maxframe.dataframe.DataFrame.rfloordiv#

DataFrame.rfloordiv(other, axis='columns', level=None, fill_value=None)#

Get Integer division of dataframe and other, element-wise (binary operator rfloordiv). Equivalent to //, but with support to substitute a fill_value for missing data in one of the inputs. With reverse version, floordiv. Among flexible wrappers (add, sub, mul, div, mod, pow) to arithmetic operators: +, -, *, /, //, %, **.

Parameters:

  • other (scalar, sequence, Series, or DataFrame) – Any single or multiple element data structure, or list-like object.

  • axis ({0 or 'index', 1 or 'columns'}) – Whether to compare by the index (0 or ‘index’) or columns (1 or ‘columns’). For Series input, axis to match Series index on.

  • level (int or label) – Broadcast across a level, matching Index values on the passed MultiIndex level.

  • fill_value (float or None, default None) – Fill existing missing (NaN) values, and any new element needed for successful DataFrame alignment, with this value before computation. If data in both corresponding DataFrame locations is missing the result will be missing.

Returns:

Result of the arithmetic operation.

Return type:

DataFrame

See also

DataFrame.add

Add DataFrames.

DataFrame.sub

Subtract DataFrames.

DataFrame.mul

Multiply DataFrames.

DataFrame.div

Divide DataFrames (float division).

DataFrame.truediv

Divide DataFrames (float division).

DataFrame.floordiv

Divide DataFrames (integer division).

DataFrame.mod

Calculate modulo (remainder after division).

DataFrame.pow

Calculate exponential power.

Notes

Mismatched indices will be unioned together.

Examples

>>> import maxframe.dataframe as md
>>> df = md.DataFrame({'angles': [0, 3, 4],
...                    'degrees': [360, 180, 360]},
...                   index=['circle', 'triangle', 'rectangle'])
>>> df.execute()
           angles  degrees
circle          0      360
triangle        3      180
rectangle       4      360

Add a scalar with operator version which return the same results.

>>> (df + 1).execute()
           angles  degrees
circle          1      361
triangle        4      181
rectangle       5      361

>>> df.add(1).execute()
           angles  degrees
circle          1      361
triangle        4      181
rectangle       5      361

Divide by constant with reverse version.

>>> df.div(10).execute()
           angles  degrees
circle        0.0     36.0
triangle      0.3     18.0
rectangle     0.4     36.0

>>> df.rdiv(10).execute()
             angles   degrees
circle          inf  0.027778
triangle   3.333333  0.055556
rectangle  2.500000  0.027778

Subtract a list and Series by axis with operator version.

>>> (df - [1, 2]).execute()
           angles  degrees
circle         -1      358
triangle        2      178
rectangle       3      358

>>> df.sub([1, 2], axis='columns').execute()
           angles  degrees
circle         -1      358
triangle        2      178
rectangle       3      358

>>> df.sub(md.Series([1, 1, 1], index=['circle', 'triangle', 'rectangle']),
...        axis='index').execute()
           angles  degrees
circle         -1      359
triangle        2      179
rectangle       3      359

Multiply a DataFrame of different shape with operator version.

>>> other = md.DataFrame({'angles': [0, 3, 4]},
...                      index=['circle', 'triangle', 'rectangle'])
>>> other.execute()
           angles
circle          0
triangle        3
rectangle       4

>>> df.mul(other, fill_value=0).execute()
           angles  degrees
circle          0      0.0
triangle        9      0.0
rectangle      16      0.0
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