iode.ComputedTable.plotting_series_name

ComputedTable.plotting_series_name(row: int, op_files: int) → str[source]

Name of the series to plot.

Parameters:

rowint: The row passed as position (int).
op_filesint: The files operation passed as position (int).

Returns:

str

Examples

>>> from iode import SAMPLE_DATA_DIR
>>> from iode import Table, tables
>>> tables.load(f"{SAMPLE_DATA_DIR}/fun.tbl")           
Loading .../fun.tbl
46 objects loaded
>>> # simple time series (one extra file) - 5 observations
>>> computed_table = tables["C8_1"].compute("2010[1;2]:5")
>>> computed_table              
   line title \ period[file]     |  10[1]   |  10[2]   |...|  14[1]   |  14[2]
--------------------------------------------------------...----------------------
Output potentiel                 |  6936.11 |  6797.39 |...|  7460.12 |  7310.91
Stock de capital                 | 11293.85 | 11067.97 |...| 12263.95 | 12018.67
Intensité de capital             |     0.39 |     0.38 |...|     0.36 |     0.35
Productivité totale des facteurs |     1.10 |     1.08 |...|     1.14 |     1.12

>>> computed_table.plotting_series_name(0, 0)
'Output potentiel [1]'
>>> computed_table.plotting_series_name(2, 1)
'Intensité de capital [2]'
>>> computed_table.plotting_series_name(3, 0)
'Productivité totale des facteurs [1]'