Module `trase.tools.sei_pcs.plotting`

Functions

def dumbbell_compare(df_a, df_b, value, group_by, comparator=<function Compare.absolute_error>, labels=('Base', 'Comparison'), colors=('#4e6356', '#ff6a5f'), title_text='', xaxis_title='', yaxis_title='', legend_title='', label_width=15, shorten_end=False, max_rows=15, other_label='OTHER', include_other=True, row_height_px=40) ‑> plotly.graph_objs.Figure

Compare two dataframes and create a "dumbbell"-style plot.

Here is an ASCII-art of what that looks like:

  BUNGE │   *─────*
CARGILL │          *───*
   ADM  │  *─*
  OTHER │  *
        └────────────────
         0   10   20   30

Args

df_a: base DataFrame.
df_b: comparison DataFrame.
value: the name of the column containing numerical data that will be compared. Any values duplicated over group_by will be summed.
group_by: a list of categorical columns to group by.
comparator : optional: a function which takes two series and returns their comparison. You can also pass in the string name of a method on Compare. See Compare for some examples. Defaults to Compare.absolute_error.
labels : optional: name of the two series that will appear in the legend. Default: ("Base", "Comparison").
title_text : optional: title for the chart. Default ""
xaxis_title : optional: title for the X-axis. Default ""
yaxis_title : optional: title for the Y-axis. Default ""
legend_title : optional: title for the legend. Default ""
label_width : optional: the maximum length of a label before it is shortened with "…". Default: 15
shorten_end : optional: if True labels will be shortened from the end ("LONG LA…"); if False they will be shortened from the start (e.g. "…G LABEL"). Default: False
max_rows : optional: how many rows to show, or None if all rows should be shown. Default: 15
other_label : optional: the name of the "other" category; either a string or a tuple of strings of the same length as group_by. Default: "OTHER"
include_other : optional: whether to include the "OTHER". Default: True

Returns: the plotly Figure

def histogram_compare(df_a, df_b, value, group_by, comparator=<function Compare.absolute_error>, title_text='', scale_by='none', bins=15, significant_digits=2, decimal_points=0, posinf_label='only in b', neginf_label='only in a')

def render_label(value: Union[Tuple, str], shorten_end=False, label_width=15) ‑> str

Plotly cannot render pd.MultiIndex, so we convert the tuples to strings. This function works both on MultiIndex (tuples) or Index (strings).

def sankey(df, value_column, categorical_columns, title_text='', shorten_end=False, label_width=15) ‑> plotly.graph_objs.Figure

Args

df: the dataframe to be rendered. You do not need to consolidate the dataframe, this will be done for you in the function.
value_column: the column which will be used for the widths of the flows
categorical_columns: the columns which will be used for the columns of the Sankey.
title_text : optional: title for the chart. Default ""
label_width : optional: the maximum length of a label before it is shortened with "…". Default: 15
shorten_end : optional: if True labels will be shortened from the end ("LONG LA…"); if False they will be shortened from the start (e.g. "…G LABEL"). Default: False

Returns: the plotly Figure

def shorten_label(label: str, shorten_end=False, label_width=15) ‑> str

Trims labels that are too long and adds '…'