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Mastering pandas for finance :: master pandas, an open source Python data analysis library, for financial data analysis /

If you are interested in quantitative finance, financial modeling, and trading, or simply want to learn how Python and pandas can be applied to finance, then this book is ideal for you. Some knowledge of Python and pandas is assumed. Interest in financial concepts is helpful, but no prior knowledge...

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Bibliographische Detailangaben
1. Verfasser:	Heydt, Michael (VerfasserIn)
Format:	Elektronisch E-Book
Sprache:	English
Veröffentlicht:	Birmingham, UK : Packt Publishing, 2015.
Schriftenreihe:	Community experience distilled.
Schlagworte:	Python (Computer program language) Finance. Quantitative research. Open source software. Python (Langage de programmation) Finances. Recherche quantitative. Logiciels libres. finance. BUSINESS & ECONOMICS > Finance. Finance Open source software Quantitative research
Online-Zugang:	Volltext
Zusammenfassung:	If you are interested in quantitative finance, financial modeling, and trading, or simply want to learn how Python and pandas can be applied to finance, then this book is ideal for you. Some knowledge of Python and pandas is assumed. Interest in financial concepts is helpful, but no prior knowledge is expected.
Beschreibung:	Includes index.
Beschreibung:	1 online resource (1 volume) : illustrations
ISBN:	9781783985111 1783985119

