Attributes and methods
- object introspection, Introspection
- optimized for GroupBy, Data Aggregation
- statistical, Mathematical and Statistical Methods-Mathematical and Statistical Methods
- ufunc instance methods, ufunc Instance Methods-ufunc Instance Methods
- vectorized string methods in pandas, Vectorized String Functions in pandas-Vectorized String Functions in pandas
- Microsoft Excel files, Reading Microsoft Excel Files-Reading Microsoft Excel Files
- min method, Mathematical and Statistical Methods, Sorting and Ranking, Summarizing and Computing Descriptive Statistics, Data Aggregation
- minimum function, Universal Functions: Fast Element-Wise Array Functions
- missing data
- mixture-of-normals estimate, Histograms and Density Plots
- MKL (Math Kernel Library), Linear Algebra
- mod function, Universal Functions: Fast Element-Wise Array Functions
- modf function, Universal Functions: Fast Element-Wise Array Functions-Universal Functions: Fast Element-Wise Array Functions
- modules
- MovieLens 1M dataset example, MovieLens 1M Dataset-Measuring Rating Disagreement
- moving window functions
- mro method, NumPy dtype Hierarchy
- MSFT attribute, Correlation and Covariance
- mul method, Arithmetic methods with fill values
- multiply function, Universal Functions: Fast Element-Wise Array Functions
- munging (see data wrangling)
- mutable objects, Mutable and immutable objects
N
- n(ext) debugger command, Interactive Debugger
- NA data type, Handling Missing Data
- name attribute, Series, DataFrame
- names attribute, Boolean Indexing, Structured and Record Arrays
- namespaces
- NaN (Not a Number), Universal Functions: Fast Element-Wise Array Functions, Series, Handling Missing Data
- NaT (Not a Time), Converting Between String and Datetime
- ndarray object
- about, NumPy Basics: Arrays and Vectorized
Computation, The NumPy ndarray: A Multidimensional Array Object-The NumPy ndarray: A Multidimensional Array Object
- advanced input and output, Advanced Array Input and Output-HDF5 and Other Array Storage Options
- arithmetic with, Arithmetic with NumPy Arrays
- array-oriented programming, Array-Oriented Programming with Arrays-Unique and Other Set Logic
- as structured arrays, Structured and Record Arrays-Why Use Structured Arrays?
- attributes for, Creating ndarrays, Reshaping Arrays, Broadcasting Over Other Axes, The Importance of Contiguous Memory
- boolean indexing, Boolean Indexing-Boolean Indexing
- broadcasting and, Arithmetic with NumPy Arrays, Repeating Elements: tile and repeat, Broadcasting-Setting Array Values by Broadcasting
- C versus Fortan order, C Versus Fortran Order
- C versus Fortran order, The Importance of Contiguous Memory
- concatenating arrays, Concatenating and Splitting Arrays
- creating, Creating ndarrays-Creating ndarrays
- creating PeriodIndex from arrays, Creating a PeriodIndex from Arrays
- data types for, Data Types for ndarrays-Data Types for ndarrays
- fancy indexing, Fancy Indexing, Fancy Indexing Equivalents: take and put
- file input and output, File Input and Output with Arrays
- finding elements in sorted arrays, numpy.searchsorted: Finding Elements in a Sorted Array
- indexes for, Basic Indexing and Slicing-Indexing with slices
- internals overview, ndarray Object Internals-NumPy dtype Hierarchy
- linear algebra and, Linear Algebra-Linear Algebra
- partially sorting arrays, Partially Sorting Arrays
- pseudorandom number generation, Pseudorandom Number Generation-Pseudorandom Number Generation
- random walks example, Example: Random Walks-Simulating Many Random Walks at Once
- repeating elements in, Repeating Elements: tile and repeat
- reshaping arrays, Transposing Arrays and Swapping Axes, Reshaping Arrays
- slicing arrays, Basic Indexing and Slicing-Indexing with slices
- sorting considerations, Sorting, More About Sorting
- splitting arrays, Concatenating and Splitting Arrays
- storage options, HDF5 and Other Array Storage Options
- swapping axes in, Transposing Arrays and Swapping Axes
- transposing arrays, Transposing Arrays and Swapping Axes
- ndim attribute, Creating ndarrays
- nested code, Flat is better than nested
- nested data types, Nested dtypes and Multidimensional Fields
- nested list comprehensions, Nested list comprehensions-Nested list comprehensions
- nested tuples, Unpacking tuples
- New York MTA (Metropolitan Transportation
Authority), Parsing XML with lxml.objectify
- newaxis attribute, Broadcasting Over Other Axes
- “no-op” statement, pass
- None data type, Scalar Types, None, Handling Missing Data
- normal function, Pseudorandom Number Generation
- not keyword, Adding and removing elements
- notfull method, Handling Missing Data
- notnull method, Series
- not_equal function, Universal Functions: Fast Element-Wise Array Functions
- .npy file extension, File Input and Output with Arrays
- .npz file extension, File Input and Output with Arrays
- null value, Scalar Types, None, JSON Data
- Numba
- numeric data types, Numeric types
- NumPy library
- about, NumPy, NumPy Basics: Arrays and Vectorized
Computation-NumPy Basics: Arrays and Vectorized
Computation
- advanced array input and output, Advanced Array Input and Output-HDF5 and Other Array Storage Options
- advanced array manipulation, Advanced Array Manipulation-Fancy Indexing Equivalents: take and put
- advanced ufunc usage, Advanced ufunc Usage-Writing New ufuncs in Python
- array-oriented programming, Array-Oriented Programming with Arrays-Unique and Other Set Logic
- arrays and broadcasting, Broadcasting-Setting Array Values by Broadcasting
- file input and output with arrays, File Input and Output with Arrays
- linear algebra and, Linear Algebra-Linear Algebra
- ndarray object internals, ndarray Object Internals-NumPy dtype Hierarchy
- ndarray object overview, The NumPy ndarray: A Multidimensional Array Object-Transposing Arrays and Swapping Axes
- performance tips, Performance Tips-The Importance of Contiguous Memory
- pseudorandom number generation, Pseudorandom Number Generation-Pseudorandom Number Generation
- random walks example, Example: Random Walks-Simulating Many Random Walks at Once
- sorting considerations, Sorting, More About Sorting-numpy.searchsorted: Finding Elements in a Sorted Array
- structured and record arrays, Structured and Record Arrays-Why Use Structured Arrays?
- ufunc overview, Universal Functions: Fast Element-Wise Array Functions-Universal Functions: Fast Element-Wise Array Functions
- writing fast functions with Numba, Writing Fast NumPy Functions with Numba-Creating Custom numpy.ufunc Objects with Numba
O
- object data type, Data Types for ndarrays
- object introspection, Introspection-Introspection
- object model, Everything is an object
- objectify function, Parsing XML with lxml.objectify-Parsing XML with lxml.objectify
- objects (see Python objects)
- OHLC (Open-High-Low-Close) resampling, Open-High-Low-Close (OHLC) resampling
- ohlc aggregate function, Open-High-Low-Close (OHLC) resampling
- Oliphant, Travis, NumPy Basics: Arrays and Vectorized
Computation
- OLS (ordinary least squares) regression, Example: Group-Wise Linear Regression, Creating Model Descriptions with Patsy
- OLS class, Estimating Linear Models
- Olson database, Time Zone Handling
- ones function, Creating ndarrays-Creating ndarrays
- ones_like function, Creating ndarrays
- open built-in function, Files and the Operating System, Bytes and Unicode with Files
- openpyxl package, Reading Microsoft Excel Files
- operating system, IPython interacting with, Interacting with the Operating System-Directory Bookmark System
- or keyword, Booleans, Boolean Indexing
- OS X, setting up Python on, Apple (OS X, macOS)
- outer join type, Database-Style DataFrame Joins
- outer method, ufunc Instance Methods
- outliers, detecting and filtering, Detecting and Filtering Outliers
- output variables, Input and Output Variables
P
- %p datetime
format, Converting Between String and Datetime
- packages, installing or updating, Installing or Updating Python Packages
- pad method, Vectorized String Functions in pandas
- %page magic
function, About Magic Commands
- pairplot function, Scatter or Point Plots
- pairs plot, Scatter or Point Plots
- pandas library, pandas
- (see also data wrangling)
- about, pandas, Getting Started with pandas
- arithmetic and data alignment, Arithmetic and Data Alignment-Operations between DataFrame and Series
- as time zone naive, Time Zone Localization and Conversion
- binary data formats, Binary Data Formats-Reading Microsoft Excel Files
- categorical data and, Categorical Data-Creating dummy variables for modeling
- data structures for, Introduction to pandas Data Structures-Index Objects
- drop method, Dropping Entries from an Axis
- filtering in, Indexing, Selection, and Filtering-Selection with loc and iloc
- function application and mapping, Function Application and Mapping
- group operations and, Advanced GroupBy Use-Grouped Time Resampling
- indexes in, Indexing, Selection, and Filtering-Selection with loc and iloc, Axis Indexes with Duplicate Labels
- integer indexing, Integer Indexes
- interacting with databases, Interacting with Databases
- interacting with Web APIs, Interacting with Web APIs
- interfacing with model code, Interfacing Between pandas and Model Code
- JSON data, JSON Data-JSON Data
- method chaining, Techniques for Method Chaining-The pipe Method
- nested data types and, Nested dtypes and Multidimensional Fields
