estimators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 194 19 Related Python libraries 195 19.1 la (larry) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 195 20 Comparison with R / R libraries 197 20.1 data.frame . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . intended to integrate well within a scientific computing environment with many other 3rd party libraries. Here are just a few of the things that pandas does well: • Easy handling of missing data (represented

estimators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 194 19 Related Python libraries 195 19.1 la (larry) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 195 20 Comparison with R / R libraries 197 20.1 data.frame . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . intended to integrate well within a scientific computing environment with many other 3rd party libraries. Here are just a few of the things that pandas does well: • Easy handling of missing data (represented

environment is like a virtualenv that allows you to specify a specific version of Python and set of libraries. Run the following commands from a terminal window: conda create -n name_of_my_env python This If installed, must be Version 1.2.1 or higher. Note: You are highly encouraged to install these libraries, as they provide speed improvements, especially when working with large data sets. 2.4.2 Optional Compression for msgpack Optional dependencies for parsing HTML One of the following combinations of libraries is needed to use the top-level read_html() function: Changed in version 0.23.0. • BeautifulSoup4

estimators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 206 19 Related Python libraries 207 19.1 la (larry) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 207 20 Comparison with R / R libraries 209 20.1 data.frame . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . intended to integrate well within a scientific computing environment with many other 3rd party libraries. Here are just a few of the things that pandas does well: • Easy handling of missing data (represented

estimators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 432 23 Related Python libraries 433 23.1 la (larry) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 433 24 Comparison with R / R libraries 435 24.1 data.frame . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . intended to integrate well within a scientific computing environment with many other 3rd party libraries. Here are just a few of the things that pandas does well: • Easy handling of missing data (represented

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 855 2.22.4 Use other libraries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 856 2.23 Sparse environment is like a virtualenv that allows you to specify a specific version of Python and set of libraries. Run the following commands from a terminal window: conda create -n name_of_my_env python This encounter an ImportError, it usually means that Python couldn’t find pandas in the list of available libraries. Python internally has a list of directories it searches through, to find packages. You can obtain

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 855 2.22.4 Use other libraries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 856 2.23 Sparse environment is like a virtualenv that allows you to specify a specific version of Python and set of libraries. Run the following commands from a terminal window: conda create -n name_of_my_env python This encounter an ImportError, it usually means that Python couldn’t find pandas in the list of available libraries. Python internally has a list of directories it searches through, to find packages. You can obtain

4 X python-dateutil 2.6.1 X bottleneck 1.2.1 numexpr 2.6.2 pytest (dev) 4.0.2 For optional libraries the general recommendation is to use the latest version. The following table lists the lowest version version per library that is currently being tested throughout the development of pandas. Optional libraries below the lowest tested version may still work, but are not considered supported. 16 Chapter 1 environment is like a virtualenv that allows you to specify a specific version of Python and set of libraries. Run the following commands from a terminal window: conda create -n name_of_my_env python This

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 916 2.24.4 Use other libraries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 917 2.25 Sparse environment is like a virtualenv that allows you to specify a specific version of Python and set of libraries. Run the following commands from a terminal window: conda create -n name_of_my_env python This encounter an ImportError, it usually means that Python couldn’t find pandas in the list of available libraries. Python internally has a list of directories it searches through, to find packages. You can obtain

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 954 2.24.4 Use other libraries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 956 2.25 Sparse data environment is like a virtualenv that allows you to specify a specific version of Python and set of libraries. Run the following commands from a terminal window: conda create -n name_of_my_env python This encounter an ImportError, it usually means that Python couldn’t find pandas in the list of available libraries. Python internally has a list of directories it searches through, to find packages. You can obtain