involves downloading the installer which is a few hundred megabytes in size. If you want to have more control on which packages, or have a limited internet bandwidth, then installing pandas with Miniconda may to_numpy() may involve copying data and coercing values. See dtypes for more. to_numpy() gives some control over the dtype of the resulting numpy.ndarray. For example, consider date- times with timezones. Dependencies for more installation info. These are both enabled to be used by default, you can control this by setting the options: New in version 0.20.0. pd.set_option('compute.use_bottleneck', False)

. . . . . . . . . . . . . . . . . . . . 68 3 Frequently Asked Questions (FAQ) 69 3.1 How do I control the way my DataFrame is displayed? . . . . . . . . . . . . . . . . . . . . . . . . . 69 3.2 Adding added option display.max_seq_items to control the number of elements printed per sequence pprinting it. (GH2979) • added option display.chop_threshold to control display of small numerical values. (GH2739) and 0) for numeric operations. (GH2641) • to_html() now accepts an optional “escape” argument to control reserved HTML character escaping (enabled by default) and escapes &, in addition to < and >. (GH2919)

. . . . . . . . . . . . . . . . . . . 100 3 Frequently Asked Questions (FAQ) 101 3.1 How do I control the way my DataFrame is displayed? . . . . . . . . . . . . . . . . . . . . . . . . . 101 3.2 Adding datetime64[ns](1), float64(2) • Add show_dimensions display option for the new DataFrame repr to control whether the dimensions print. In [14]: df = DataFrame([[1, 2], [3, 4]]) In [15]: pd.set_option(’show_dimensions’ added option display.max_seq_items to control the number of elements printed per sequence pprinting it. (GH2979) • added option display.chop_threshold to control display of small numerical values. (GH2739)

. . . . . . . . . . . . . . . . . . . 128 3 Frequently Asked Questions (FAQ) 129 3.1 How do I control the way my DataFrame is displayed? . . . . . . . . . . . . . . . . . . . . . . . . . 129 3.2 Adding datetime64[ns](1), float64(2) • Add show_dimensions display option for the new DataFrame repr to control whether the dimensions print. In [14]: df = DataFrame([[1, 2], [3, 4]]) In [15]: pd.set_option(’show_dimensions’ added option display.max_seq_items to control the number of elements printed per sequence pprinting it. (GH2979) • added option display.chop_threshold to control display of small numerical values. (GH2739)

float64(2) memory usage: 320.0 bytes • Add show_dimensions display option for the new DataFrame repr to control whether the dimensions print. In [14]: df = DataFrame([[1, 2], [3, 4]]) In [15]: pd.set_option(’show_dimensions’ added option display.max_seq_items to control the number of elements printed per sequence pprinting it. (GH2979) • added option display.chop_threshold to control display of small numerical values. (GH2739) and 0) for numeric operations. (GH2641) • to_html() now accepts an optional “escape” argument to control reserved HTML character escaping (enabled by default) and escapes &, in addition to < and >. (GH2919)

float64(2) memory usage: 320.0 bytes • Add show_dimensions display option for the new DataFrame repr to control whether the dimensions print. In [14]: df = DataFrame([[1, 2], [3, 4]]) In [15]: pd.set_option(’show_dimensions’ added option display.max_seq_items to control the number of elements printed per sequence pprinting it. (GH2979) • added option display.chop_threshold to control display of small numerical values. (GH2739) and 0) for numeric operations. (GH2641) • to_html() now accepts an optional “escape” argument to control reserved HTML character escaping (enabled by default) and escapes &, in addition to < and >. (GH2919)

Out[56]: 2 C 5 D dtype: object • Reindex now has a tolerance argument that allows for finer control of Limits on filling while reindexing (GH10411): In [57]: df = pd.DataFrame({'x': range(5), . step with how numpy handles formatting. Going forward the value of display.precision will directly control the number of places after the decimal, for regular formatting as well as scientific notation, similar float64(2) memory usage: 320.0 bytes • Add show_dimensions display option for the new DataFrame repr to control whether the dimensions print. In [14]: df = DataFrame([[1, 2], [3, 4]]) In [15]: pd.set_option('show_dimensions'

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 379 3.3.1 Version control, Git, and GitHub . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 379 3.3.2 Getting . . . . . . . . . . . 983 23.2 Finer Control: Slicing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 984 23.3 Finer Control: Display Values . . . . . . . . . . . timedelta64 dtypes (GH14714, GH14798) • pd.qcut has gained the duplicates='raise'|'drop' option to control whether to raise on duplicated edges (GH7751) 20 Chapter 1. What’s New pandas: powerful Python

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 377 3.3.1 Version control, Git, and GitHub . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 377 3.3.2 Getting . . . . . . . . . . . 979 23.2 Finer Control: Slicing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 980 23.3 Finer Control: Display Values . . . . . . . . . . . timedelta64 dtypes (GH14714, GH14798) • pd.qcut has gained the duplicates='raise'|'drop' option to control whether to raise on duplicated edges (GH7751) • Series provides a to_excel method to output Excel

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 329 vi 3.3.1 Version control, Git, and GitHub . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 329 3.3.2 Getting that simply silenced the warning. Use numpy.errstate around the source of the RuntimeWarning to control how these conditions are handled. 1.1. v0.19.0 (October 2, 2016) 13 pandas: powerful Python data columns with mixed dtypes and how to handle it (GH13746) • to_html() now has a border argument to control the value in the opening tag. The default is the value of the html.border option, which defaults