- plotting with, Plotting with pandas and seaborn-Facet Grids and Categorical Data
- ranking data in, Sorting and Ranking-Sorting and Ranking
- reading and writing data in text format, Reading and Writing Data in Text Format-Writing Data to Text Format
- reductions in, Summarizing and Computing Descriptive Statistics-Unique Values, Value Counts, and Membership
- reindex method, Reindexing-Reindexing
- selecting data in, Indexing, Selection, and Filtering-Selection with loc and iloc
- sorting considerations, Sorting and Ranking-Sorting and Ranking, Indirect Sorts: argsort and lexsort, numpy.searchsorted: Finding Elements in a Sorted Array
- summary statistics in, Summarizing and Computing Descriptive Statistics-Unique Values, Value Counts, and Membership
- vectorized string methods in, Vectorized String Functions in pandas-Vectorized String Functions in pandas
- Web scraping, XML and HTML: Web Scraping-Parsing XML with lxml.objectify
- working with delimited formats, Working with Delimited Formats-Working with Delimited Formats
- pandas-datareader package, Correlation and Covariance
- parentheses (), Function and object method calls, Tuple
- parse method, Reading Microsoft Excel Files, Converting Between String and Datetime
- partial argument application, Currying: Partial Argument Application
- partial function, Currying: Partial Argument Application
- partition method, Partially Sorting Arrays
- pass statement, pass
- %paste magic
function, Executing Code from the Clipboard, About Magic Commands
- patches, defined, Annotations and Drawing on a Subplot
- Patsy library
- pct_change method, Summarizing and Computing Descriptive Statistics, Example: Group Weighted Average and Correlation
- %pdb magic
function, About Magic Commands, Exceptions in IPython, Interactive Debugger
- percent sign (%), About Magic Commands, Basic Profiling: %prun and %run -p
- percentileofscore function, User-Defined Moving Window Functions
- Pérez, Fernando, IPython and Jupyter
- period (.), Tab Completion
- Period class, Periods and Period Arithmetic
- PeriodIndex class, Periods and Period Arithmetic, Creating a PeriodIndex from Arrays
- periods of dates and times
- period_range function, Periods and Period Arithmetic, Quarterly Period Frequencies
- Perktold, Josef, statsmodels
- permutation function, Pseudorandom Number Generation, Permutation and Random Sampling
- permutations function, itertools module
- pickle module, Binary Data Formats
- pinv function, Linear Algebra
- pip tool, Installing or Updating Python Packages, XML and HTML: Web Scraping
- pipe method, The pipe Method
- pivot method, Pivoting “Long” to “Wide” Format
- pivot tables, Data Aggregation and Group
Operations, Pivot Tables and Cross-Tabulation-Cross-Tabulations: Crosstab
- pivoting data, Pivoting “Long” to “Wide” Format-Pivoting “Wide” to “Long” Format
- pivot_table method, Pivot Tables and Cross-Tabulation
- plot function, Colors, Markers, and Line Styles
- plot method, Line Plots-Line Plots
- Plotly tool, Other Python Visualization Tools
- plotting
- point plots, Scatter or Point Plots
- pop method, Adding and removing elements, dict-Default values, set
- %popd magic
function, Interacting with the Operating System
- positional arguments, Function and object method calls, Functions
- pound sign (#), Comments
- pow method, Arithmetic methods with fill values
- power function, Universal Functions: Fast Element-Wise Array Functions
- pprint module, Making Your Own Classes IPython-Friendly
- predict method, Introduction to scikit-learn
- preparation, data (see data wrangling)
- private attributes, Tab Completion
- private methods, Tab Completion
- prod method, Summarizing and Computing Descriptive Statistics, Data Aggregation
- product function, itertools module
- profiles for IPython, Profiles and Configuration-Profiles and Configuration
- profiling code in IPython, Basic Profiling: %prun and %run -p-Basic Profiling: %prun and %run -p
- profiling functions line by line, Profiling a Function Line by Line-Profiling a Function Line by Line
- %prun magic
function, About Magic Commands, Basic Profiling: %prun and %run -p-Profiling a Function Line by Line
- pseudocode, Jargon, Language Semantics
- pseudorandom number generation, Pseudorandom Number Generation-Pseudorandom Number Generation
- %pushd magic
function, Interacting with the Operating System
- put method, Fancy Indexing Equivalents: take and put
- %pwd magic
function, Interacting with the Operating System
- .py file extension, The Python Interpreter, Imports
- pyplot module, Ticks, Labels, and Legends
- Python
- community and conferences, Community and Conferences
- control flow, Control Flow-Ternary expressions
