. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 635 2.12.11 Differences to R’s factor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 636 2.12.12 Gotchas manipulating tablular data? Learn the pandas-equivalent operations compared to software you already know: The R programming language provides the data.frame data structure and multiple packages, such as tidyverse cases in finance, statistics, social science, and many areas of engineering. For R users, DataFrame provides everything that R’s data.frame provides and much more. pandas is built on top of NumPy and is intended

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 663 2.12.11 Differences to R’s factor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 664 2.12.12 Gotchas manipulating tablular data? Learn the pandas-equivalent operations compared to software you already know: The R programming language provides the data.frame data structure and multiple packages, such as tidyverse cases in finance, statistics, social science, and many areas of engineering. For R users, DataFrame provides everything that R’s data.frame provides and much more. pandas is built on top of NumPy and is intended

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 664 2.12.11 Differences to R’s factor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 665 2.12.12 Gotchas manipulating tablular data? Learn the pandas-equivalent operations compared to software you already know: The R programming language provides the data.frame data structure and multiple packages, such as tidyverse cases in finance, statistics, social science, and many areas of engineering. For R users, DataFrame provides everything that R’s data.frame provides and much more. pandas is built on top of NumPy and is intended

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 666 2.12.11 Differences to R’s factor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 667 2.12.12 Gotchas manipulating tablular data? Learn the pandas-equivalent operations compared to software you already know: The R programming language provides the data.frame data structure and multiple packages, such as tidyverse cases in finance, statistics, social science, and many areas of engineering. For R users, DataFrame provides everything that R’s data.frame provides and much more. pandas is built on top of NumPy and is intended

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 666 2.12.11 Differences to R’s factor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 667 2.12.12 Gotchas manipulating tablular data? Learn the pandas-equivalent operations compared to software you already know: The R programming language provides the data.frame data structure and multiple packages, such as tidyverse cases in finance, statistics, social science, and many areas of engineering. For R users, DataFrame provides everything that R’s data.frame provides and much more. pandas is built on top of NumPy and is intended

manipulating tablular data? Learn the pandas-equivalent operations compared to software you already know: The R programming language provides the data.frame data structure and multiple packages, such as tidyverse cases in finance, statistics, social science, and many areas of engineering. For R users, DataFrame provides everything that R’s data.frame provides and much more. pandas is built on top of NumPy and is intended categorical data and more) in columns. It is similar to a spreadsheet, a SQL table or the data. frame in R. • The table has 3 columns, each of them with a column label. The column labels are respectively Name

428 22 rpy2 / R interface 431 22.1 Transferring R data sets into Python . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 431 22.2 Converting DataFrames into R objects . . . . . . . . . . . 432 22.3 Calling R functions with pandas objects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 432 22.4 High-level interface to R estimators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 433 24 Comparison with R / R libraries 435 24.1 data.frame . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

majority of typical use cases in finance, statistics, social science, and many areas of engineering. For R users, DataFrame provides everything that Rs data.frame provides and much more. pandas is built on top ============================================================================== Dep. Variable: hr R-squared: 0.685 Model: OLS Adj. R-squared: 0.665 Method: Least Squares F-statistic: 34.28 Date: Sat, 02 Nov 2019 Prob more recently dplyr and magrittr, which have introduced the popular (%>%) (read pipe) operator for R. The implementation of pipe here is quite clean and feels right at home in python. 3.3. Essential basic

560 24 rpy2 / R interface 561 24.1 Transferring R data sets into Python . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 561 24.2 Converting DataFrames into R objects . . . . . . . . . . . 562 24.3 Calling R functions with pandas objects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 562 24.4 High-level interface to R estimators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 564 26 Comparison with R / R libraries 565 26.1 Base R . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 817 22.10 Differences to R’s factor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 818 22.11 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1035 29.2.4 Why not make NumPy like R? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1035 29.3 Integer indexing . . . . . . . . . 1042 30 rpy2 / R interface 1043 30.1 Updating your code to use rpy2 functions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1043 30.2 R interface with rpy2 . . . . .