# datascience.tables.Table.plot¶

Table.plot(column_for_xticks=None, select=None, overlay=True, width=6, height=4, **vargs)[source]

Plot line charts for the table.

Args:
column_for_xticks (str/array): A column containing x-axis labels
Kwargs:
overlay (bool): create a chart with one color per data column;
if False, each plot will be displayed separately.
vargs: Additional arguments that get passed into plt.plot.
See http://matplotlib.org/api/pyplot_api.html#matplotlib.pyplot.plot for additional arguments that can be passed into vargs.
Raises:
ValueError – Every selected column must be numerical.
Returns:
Returns a line plot (connected scatter). Each plot is labeled using the values in column_for_xticks and one plot is produced for all other columns in self (or for the columns designated by select).
>>> table = Table().with_columns(
...     'days',  make_array(0, 1, 2, 3, 4, 5),
...     'price', make_array(90.5, 90.00, 83.00, 95.50, 82.00, 82.00),
...     'projection', make_array(90.75, 82.00, 82.50, 82.50, 83.00, 82.50))
>>> table
days | price | projection
0    | 90.5  | 90.75
1    | 90    | 82
2    | 83    | 82.5
3    | 95.5  | 82.5
4    | 82    | 83
5    | 82    | 82.5
>>> table.plot('days') # doctest: +SKIP
<line graph with days as x-axis and lines for price and projection>
>>> table.plot('days', overlay=False) # doctest: +SKIP
<line graph with days as x-axis and line for price>
<line graph with days as x-axis and line for projection>
>>> table.plot('days', 'price') # doctest: +SKIP
<line graph with days as x-axis and line for price>