- data analysis with, Why Python for Data Analysis?-Why Not Python?, Python Language Basics, IPython, and Jupyter Notebooks-Python Language Basics, IPython, and Jupyter Notebooks
- essential libraries, Essential Python Libraries-statsmodels
- historical background, Python 2 and Python 3
- import conventions, Import Conventions, Imports, The NumPy ndarray: A Multidimensional Array Object
- installation and setup, Installation and Setup-Integrated Development Environments (IDEs) and Text
Editors
- interpreter for, The Python Interpreter
- language semantics, Language Semantics-Mutable and immutable objects
- scalar types, Scalar Types-Dates and times
- python command, The Python Interpreter
- Python objects
- pytz library, Time Zone Handling
Q
- q(uit) debugger command, Interactive Debugger
- qcut function, Discretization and Binning, Quantile and Bucket Analysis, Computations with Categoricals
- qr function, Linear Algebra
- quantile analysis, Quantile and Bucket Analysis
- quantile method, Summarizing and Computing Descriptive Statistics, Data Aggregation
- quarterly period frequencies, Quarterly Period Frequencies
- question mark (?), Introspection-Introspection
- %quickref magic
function, About Magic Commands
- quicksort method, Alternative Sort Algorithms
- quotation marks in strings, Strings
R
- r character prefacing quotes, Strings
- R language, pandas, statsmodels, Handling Missing Data
- radd method, Arithmetic methods with fill values
- rand function, Pseudorandom Number Generation
- randint function, Pseudorandom Number Generation
- randn function, Boolean Indexing, Pseudorandom Number Generation
- random module, Pseudorandom Number Generation-Simulating Many Random Walks at Once
- random number generation, Pseudorandom Number Generation-Pseudorandom Number Generation
- random sampling and permutation, Example: Random Sampling and Permutation
- random walks example, Example: Random Walks-Simulating Many Random Walks at Once
- RandomState class, Pseudorandom Number Generation
- range function, range, Creating ndarrays
- rank method, Sorting and Ranking
- ranking data in pandas library, Sorting and Ranking-Sorting and Ranking
- ravel method, Reshaping Arrays
- rc method, matplotlib Configuration
- rdiv method, Arithmetic methods with fill values
- re module, Functions Are Objects, Regular Expressions
- read method, Files and the Operating System-Files and the Operating System
- read-and-write mode for files, Files and the Operating System
- read-only mode for files, Files and the Operating System
- reading data
- readline functionality, Searching and Reusing the Command History
- readlines method, Files and the Operating System
- read_clipboard function, Reading and Writing Data in Text Format
- read_csv function, Files and the Operating System, Reading and Writing Data in Text Format, Reading and Writing Data in Text Format, Bar Plots, Column-Wise and Multiple Function Application
- read_excel function, Reading and Writing Data in Text Format, Reading Microsoft Excel Files
- read_feather function, Reading and Writing Data in Text Format
- read_fwf function, Reading and Writing Data in Text Format
- read_hdf function, Reading and Writing Data in Text Format, Using HDF5 Format
- read_html function, Reading and Writing Data in Text Format, XML and HTML: Web Scraping-Parsing XML with lxml.objectify
- read_json function, Reading and Writing Data in Text Format, JSON Data
- read_msgpack function, Reading and Writing Data in Text Format
- read_pickle function, Reading and Writing Data in Text Format, Binary Data Formats
- read_sas function, Reading and Writing Data in Text Format
- read_sql function, Reading and Writing Data in Text Format, Interacting with Databases
- read_stata function, Reading and Writing Data in Text Format
- read_table function, Reading and Writing Data in Text Format, Reading and Writing Data in Text Format, Working with Delimited Formats
- reduce method, ufunc Instance Methods
- reduceat method, ufunc Instance Methods
- reductions (aggregations), Mathematical and Statistical Methods
- references in Python, Variables and argument passing-Dynamic references, strong types
- regplot method, Scatter or Point Plots
- regress function, Example: Group-Wise Linear Regression
- regular expressions
- reindex method, Reindexing-Reindexing, Selection with loc and iloc, Axis Indexes with Duplicate Labels, Upsampling and Interpolation
- reload function, Reloading Module Dependencies
- remove method, Adding and removing elements, set
- remove_categories method, Categorical Methods
- remove_unused_categories method, Categorical Methods
- rename method, Renaming Axis Indexes
- rename_categories method, Categorical Methods
- reorder_categories method, Categorical Methods
