. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2484 3.12.2 Styler properties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2517 viii 3 One way you could be encountering this error is if you have multiple Python installations on your system and you don’t have pandas installed in the Python installation you’re currently using. In Linux/Mac installation you’re using. If it’s something like “/usr/bin/python”, you’re using the Python from the system, which is not recommended. It is highly recommended to use conda, for quick installation and for

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2561 3.12.2 Styler properties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2593 viii 3 One way you could be encountering this error is if you have multiple Python installations on your system and you don’t have pandas installed in the Python installation you’re currently using. In Linux/Mac installation you’re using. If it’s something like “/usr/bin/python”, you’re using the Python from the system, which is not recommended. It is highly recommended to use conda, for quick installation and for

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2561 3.12.2 Styler properties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2593 viii 3 One way you could be encountering this error is if you have multiple Python installations on your system and you don’t have pandas installed in the Python installation you’re currently using. In Linux/Mac installation you’re using. If it’s something like “/usr/bin/python”, you’re using the Python from the system, which is not recommended. It is highly recommended to use conda, for quick installation and for

underlying array is a numpy.ndarray. However, pandas and 3rd party libraries may extend NumPy’s type system to add support for custom arrays (see dtypes). To get the actual data inside a Index or Series, tuples are returned. 3.3.9 .dt accessor Series has an accessor to succinctly return datetime like properties for the values of the Series, if it is a date- time/period like Series. This will return a Series does not support timezone-aware datetimes). Pandas and third-party libraries extend NumPy’s type system in a few places. This section describes the extensions pandas has made internally. See Extension

underlying array is a numpy.ndarray. However, pandas and 3rd party libraries may extend NumPy’s type system to add support for custom arrays (see dtypes). To get the actual data inside a Index or Series, tuples are returned. 2.4.9 .dt accessor Series has an accessor to succinctly return datetime like properties for the values of the Series, if it is a date- time/period like Series. This will return a Series does not support timezone-aware datetimes). Pandas and third-party libraries extend NumPy’s type system in a few places. This section describes the extensions pandas has made internally. See Extension

format_and_align(styler): ....: return (styler.format({'N': '{:,}', 'X': '{:.1%}'}) ....: .set_properties(**{'text-align': 'right'})) ....: In [48]: df.style.pipe(format_and_align).set_caption('Summary issues surrounding the installation and usage of the above three libraries. Note: – if you’re on a system with apt-get you can do sudo apt-get build-dep python-lxml to get the necessary dependencies for underlying array is a numpy.ndarray. However, pandas and 3rd party libraries may extend NumPy’s type system to add support for custom arrays (see dtypes). To get the actual data inside a Index or Series,

underlying array is a numpy.ndarray. However, pandas and 3rd party libraries may extend NumPy’s type system to add support for custom arrays (see dtypes). To get the actual data inside a Index or Series, tuples are returned. 3.3.9 .dt accessor Series has an accessor to succinctly return datetime like properties for the values of the Series, if it is a date- time/period like Series. This will return a Series does not support timezone-aware datetimes). Pandas and third-party libraries extend NumPy’s type system in a few places. This section describes the extensions pandas has made internally. See Extension

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2311 3.13.2 Styler properties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2326 3.13.3 One way you could be encountering this error is if you have multiple Python installations on your system and you don’t have pandas installed in the Python installation you’re currently using. In Linux/Mac installation you’re using. If it’s something like “/usr/bin/python”, you’re using the Python from the system, which is not recommended. It is highly recommended to use conda, for quick installation and for

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2311 3.13.2 Styler properties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2326 3.13.3 One way you could be encountering this error is if you have multiple Python installations on your system and you don’t have pandas installed in the Python installation you’re currently using. In Linux/Mac installation you’re using. If it’s something like “/usr/bin/python”, you’re using the Python from the system, which is not recommended. It is highly recommended to use conda, for quick installation and for

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2634 3.12.2 Styler properties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2677 viii 3 One way you could be encountering this error is if you have multiple Python installations on your system and you don’t have pandas installed in the Python installation you’re currently using. In Linux/Mac installation you’re using. If it’s something like “/usr/bin/python”, you’re using the Python from the system, which is not recommended. It is highly recommended to use conda, for quick installation and for