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Mastering pandas for finance : master pandas, an open source Python Data Analysis Library, for financial data analysis / / Michael Heydt ; reviewers, James Beveridge [and four others] ; commissioning editor, Kartikey Pandey ; content development editor, Merwyn D'souza ; technical editor, Shashank Desai ; copy editor, Sarang Chari ; project coordinator, Neha Bhatnagar ; proofreaders, Stephen Copestake, Safis Editing ; indexer, Mariammal Chettiyar ; graphics, Sheetal Aute, Disha Haria ; production coordinator, Conidon Miranda ; cover work, Conidon Miranda
| Mastering pandas for finance : master pandas, an open source Python Data Analysis Library, for financial data analysis / / Michael Heydt ; reviewers, James Beveridge [and four others] ; commissioning editor, Kartikey Pandey ; content development editor, Merwyn D'souza ; technical editor, Shashank Desai ; copy editor, Sarang Chari ; project coordinator, Neha Bhatnagar ; proofreaders, Stephen Copestake, Safis Editing ; indexer, Mariammal Chettiyar ; graphics, Sheetal Aute, Disha Haria ; production coordinator, Conidon Miranda ; cover work, Conidon Miranda |
| Autore | Heydt Michael |
| Edizione | [1st edition] |
| Pubbl/distr/stampa | Birmingham, England ; ; Mumbai, [India] : , : Packt Publishing, , 2015 |
| Descrizione fisica | 1 online resource (298 p.) |
| Disciplina | 332 |
| Collana | Community experience distilled |
| Soggetto topico |
Finance - Mathematical models
Python (Computer program language) Data mining |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
""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 � 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 � .loc[] and .iloc[]""; ""Selecting rows by the index label and/or location � .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 objects""""Summary""; ""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 frequencies""""Representing 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 calculations""""Calculating 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"" ""A brief on Quantifying Trading Behavior in Financial Markets Using Google Trends"" |
| Record Nr. | UNINA-9910797265203321 |
Heydt Michael
|
||
| Birmingham, England ; ; Mumbai, [India] : , : Packt Publishing, , 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Mastering pandas for finance : master pandas, an open source Python Data Analysis Library, for financial data analysis / / Michael Heydt ; reviewers, James Beveridge [and four others] ; commissioning editor, Kartikey Pandey ; content development editor, Merwyn D'souza ; technical editor, Shashank Desai ; copy editor, Sarang Chari ; project coordinator, Neha Bhatnagar ; proofreaders, Stephen Copestake, Safis Editing ; indexer, Mariammal Chettiyar ; graphics, Sheetal Aute, Disha Haria ; production coordinator, Conidon Miranda ; cover work, Conidon Miranda
| Mastering pandas for finance : master pandas, an open source Python Data Analysis Library, for financial data analysis / / Michael Heydt ; reviewers, James Beveridge [and four others] ; commissioning editor, Kartikey Pandey ; content development editor, Merwyn D'souza ; technical editor, Shashank Desai ; copy editor, Sarang Chari ; project coordinator, Neha Bhatnagar ; proofreaders, Stephen Copestake, Safis Editing ; indexer, Mariammal Chettiyar ; graphics, Sheetal Aute, Disha Haria ; production coordinator, Conidon Miranda ; cover work, Conidon Miranda |
| Autore | Heydt Michael |
| Edizione | [1st edition] |
| Pubbl/distr/stampa | Birmingham, England ; ; Mumbai, [India] : , : Packt Publishing, , 2015 |
| Descrizione fisica | 1 online resource (298 p.) |
| Disciplina | 332 |
| Collana | Community experience distilled |
| Soggetto topico |
Finance - Mathematical models
Python (Computer program language) Data mining |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
""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 � 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 � .loc[] and .iloc[]""; ""Selecting rows by the index label and/or location � .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 objects""""Summary""; ""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 frequencies""""Representing 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 calculations""""Calculating 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"" ""A brief on Quantifying Trading Behavior in Financial Markets Using Google Trends"" |
| Record Nr. | UNINA-9910810400103321 |
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Heydt Michael
|
||
| Birmingham, England ; ; Mumbai, [India] : , : Packt Publishing, , 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||