- repeat function, Repeating Elements: tile and repeat
- repeat method, Vectorized String Functions in pandas
- replace method, Replacing Values, String Object Methods-String Object Methods, Vectorized String Functions in pandas
- requests package, Interacting with Web APIs
- resample method, Date Ranges, Frequencies, and Shifting, Resampling and Frequency Conversion-Open-High-Low-Close (OHLC) resampling, Grouped Time Resampling
- resampling
- %reset magic
function, About Magic Commands, Input and Output Variables
- reset_index method, Pivoting “Wide” to “Long” Format, Returning Aggregated Data Without Row Indexes
- reshape method, Fancy Indexing, Reshaping Arrays
- *rest syntax, Unpacking tuples
- return statement, Functions
- reusing command history, Searching and Reusing the Command History
- reversed function, reversed
- rfind method, String Object Methods
- rfloordiv method, Arithmetic methods with fill values
- right join type, Database-Style DataFrame Joins
- rint function, Universal Functions: Fast Element-Wise Array Functions
- rjust method, String Object Methods
- rmul method, Arithmetic methods with fill values
- rollback method, Shifting dates with offsets
- rollforward method, Shifting dates with offsets
- rolling function, Moving Window Functions, Moving Window Functions
- rolling_corr function, Binary Moving Window Functions
- row major order (C order), C Versus Fortran Order, The Importance of Contiguous Memory
- row_stack function, Concatenating and Splitting Arrays
- rpow method, Arithmetic methods with fill values
- rstrip method, String Object Methods, Vectorized String Functions in pandas
- rsub method, Arithmetic methods with fill values
- %run magic function
- r_ object, Stacking helpers: r_ and c_
S
- %S datetime
format, Dates and times, Converting Between String and Datetime
- s(tep) debugger command, Interactive Debugger
- sample method, Permutation and Random Sampling, Example: Random Sampling and Permutation
- save function, File Input and Output with Arrays, Advanced Array Input and Output
- savefig method, Saving Plots to File
- savez function, File Input and Output with Arrays
- savez_compressed function, File Input and Output with Arrays
- scalar types in Python, Scalar Types-Dates and times, Arithmetic with NumPy Arrays
- scatter plot matrix, Scatter or Point Plots
- scatter plots, Scatter or Point Plots
- scikit-learn library, scikit-learn, Introduction to scikit-learn-Introduction to scikit-learn
- SciPy library, SciPy
- scope of functions, Namespaces, Scope, and Local Functions
- scripting languages, Why Python for Data Analysis?
- Seabold, Skipper, statsmodels
- seaborn library, Plotting with pandas and seaborn
- search method, Regular Expressions, Regular Expressions
- searching
- searchsorted method, numpy.searchsorted: Finding Elements in a Sorted Array
- seed function, Pseudorandom Number Generation
- seek method, Files and the Operating System, Files and the Operating System-Bytes and Unicode with Files
- semantics, language (see language semantics for Python)
- semicolon (;), Indentation, not braces
- sentinel value, Reading and Writing Data in Text Format, Handling Missing Data
- sequence functions, Built-in Sequence Functions-reversed
- serialization (see storing data)
- Series data structure
- about, pandas, Series-Series
- duplicate indexes example, Axis Indexes with Duplicate Labels
- grouping with, Grouping with Dicts and Series
- JSON data and, JSON Data
- operations between DataFrame and, Operations between DataFrame and Series
- plot method arguments, Line Plots
- ranking data in, Sorting and Ranking
- sorting considerations, Sorting and Ranking, Indirect Sorts: argsort and lexsort
- summary statistics methods for, Correlation and Covariance
- set comprehensions, List, Set, and Dict Comprehensions
- set function, set, Bar Plots
- set literals, set
- set operations, set-set, Unique and Other Set Logic
- setattr function, Attributes and methods
- setdefault method, Default values
- setdiff1d method, Unique and Other Set Logic
- sets (data structures), set-set
- setxor1d method, Unique and Other Set Logic
- set_categories method, Categorical Methods
- set_index method, Pivoting “Long” to “Wide” Format
- set_title method, Setting the title, axis labels, ticks, and ticklabels, Annotations and Drawing on a Subplot
- set_trace function, Other ways to make use of the debugger
- set_value method, Selection with loc and iloc
- set_xlabel method, Setting the title, axis labels, ticks, and ticklabels
- set_xlim method, Annotations and Drawing on a Subplot
- set_xticklabels method, Setting the title, axis labels, ticks, and ticklabels
- set_xticks method, Setting the title, axis labels, ticks, and ticklabels
