BarDatafier

Bases: BaseDatafier

Contains data preparation modules, which includes interpolation, rank generation. data should be in this format where time is set to index

    Example:
    >>> time  col1 col2 col3 ...
    >>> 2012   1    0    2
    >>> 2013   2    3    1

Parameters:

Name	Type	Description	Default
`data`	`pd.DataFrame`	The data to be prepared, should be in this format where time is set to index	required
`time_format`	`str`	Index datetime format	required
`ip_freq`	`str`	Interpolation frequency	required
`ip_frac`	`float`	Rank interpolation fraction (check end of docstring), by default 0.5	`0.1`
`n_bars`	`int`	Number of bars to be visible on the plot, by default 10 or less	`10`
`ip_method`	`str`	Interpolation Method, by default "linear"	`'linear'`
`ip_fill_method`	`str`	fill method for ip_frac, by default "bfill"	`'bfill'`

ip_frac is the percentage of NaN values to be linearly interpolated for column ranks

    Consider this example
    >>>               a    b
    >>> date
    >>> 2021-11-13  1.0  4.0
    >>> 2021-11-14  NaN  NaN
    >>> 2021-11-15  NaN  NaN
    >>> 2021-11-16  NaN  NaN
    >>> 2021-11-17  NaN  NaN
    >>> 2021-11-18  2.0  6.0

with ip_frac set to 0.5, 50% of NaN's will be interpolated by ip_method while the rest will be filled by ip_fill_method. The example uses bfill, if ffill is used the filling will happen before interpolation.

    >>>              a      b
    >>> 2021-11-13  1.00  4.00  << original value --------
    >>> 2021-11-14  1.33  4.67                            |
    >>> 2021-11-15  1.67  5.33                            |  50% interpolated
    >>> 2021-11-16  2.00  6.00  <- linear interpolation   |  by ip_method
    >>> 2021-11-17  2.00  6.00      upto here             |  rest are filled
    >>> 2021-11-18  2.00  6.00  << original value---------   by ip_fill_method

This adds stability in the barChartRace and reduces constant shaking of bars.

`get_data_ranks(ip_frac=0.1)`

Creates column ranks and interpolates them.

Parameters:

Name	Type	Description	Default
`ip_frac`	`float`	pct of NaNs to interpolate by 'self.method' rest will be backfilled, by default 0.1	`0.1`

Returns:

Type	Description
`pd.DataFrame`	Interpolated column ranks

`get_top_cols()`

Selects columns where column_rank < n_bars in any timestamp

Returns:

Type	Description
`list[str]`	List of columns that will appear in the animation at least once