Internformat

MARC


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contents	""Cover""; ""Copyright""; ""Credits""; ""About the Author""; ""About the Reviewers""; ""www.PacktPub.com""; ""Table of Contents""; ""Preface""; ""Chapter 1: Getting Started with pandas Using Wakari.io""; ""What is Wakari?""; ""Creating a Wakari cloud account""; ""Updating existing packages""; ""Installing new packages""; ""Installing the samples in Wakari""; ""Summary""; ""Chapter 2: Introducing the Series and DataFrame""; ""Notebook setup""; ""The main pandas data structures â€? Series and DataFrame""; ""The Series""; ""The DataFrame""; ""The basics of the Series and DataFrame objects"" ""Creating a Series and accessing elements""""Size, shape, uniqueness, and counts of values""; ""Alignment via index labels""; ""Creating a DataFrame""; ""Example data""; ""Selecting columns of a DataFrame""; ""Selecting rows of a DataFrame using the index""; ""Slicing using the [] operator""; ""Selecting rows by the index label and location â€? .loc[] and .iloc[]""; ""Selecting rows by the index label and/or location â€? .ix[]""; ""Scalar lookup by label or location using .at[] and .iat[]""; ""Selecting rows using the Boolean selection""; ""Arithmetic on a DataFrame"" Reindexing the Series and DataFrame objectsSummary -- Chapter 3: Reshaping, Reorganizing, and Aggregating -- Notebook setup -- Loading historical stock data -- Organizing the data for the examples -- Reorganizing and reshaping data -- Concatenating multiple DataFrame objects -- Merging DataFrame objects -- Pivoting -- Stacking and unstacking -- Melting -- Grouping and aggregating -- Splitting -- Aggregating -- Summary -- Chapter 4: Time-series -- Notebook setup -- Time-series data and the DatetimeIndex Creating time-series with specific frequenciesRepresenting intervals of time using periods -- Shifting and lagging time-series data -- Frequency conversion of time-series data -- Resampling of time-series -- Summary -- Chapter 5: Time-series Stock Data -- Notebook setup -- Obtaining historical stock and index data -- Fetching historical stock data from Yahoo! -- Fetching index data from Yahoo! -- Visualizing financial time-series data -- Plotting closing prices -- Plotting volume-series data -- Combined price and volumes -- Plotting candlesticks Fundamental financial calculationsCalculating simple daily percentage change -- Calculating simple daily cumulative returns -- Analyzing the distribution of returns -- Histograms -- Q-Q plots -- Box-and-whisker plots -- Comparison of daily percentage change between stocks -- Moving windows -- Volatility calculation -- Rolling correlation of returns -- Least-squares regression of returns -- Comparing stocks to the S & P 500 -- Summary -- Chapter 6: Trading Using Google Trends -- Notebook setup
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series	Community experience distilled.
series2	Community experience distilled
spelling	Heydt, Michael, author. Mastering pandas for finance : master pandas, an open source Python data analysis library, for financial data analysis / Michael Heydt. Master pandas, an open source Python data analysis library, for financial data analysis Birmingham, UK : Packt Publishing, 2015. 1 online resource (1 volume) : illustrations text txt rdacontent computer c rdamedia online resource cr rdacarrier text file Community experience distilled Online resource; title from cover (Safari, viewed June 10, 2015). Includes index. ""Cover""; ""Copyright""; ""Credits""; ""About the Author""; ""About the Reviewers""; ""www.PacktPub.com""; ""Table of Contents""; ""Preface""; ""Chapter 1: Getting Started with pandas Using Wakari.io""; ""What is Wakari?""; ""Creating a Wakari cloud account""; ""Updating existing packages""; ""Installing new packages""; ""Installing the samples in Wakari""; ""Summary""; ""Chapter 2: Introducing the Series and DataFrame""; ""Notebook setup""; ""The main pandas data structures â€? Series and DataFrame""; ""The Series""; ""The DataFrame""; ""The basics of the Series and DataFrame objects"" ""Creating a Series and accessing elements""""Size, shape, uniqueness, and counts of values""; ""Alignment via index labels""; ""Creating a DataFrame""; ""Example data""; ""Selecting columns of a DataFrame""; ""Selecting rows of a DataFrame using the index""; ""Slicing using the [] operator""; ""Selecting rows by the index label and location â€? .loc[] and .iloc[]""; ""Selecting rows by the index label and/or location â€? .ix[]""; ""Scalar lookup by label or location using .at[] and .iat[]""; ""Selecting rows using the Boolean selection""; ""Arithmetic on a DataFrame"" Reindexing the Series and DataFrame objectsSummary -- Chapter 3: Reshaping, Reorganizing, and Aggregating -- Notebook setup -- Loading historical stock data -- Organizing the data for the examples -- Reorganizing and reshaping data -- Concatenating multiple DataFrame objects -- Merging DataFrame objects -- Pivoting -- Stacking and unstacking -- Melting -- Grouping and aggregating -- Splitting -- Aggregating -- Summary -- Chapter 4: Time-series -- Notebook setup -- Time-series data and the DatetimeIndex Creating time-series with specific frequenciesRepresenting intervals of time using periods -- Shifting and lagging time-series data -- Frequency conversion of time-series data -- Resampling of time-series -- Summary -- Chapter 5: Time-series Stock Data -- Notebook setup -- Obtaining historical stock and index data -- Fetching historical stock data from Yahoo! -- Fetching index data from Yahoo! -- Visualizing financial time-series data -- Plotting closing prices -- Plotting volume-series data -- Combined price and volumes -- Plotting candlesticks Fundamental financial calculationsCalculating simple daily percentage change -- Calculating simple daily cumulative returns -- Analyzing the distribution of returns -- Histograms -- Q-Q plots -- Box-and-whisker plots -- Comparison of daily percentage change between stocks -- Moving windows -- Volatility calculation -- Rolling correlation of returns -- Least-squares regression of returns -- Comparing stocks to the S & P 500 -- Summary -- Chapter 6: Trading Using Google Trends -- Notebook setup If you are interested in quantitative finance, financial modeling, and trading, or simply want to learn how Python and pandas can be applied to finance, then this book is ideal for you. Some knowledge of Python and pandas is assumed. Interest in financial concepts is helpful, but no prior knowledge is expected. English. Python (Computer program language) http://id.loc.gov/authorities/subjects/sh96008834 Finance. http://id.loc.gov/authorities/subjects/sh85048256 Quantitative research. http://id.loc.gov/authorities/subjects/sh2007000909 Open source software. http://id.loc.gov/authorities/subjects/sh99003437 Python (Langage de programmation) Finances. Recherche quantitative. Logiciels libres. finance. aat BUSINESS & ECONOMICS Finance. bisacsh Finance fast Open source software fast Python (Computer program language) fast Quantitative research fast has work: Mastering pandas for Finance (Text) https://id.oclc.org/worldcat/entity/E39PCYb8t3C9739Jd6Txkh9wwd https://id.oclc.org/worldcat/ontology/hasWork Print version: Heydt, Michael. Mastering pandas for finance : master pandas, an open source Python Data Analysis Library, for financial data analysis. Birmingham, England ; Mumbai, [India] : Packt Publishing, ©2015 viii, 275 pages 9781783985104 Community experience distilled. http://id.loc.gov/authorities/names/no2011030603 FWS01 ZDB-4-EBA FWS_PDA_EBA https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=996726 Volltext