- set_ylim method, Annotations and Drawing on a Subplot
- shape attribute, The NumPy ndarray: A Multidimensional Array Object-Creating ndarrays, Reshaping Arrays
- shell commands in IPython, Shell Commands and Aliases
- shift method, Shifting (Leading and Lagging) Data, Downsampling
- shifting time series data, Shifting (Leading and Lagging) Data-Shifting dates with offsets
- shuffle function, Pseudorandom Number Generation
- side effects, Mutable and immutable objects
- sign function, Universal Functions: Fast Element-Wise Array Functions, Detecting and Filtering Outliers
- sin function, Universal Functions: Fast Element-Wise Array Functions
- sinh function, Universal Functions: Fast Element-Wise Array Functions
- size method, GroupBy Mechanics
- skew method, Summarizing and Computing Descriptive Statistics
- skipna method, Summarizing and Computing Descriptive Statistics
- slice method, Vectorized String Functions in pandas
- slice notation, Slicing
- slicing
- Smith, Nathaniel, statsmodels
- Social Security Administration (SSA), US Baby Names 1880–2010
- software development tools for IPython
- solve function, Linear Algebra
- sort method, Sorting, sorted, Anonymous (Lambda) Functions, Sorting
- sorted function, Sorting, sorted
- sorting considerations
- finding elements in sorted arrays, numpy.searchsorted: Finding Elements in a Sorted Array
- hierarchical indexing, Reordering and Sorting Levels
- in-place sorts, Sorting, More About Sorting
- indirect sorts, Indirect Sorts: argsort and lexsort
- missing data, Sorting and Ranking
- NumPy library, Sorting, More About Sorting-numpy.searchsorted: Finding Elements in a Sorted Array
- pandas library, Sorting and Ranking-Sorting and Ranking, Indirect Sorts: argsort and lexsort, numpy.searchsorted: Finding Elements in a Sorted Array
- partially sorting arrays, Partially Sorting Arrays
- stable sorting, Alternative Sort Algorithms
- sort_index method, Sorting and Ranking
- sort_values method, Sorting and Ranking, Indirect Sorts: argsort and lexsort
- spaces, structuring code with, Indentation, not braces
- split concatenation function, Concatenating and Splitting Arrays
- split function, Concatenating and Splitting Arrays
- split method, Working with Delimited Formats, String Object Methods, String Object Methods-Regular Expressions, Regular Expressions, Vectorized String Functions in pandas
- split-apply-combine
- SQL (structured query language), Data Aggregation and Group
Operations
- SQLAlchemy project, Interacting with Databases
- sqlite3 module, Interacting with Databases
- sqrt function, Universal Functions: Fast Element-Wise Array Functions
- square brackets [], Tuple, List
- square function, Universal Functions: Fast Element-Wise Array Functions
- SSA (Social Security Administration), US Baby Names 1880–2010
- stable sorting, Alternative Sort Algorithms
- stack method, Reshaping with Hierarchical Indexing
- stacked format, Pivoting “Long” to “Wide” Format
- stacking operation, Combining and Merging Datasets, Concatenating Along an Axis
- start index, Slicing
- startswith method, String Object Methods, Vectorized String Functions in pandas
- Stata file format, Reading and Writing Data in Text Format
- statistical methods, Mathematical and Statistical Methods-Mathematical and Statistical Methods
- statsmodels library
- std method, Mathematical and Statistical Methods, Summarizing and Computing Descriptive Statistics, Data Aggregation
- step index, Slicing
- stop index, Slicing
- storing data
- str data type, Scalar Types, Type casting
- str function, Strings, Type casting, Converting Between String and Datetime
- strftime method, Dates and times, Converting Between String and Datetime
- strides/strided view, ndarray Object Internals
- strings
- concatenating, Strings
- converting between datetime and, Converting Between String and Datetime-Converting Between String and Datetime
- converting Python objects to, Strings
- data types for, Strings-Strings
- formatting, Strings
- manipulating, String Manipulation-Vectorized String Functions in pandas
- methods for, String Object Methods-String Object Methods
- regular expressions and, Regular Expressions-Regular Expressions
- slicing, Strings
- vectorized methods in pandas, Vectorized String Functions in pandas-Vectorized String Functions in pandas
- string_ data type, Data Types for ndarrays
- strip method, String Object Methods, String Object Methods, Vectorized String Functions in pandas
- strongly typed language, Dynamic references, strong types
- strptime function, Dates and times, Converting Between String and Datetime
- structured arrays, Structured and Record Arrays-Why Use Structured Arrays?
- structured data, What Kinds of Data?
