6.0 Utils for entry points of plotting backend matplotlib 2.2.3 Plotting library Jinja2 2.10 Conditional formatting with DataFrame.style tabulate 0.8.7 Printing in Markdown-friendly format (see tabulate) (Mary D Kingcome) ˓→... 248706 16.0000 NaN S [5 rows x 12 columns] To select rows based on a conditional expression, use a condition inside the selection brackets []. The condition inside the selection Getting started pandas: powerful Python data analysis toolkit, Release 1.3.2 The output of the conditional expression (>, but also ==, !=, <, <=,... would work) is actually a pandas Series of boolean values

6.0 Utils for entry points of plotting backend matplotlib 2.2.3 Plotting library Jinja2 2.10 Conditional formatting with DataFrame.style tabulate 0.8.7 Printing in Markdown-friendly format (see tabulate) Kingcome) ␣ ˓→female ... 0 248706 16.0000 NaN S [5 rows x 12 columns] To select rows based on a conditional expression, use a condition inside the selection brackets []. The condition inside the selection (continued from previous page) 890 False Name: Age, Length: 891, dtype: bool The output of the conditional expression (>, but also ==, !=, <, <=,... would work) is actually a pandas Series of boolean values

6.0 Utils for entry points of plotting backend matplotlib 2.2.3 Plotting library Jinja2 2.10 Conditional formatting with DataFrame.style tabulate 0.8.7 Printing in Markdown-friendly format (see tabulate) Hewlett, Mrs. (Mary D Kingcome) ␣ ˓→female 55.0 0 0 248706 16.0000 NaN S To select rows based on a conditional expression, use a condition inside the selection brackets []. The condition inside the selection Getting started pandas: powerful Python data analysis toolkit, Release 1.3.4 The output of the conditional expression (>, but also ==, !=, <, <=,... would work) is actually a pandas Series of boolean values

Visualization Dependency Minimum Version Notes matplotlib 3.3.2 Plotting library Jinja2 2.11 Conditional formatting with DataFrame.style tabulate 0.8.7 Printing in Markdown-friendly format (see tabulate) Kingcome) ␣ ˓→female ... 0 248706 16.0000 NaN S [5 rows x 12 columns] To select rows based on a conditional expression, use a condition inside the selection brackets []. The condition inside the selection (continued from previous page) 890 False Name: Age, Length: 891, dtype: bool The output of the conditional expression (>, but also ==, !=, <, <=,... would work) is actually a pandas Series of boolean values

Visualization Dependency Minimum Version Notes matplotlib 3.3.2 Plotting library Jinja2 2.11 Conditional formatting with DataFrame.style tabulate 0.8.7 Printing in Markdown-friendly format (see tabulate) Kingcome) ␣ ˓→female ... 0 248706 16.0000 NaN S [5 rows x 12 columns] To select rows based on a conditional expression, use a condition inside the selection brackets []. The condition inside the selection (continued from previous page) 890 False Name: Age, Length: 891, dtype: bool The output of the conditional expression (>, but also ==, !=, <, <=,... would work) is actually a pandas Series of boolean values

Visualization Dependency Minimum Version Notes matplotlib 3.3.2 Plotting library Jinja2 3.0.0 Conditional formatting with DataFrame.style tabulate 0.8.9 Printing in Markdown-friendly format (see tabulate) Kingcome) ␣ ˓→female ... 0 248706 16.0000 NaN S [5 rows x 12 columns] To select rows based on a conditional expression, use a condition inside the selection brackets []. The condition inside the selection False 888 False 889 False 890 False Name: Age, Length: 891, dtype: bool The output of the conditional expression (>, but also ==, !=, <, <=,... would work) is actually a pandas Series of boolean values

Dependency Minimum Version Notes BeautifulSoup4 4.6.0 HTML parser for read_html (see note) Jinja2 Conditional formatting with DataFrame.style PyQt4 Clipboard I/O PyQt5 Clipboard I/O PyTables 3.4.3 HDF5-based Kingcome) ˓→female ... 0 248706 16.0000 NaN S [5 rows x 12 columns] To select rows based on a conditional expression, use a condition inside the selection brackets []. 22 Chapter 1. Getting started pandas: False 888 False 889 False 890 False Name: Age, Length: 891, dtype: bool The output of the conditional expression (>, but also ==, !=, <, <=,... would work) is actually a pandas Series of boolean values

Dependency Minimum Version Notes BeautifulSoup4 4.6.0 HTML parser for read_html (see note) Jinja2 Conditional formatting with DataFrame.style PyQt4 Clipboard I/O PyQt5 Clipboard I/O PyTables 3.4.3 HDF5-based Hewlett, Mrs. (Mary D Kingcome) ˓→female 55.0 0 0 248706 16.0000 NaN S To select rows based on a conditional expression, use a condition inside the selection brackets []. The condition inside the selection False 888 False 889 False 890 False Name: Age, Length: 891, dtype: bool The output of the conditional expression (>, but also ==, !=, <, <=,... would work) is actually a pandas Series of boolean values

Dependency Minimum Version Notes BeautifulSoup4 4.6.0 HTML parser for read_html (see note) Jinja2 Conditional formatting with DataFrame.style PyQt4 Clipboard I/O PyQt5 Clipboard I/O PyTables 3.4.2 HDF5-based powerful Python data analysis toolkit, Release 1.0.5 Selection Note: While standard Python / Numpy expressions for selecting and setting are intuitive and come in handy for interactive work, for production array, as in the code snippet below. Note that pattern-matching in str generally uses regular expressions by default (and in some cases always uses them). See more at Vectorized String Methods. In [71]:

Dependency Minimum Version Notes BeautifulSoup4 4.6.0 HTML parser for read_html (see note) Jinja2 Conditional formatting with DataFrame.style PyQt4 Clipboard I/O PyQt5 Clipboard I/O PyTables 3.4.2 HDF5-based powerful Python data analysis toolkit, Release 1.0.4 Selection Note: While standard Python / Numpy expressions for selecting and setting are intuitive and come in handy for interactive work, for production array, as in the code snippet below. Note that pattern-matching in str generally uses regular expressions by default (and in some cases always uses them). See more at Vectorized String Methods. In [71]: