Detail: IndexMillisecond: Exporter

IndexMillisecond.to_html(config=None, style_config=<static_frame.core.style_config.StyleConfig object>)

Return an HTML table representation of this Index using standard TABLE, TR, and TD tags. This is not a complete HTML page.

Parameters:: config – Optional DisplayConfig instance.
Returns:: str

IndexMillisecond.to_html_datatables(fp=None, *, show=True, config=None)

Return a complete HTML representation of this Index using the DataTables JS library for table naviagation and search. The page links to CDNs for JS resources, and thus will not fully render without an internet connection.

Parameters:

fp – optional file path to write; if not provided, a temporary file will be created. Note: the caller is responsible for deleting this file.
show – if True, the file will be opened with a webbrowser.
config – Optional DisplayConfig instance.

Returns:

str, absolute file path to the file written.

IndexMillisecond.to_pandas()

Return a Pandas Index.

>>> ix = sf.IndexMillisecond(('1517-04-01', '1517-12-31', '1517-06-30'))
>>> ix
<IndexMillisecond>
1517-04-01T00:00:00.000
1517-12-31T00:00:00.000
1517-06-30T00:00:00.000
<datetime64[ms]>
>>> ix.to_pandas()
DatetimeIndex(['1517-04-01', '1517-12-31', '1517-06-30'], dtype='datetime64[ms]', freq=None)

IndexMillisecond.to_series()

Return a Series with values from this Index’s labels.

>>> ix = sf.IndexMillisecond(('1517-04-01', '1517-12-31', '1517-06-30'))
>>> ix
<IndexMillisecond>
1517-04-01T00:00:00.000
1517-12-31T00:00:00.000
1517-06-30T00:00:00.000
<datetime64[ms]>
>>> ix.to_series()
<Series>
<Index>
0        1517-04-01T00:00:...
1        1517-12-31T00:00:...
2        1517-06-30T00:00:...
<int64>  <datetime64[ms]>

IndexMillisecond.to_visidata(): Open an interactive VisiData session.