- sub method, Arithmetic methods with fill values, Regular Expressions, Regular Expressions
- subn method, Regular Expressions
- subplots
- subplots method, Figures and Subplots
- subplots_adjust method, Adjusting the spacing around subplots
- subsetting time series data, Indexing, Selection, Subsetting
- subtract function, Universal Functions: Fast Element-Wise Array Functions
- sum method, Mathematical and Statistical Methods, Summarizing and Computing Descriptive Statistics, Summarizing and Computing Descriptive Statistics, Data Aggregation, ufunc Instance Methods
- summary method, Estimating Linear Models
- summary statistics
- svd function, Linear Algebra
- swapaxes method, Transposing Arrays and Swapping Axes
- swapping axes in arrays, Transposing Arrays and Swapping Axes
- symmetric_difference method, set
- symmetric_difference_update method, set
- syntactic sugar, Jargon
- sys module, Files and the Operating System, Writing Data to Text Format
T
- T attribute, Transposing Arrays and Swapping Axes
- tab completion in IPython, Tab Completion-Tab Completion
- tabs, structuring code with, Indentation, not braces
- take method, Permutation and Random Sampling, Background and Motivation, Fancy Indexing Equivalents: take and put
- tan function, Universal Functions: Fast Element-Wise Array Functions
- tanh function, Universal Functions: Fast Element-Wise Array Functions
- Taylor, Jonathan, statsmodels
- tell method, Files and the Operating System, Files and the Operating System
- ternary expressions, Ternary expressions
- text editors, Integrated Development Environments (IDEs) and Text
Editors
- text files
- text function, Annotations and Drawing on a Subplot
- TextParser class, Reading Text Files in Pieces
- tick mark selection in matplotlib, Ticks, Labels, and Legends-Setting the title, axis labels, ticks, and ticklabels
- tile function, Repeating Elements: tile and repeat
- time data type, Dates and times, Date and Time Data Types and Tools
- %time magic
function, About Magic Commands, Timing Code: %time and %timeit
- time module, Date and Time Data Types and Tools
- time series data
- about, Time Series
- basics overview, Time Series Basics-Time Series Basics
- date offsets and, Frequencies and Date Offsets, Shifting dates with offsets-Shifting dates with offsets
- estimating time series processes, Estimating Time Series Processes
- frequences and, Generating Date Ranges
- frequencies and, Frequencies and Date Offsets, Resampling and Frequency Conversion-Resampling with Periods
- indexing and, Indexing, Selection, Subsetting
- moving window functions, Moving Window Functions-User-Defined Moving Window Functions
- periods in, Periods and Period Arithmetic-Creating a PeriodIndex from Arrays
- resampling, Resampling and Frequency Conversion-Resampling with Periods
- selecting, Indexing, Selection, Subsetting
- shifting, Shifting (Leading and Lagging) Data-Shifting dates with offsets
- subsetting, Indexing, Selection, Subsetting
- time zone handling, Time Zone Handling-Operations Between Different Time Zones
- with duplicate
indexes, Time Series with Duplicate Indices
- time zones
- time, programmer versus CPU, Why Not Python?
- timedelta data type, Time Series-Date and Time Data Types and Tools
- TimeGrouper object, Grouped Time Resampling
- %timeit magic
function, About Magic Commands, The Importance of Contiguous Memory, Timing Code: %time and %timeit
- Timestamp object, Time Series Basics, Shifting dates with offsets, Operations with Time Zone−Aware Timestamp Objects
- timestamps
- timezone method, Time Zone Handling
- timing code, Timing Code: %time and %timeit-Timing Code: %time and %timeit
- top function, Apply: General split-apply-combine
- to_csv method, Writing Data to Text Format
- to_datetime method, Converting Between String and Datetime
- to_excel method, Reading Microsoft Excel Files
- to_json method, JSON Data
- to_period method, Converting Timestamps to Periods (and Back)
- to_pickle method, Binary Data Formats
- to_timestamp method, Converting Timestamps to Periods (and Back)
- trace function, Linear Algebra
- transform method, Group Transforms and “Unwrapped” GroupBys-Group Transforms and “Unwrapped” GroupBys
- transforming data
- about, Data Transformation
- computing indicator/dummy variables, Computing Indicator/Dummy Variables-Computing Indicator/Dummy Variables
- detecting and filtering outliers, Detecting and Filtering Outliers
- discretization and binning, Discretization and Binning
- in Patsy formulas, Data Transformations in Patsy Formulas
- permutation and random sampling, Permutation and Random Sampling
- removing duplicates, Removing Duplicates
- renaming axis indexes, Renaming Axis Indexes
- replacing values, Replacing Values
- using functions or mapping, Transforming Data Using a Function or Mapping
- transpose method, Transposing Arrays and Swapping Axes
- transposing arrays, Transposing Arrays and Swapping Axes
- truncate method, Indexing, Selection, Subsetting
- try/except blocks, Errors and Exception Handling-Errors and Exception Handling
- tuples (data structures)
- “two-language”
problem, Solving the “Two-Language” Problem
- type casting, Type casting
- type inference in functions, Reading and Writing Data in Text Format
- TypeError exception, Errors and Exception Handling
- tzinfo data type, Date and Time Data Types and Tools
