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 . . . . .

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 819 22.10 Differences to R’s factor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 820 22.11 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1037 29.2.4 Why not make NumPy like R? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1037 29.3 Integer indexing . . . . . . . . . 1044 30 rpy2 / R interface 1045 30.1 Updating your code to use rpy2 functions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1045 30.2 R interface with rpy2 . . . . .

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 906 21.10 Differences to R’s factor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 907 21.11 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1137 28.3.4 Why not make NumPy like R? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1137 28.4 Differences with NumPy 1138 29 rpy2 / R interface 1139 29.1 Transferring R data sets into Python . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1139 29.2 Converting DataFrames into R objects . . . .

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 902 21.10 Differences to R’s factor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 904 21.11 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1135 28.3.4 Why not make NumPy like R? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1135 28.4 Differences with NumPy 1136 29 rpy2 / R interface 1137 29.1 Transferring R data sets into Python . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1137 29.2 Converting DataFrames into R objects . . . .

620 24 rpy2 / R interface 621 24.1 Transferring R data sets into Python . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 621 24.2 Converting DataFrames into R objects . . . . . . . . . . . 622 24.3 Calling R functions with pandas objects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 622 24.4 High-level interface to R estimators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 624 26 Comparison with R / R libraries 625 26.1 Base R . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 940 21.11 Differences to R’s factor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 941 21.12 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1173 28.3.4 Why not make NumPy like R? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1173 28.4 Differences with NumPy 1174 29 rpy2 / R interface 1175 29.1 Transferring R data sets into Python . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1175 29.2 Converting DataFrames into R objects . . . .

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 666 22.10 Differences to R’s factor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 667 22.11 . . . . . . . . 891 29 rpy2 / R interface 893 29.1 Updating your code to use rpy2 functions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 893 29.2 R interface with rpy2 . . . . . . . . . . 894 29.3 Transferring R data sets into Python . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 894 29.4 Converting DataFrames into R objects . . . . . . . . . . . . .