DatetimeIndex.nlevels

Series.dt.to_pytimedelta() [source]

MultiIndex.ndim return the number of dimensions of the underlying data, by definition 1

DataFrame.values Numpy representation of NDFrame Notes The dtype will be a lower-common-denominator dtype (implicit upcasting); that is to say if the dtypes (even of numeric types) are mixed, the one that accommodates all will be chosen. Use this with care if you are not dealing with the blocks. e.g. If the dtypes are float16 and float32, dtype will be upcast to float32. If dtypes are int32 and uint8, dtype will be upcast to int32. By numpy.find_common_type convention, mixing int64 and uint

DataFrame.get_ftype_counts() [source] Return the counts of ftypes in this object.

Index.max() [source] The maximum value of the object

pandas.read_html(io, match='.+', flavor=None, header=None, index_col=None, skiprows=None, attrs=None, parse_dates=False, tupleize_cols=False, thousands=', ', encoding=None, decimal='.', converters=None, na_values=None, keep_default_na=True) [source] Read HTML tables into a list of DataFrame objects. Parameters: io : str or file-like A URL, a file-like object, or a raw string containing HTML. Note that lxml only accepts the http, ftp and file url protocols. If you have a URL that starts wi

DatetimeIndex.hasnans = None

pandas.read_json(path_or_buf=None, orient=None, typ='frame', dtype=True, convert_axes=True, convert_dates=True, keep_default_dates=True, numpy=False, precise_float=False, date_unit=None, encoding=None, lines=False) [source] Convert a JSON string to pandas object Parameters: path_or_buf : a valid JSON string or file-like, default: None The string could be a URL. Valid URL schemes include http, ftp, s3, and file. For file URLs, a host is expected. For instance, a local file could be file://

Panel.to_long(*args, **kwargs) [source]