- tz_convert method, Time Zone Localization and Conversion
U
- %U datetime
format, Dates and times, Converting Between String and Datetime
- u(p) debugger command, Interactive Debugger
- ufuncs (see universal functions)
- uint16 data type, Data Types for ndarrays
- uint32 data type, Data Types for ndarrays
- uint64 data type, Data Types for ndarrays
- uint8 data type, Data Types for ndarrays
- unary universal functions, Universal Functions: Fast Element-Wise Array Functions, Universal Functions: Fast Element-Wise Array Functions
- underscore (_), Tab Completion, Unpacking tuples, NumPy dtype Hierarchy
- undescore (_), Input and Output Variables
- Unicode standard, Strings, Bytes and Unicode, Bytes and Unicode with Files
- unicode_ data type, Data Types for ndarrays
- uniform function, Pseudorandom Number Generation
- union method, set-set, Index Objects
- union1d method, Unique and Other Set Logic
- unique method, Unique and Other Set Logic-Unique and Other Set Logic, Index Objects, Unique Values, Value Counts, and Membership, Unique Values, Value Counts, and Membership, Background and Motivation
- universal functions
- unpacking tuples, Unpacking tuples
- unstack method, Reshaping with Hierarchical Indexing
- unwrapped group operation, Group Transforms and “Unwrapped” GroupBys
- update method, dict, set
- updating packages, Installing or Updating Python Packages
- upper method, String Object Methods, Vectorized String Functions in pandas
- upsampling, Resampling and Frequency Conversion, Upsampling and Interpolation
- US baby names dataset example, US Baby Names 1880–2010-Boy names that became girl names (and vice versa)
- US Federal Election Commission database example, 2012 Federal Election Commission Database-Donation Statistics by State
- USA.gov
dataset example, 1.USA.gov Data from Bitly-Counting Time Zones with pandas
- USDA food database example, USDA Food Database-USDA Food Database
- UTC (coordinated universal time), Time Zone Handling
- UTF-8 encoding, Bytes and Unicode with Files
V
- ValueError exception, Errors and Exception Handling, Data Types for ndarrays
- values attribute, DataFrame
- values method, dict, Pivot Tables and Cross-Tabulation
- values property, Interfacing Between pandas and Model Code
- value_count method, Discretization and Binning
- value_counts method, Unique Values, Value Counts, and Membership, Bar Plots, Background and Motivation
- var method, Mathematical and Statistical Methods, Summarizing and Computing Descriptive Statistics, Data Aggregation
- variables
- dummy, Computing Indicator/Dummy Variables-Computing Indicator/Dummy Variables, Creating dummy variables for modeling, Interfacing Between pandas and Model Code, Categorical Data and Patsy
- function scope and, Namespaces, Scope, and Local Functions
- in Python, Variables and argument passing-Dynamic references, strong types
- indicator, Computing Indicator/Dummy Variables-Computing Indicator/Dummy Variables
- input, Input and Output Variables
- output, Input and Output Variables
- shell commands and, Shell Commands and Aliases
- vectorization, Arithmetic with NumPy Arrays
- vectorize function, Writing New ufuncs in Python, Creating Custom numpy.ufunc Objects with Numba
- vectorized string methods in pandas, Vectorized String Functions in pandas-Vectorized String Functions in pandas
- visualization tools, Other Python Visualization Tools
- vsplit function, Concatenating and Splitting Arrays
- vstack function, Concatenating and Splitting Arrays
W
- %w datetime
format, Dates and times, Converting Between String and Datetime
- %W datetime
format, Dates and times, Converting Between String and Datetime
- w(here) debugger command, Interactive Debugger
- Waskom, Michael, Plotting with pandas and seaborn
- Wattenberg, Laura, The “last letter” revolution
- Web APIs, pandas interacting with, Interacting with Web APIs
- Web scraping, XML and HTML: Web Scraping-Parsing XML with lxml.objectify
- where function, Expressing Conditional Logic as Array Operations, Combining Data with Overlap
- while loops, while loops
- whitespace
- %who magic
function, About Magic Commands
- %whos magic
function, About Magic Commands
- %who_ls magic
function, About Magic Commands
- Wickham, Hadley, Binary Data Formats, GroupBy Mechanics, US Baby Names 1880–2010
- wildcard expressions, Introspection
- Williams, Ashley, USDA Food Database
- Windows, setting up Python on, Windows
- with statement, Files and the Operating System
- wrangling (see data wrangling)
- write method, Files and the Operating System
- write-only mode for files, Files and the Operating System
- writelines method, Files and the Operating System-Files and the Operating System
- writing data in text format, Reading and Writing Data in Text Format-Writing Data to Text Format
X
- %x datetime
format, Converting Between String and Datetime
- %X datetime
format, Converting Between String and Datetime
- %xdel magic
function, About Magic Commands, Input and Output Variables
- xlim method, Ticks, Labels, and Legends
- xlrd package, Reading Microsoft Excel Files
- XLS files, Reading Microsoft Excel Files
- XLSX files, Reading Microsoft Excel Files
- XML files, XML and HTML: Web Scraping-Parsing XML with lxml.objectify
- %xmode magic
function, Exceptions in IPython
Python for Data Analysis, 2nd Edition
Published by
O'Reilly Media, Inc., 2017