DataFrame.rtruediv(other, axis='columns', level=None, fill_value=None) [source] Floating division of dataframe and other, element-wise (binary operator rtruediv). Equivalent to other / dataframe, but with support to substitute a fill_value for missing data in one of the inputs. Parameters: other : Series, DataFrame, or constant axis : {0, 1, ?index?, ?columns?} For Series input, axis to match Series index on fill_value : None or float value, default None Fill missing (NaN) values with t

DataFrame.rsub(other, axis='columns', level=None, fill_value=None) [source] Subtraction of dataframe and other, element-wise (binary operator rsub). Equivalent to other - dataframe, but with support to substitute a fill_value for missing data in one of the inputs. Parameters: other : Series, DataFrame, or constant axis : {0, 1, ?index?, ?columns?} For Series input, axis to match Series index on fill_value : None or float value, default None Fill missing (NaN) values with this value. If

DataFrame.rpow(other, axis='columns', level=None, fill_value=None) [source] Exponential power of dataframe and other, element-wise (binary operator rpow). Equivalent to other ** dataframe, but with support to substitute a fill_value for missing data in one of the inputs. Parameters: other : Series, DataFrame, or constant axis : {0, 1, ?index?, ?columns?} For Series input, axis to match Series index on fill_value : None or float value, default None Fill missing (NaN) values with this val

DataFrame.round(decimals=0, *args, **kwargs) [source] Round a DataFrame to a variable number of decimal places. New in version 0.17.0. Parameters: decimals : int, dict, Series Number of decimal places to round each column to. If an int is given, round each column to the same number of places. Otherwise dict and Series round to variable numbers of places. Column names should be in the keys if decimals is a dict-like, or in the index if decimals is a Series. Any columns not included in de

DataFrame.rolling(window, min_periods=None, freq=None, center=False, win_type=None, on=None, axis=0) [source] Provides rolling window calculcations. New in version 0.18.0. Parameters: window : int, or offset Size of the moving window. This is the number of observations used for calculating the statistic. Each window will be a fixed size. If its an offset then this will be the time period of each window. Each window will be a variable sized based on the observations included in the time-

DataFrame.rmul(other, axis='columns', level=None, fill_value=None) [source] Multiplication of dataframe and other, element-wise (binary operator rmul). Equivalent to other * dataframe, but with support to substitute a fill_value for missing data in one of the inputs. Parameters: other : Series, DataFrame, or constant axis : {0, 1, ?index?, ?columns?} For Series input, axis to match Series index on fill_value : None or float value, default None Fill missing (NaN) values with this value.

DataFrame.rmod(other, axis='columns', level=None, fill_value=None) [source] Modulo of dataframe and other, element-wise (binary operator rmod). Equivalent to other % dataframe, but with support to substitute a fill_value for missing data in one of the inputs. Parameters: other : Series, DataFrame, or constant axis : {0, 1, ?index?, ?columns?} For Series input, axis to match Series index on fill_value : None or float value, default None Fill missing (NaN) values with this value. If both

DataFrame.rfloordiv(other, axis='columns', level=None, fill_value=None) [source] Integer division of dataframe and other, element-wise (binary operator rfloordiv). Equivalent to other // dataframe, but with support to substitute a fill_value for missing data in one of the inputs. Parameters: other : Series, DataFrame, or constant axis : {0, 1, ?index?, ?columns?} For Series input, axis to match Series index on fill_value : None or float value, default None Fill missing (NaN) values with

DataFrame.reset_index(level=None, drop=False, inplace=False, col_level=0, col_fill='') [source] For DataFrame with multi-level index, return new DataFrame with labeling information in the columns under the index names, defaulting to ?level_0?, ?level_1?, etc. if any are None. For a standard index, the index name will be used (if set), otherwise a default ?index? or ?level_0? (if ?index? is already taken) will be used. Parameters: level : int, str, tuple, or list, default None Only remove

DataFrame.resample(rule, how=None, axis=0, fill_method=None, closed=None, label=None, convention='start', kind=None, loffset=None, limit=None, base=0, on=None, level=None) [source] Convenience method for frequency conversion and resampling of time series. Object must have a datetime-like index (DatetimeIndex, PeriodIndex, or TimedeltaIndex), or pass datetime-like values to the on or level keyword. Parameters: rule : string the offset string or object representing target conversion axis :