spellingShingle	Heydt, Michael Mastering pandas for finance : master pandas, an open source Python data analysis library, for financial data analysis / Community experience distilled. ""Cover""; ""Copyright""; ""Credits""; ""About the Author""; ""About the Reviewers""; ""www.PacktPub.com""; ""Table of Contents""; ""Preface""; ""Chapter 1: Getting Started with pandas Using Wakari.io""; ""What is Wakari?""; ""Creating a Wakari cloud account""; ""Updating existing packages""; ""Installing new packages""; ""Installing the samples in Wakari""; ""Summary""; ""Chapter 2: Introducing the Series and DataFrame""; ""Notebook setup""; ""The main pandas data structures â€? Series and DataFrame""; ""The Series""; ""The DataFrame""; ""The basics of the Series and DataFrame objects"" ""Creating a Series and accessing elements""""Size, shape, uniqueness, and counts of values""; ""Alignment via index labels""; ""Creating a DataFrame""; ""Example data""; ""Selecting columns of a DataFrame""; ""Selecting rows of a DataFrame using the index""; ""Slicing using the [] operator""; ""Selecting rows by the index label and location â€? .loc[] and .iloc[]""; ""Selecting rows by the index label and/or location â€? .ix[]""; ""Scalar lookup by label or location using .at[] and .iat[]""; ""Selecting rows using the Boolean selection""; ""Arithmetic on a DataFrame"" Reindexing the Series and DataFrame objectsSummary -- Chapter 3: Reshaping, Reorganizing, and Aggregating -- Notebook setup -- Loading historical stock data -- Organizing the data for the examples -- Reorganizing and reshaping data -- Concatenating multiple DataFrame objects -- Merging DataFrame objects -- Pivoting -- Stacking and unstacking -- Melting -- Grouping and aggregating -- Splitting -- Aggregating -- Summary -- Chapter 4: Time-series -- Notebook setup -- Time-series data and the DatetimeIndex Creating time-series with specific frequenciesRepresenting intervals of time using periods -- Shifting and lagging time-series data -- Frequency conversion of time-series data -- Resampling of time-series -- Summary -- Chapter 5: Time-series Stock Data -- Notebook setup -- Obtaining historical stock and index data -- Fetching historical stock data from Yahoo! -- Fetching index data from Yahoo! -- Visualizing financial time-series data -- Plotting closing prices -- Plotting volume-series data -- Combined price and volumes -- Plotting candlesticks Fundamental financial calculationsCalculating simple daily percentage change -- Calculating simple daily cumulative returns -- Analyzing the distribution of returns -- Histograms -- Q-Q plots -- Box-and-whisker plots -- Comparison of daily percentage change between stocks -- Moving windows -- Volatility calculation -- Rolling correlation of returns -- Least-squares regression of returns -- Comparing stocks to the S & P 500 -- Summary -- Chapter 6: Trading Using Google Trends -- Notebook setup Python (Computer program language) http://id.loc.gov/authorities/subjects/sh96008834 Finance. http://id.loc.gov/authorities/subjects/sh85048256 Quantitative research. http://id.loc.gov/authorities/subjects/sh2007000909 Open source software. http://id.loc.gov/authorities/subjects/sh99003437 Python (Langage de programmation) Finances. Recherche quantitative. Logiciels libres. finance. aat BUSINESS & ECONOMICS Finance. bisacsh Finance fast Open source software fast Python (Computer program language) fast Quantitative research fast
subject_GND	http://id.loc.gov/authorities/subjects/sh96008834 http://id.loc.gov/authorities/subjects/sh85048256 http://id.loc.gov/authorities/subjects/sh2007000909 http://id.loc.gov/authorities/subjects/sh99003437
title	Mastering pandas for finance : master pandas, an open source Python data analysis library, for financial data analysis /
title_alt	Master pandas, an open source Python data analysis library, for financial data analysis
title_auth	Mastering pandas for finance : master pandas, an open source Python data analysis library, for financial data analysis /
title_exact_search	Mastering pandas for finance : master pandas, an open source Python data analysis library, for financial data analysis /
title_full	Mastering pandas for finance : master pandas, an open source Python data analysis library, for financial data analysis / Michael Heydt.
title_fullStr	Mastering pandas for finance : master pandas, an open source Python data analysis library, for financial data analysis / Michael Heydt.
title_full_unstemmed	Mastering pandas for finance : master pandas, an open source Python data analysis library, for financial data analysis / Michael Heydt.
title_short	Mastering pandas for finance :
title_sort	mastering pandas for finance master pandas an open source python data analysis library for financial data analysis
title_sub	master pandas, an open source Python data analysis library, for financial data analysis /
topic	Python (Computer program language) http://id.loc.gov/authorities/subjects/sh96008834 Finance. http://id.loc.gov/authorities/subjects/sh85048256 Quantitative research. http://id.loc.gov/authorities/subjects/sh2007000909 Open source software. http://id.loc.gov/authorities/subjects/sh99003437 Python (Langage de programmation) Finances. Recherche quantitative. Logiciels libres. finance. aat BUSINESS & ECONOMICS Finance. bisacsh Finance fast Open source software fast Python (Computer program language) fast Quantitative research fast
topic_facet	Python (Computer program language) Finance. Quantitative research. Open source software. Python (Langage de programmation) Finances. Recherche quantitative. Logiciels libres. finance. BUSINESS & ECONOMICS Finance. Finance Open source software Quantitative research
url	https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=996726
work_keys_str_mv	AT heydtmichael masteringpandasforfinancemasterpandasanopensourcepythondataanalysislibraryforfinancialdataanalysis AT heydtmichael masterpandasanopensourcepythondataanalysislibraryforfinancialdataanalysis

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