MCPcopy
hub / github.com/matplotlib/matplotlib / plot

Method plot

lib/matplotlib/axes/_axes.py:1548–1799  ·  view source on GitHub ↗

Plot y versus x as lines and/or markers. Call signatures:: plot([x], y, [fmt], *, data=None, **kwargs) plot([x], y, [fmt], [x2], y2, [fmt2], ..., **kwargs) The coordinates of the points or line nodes are given by *x*, *y*. The optional par

(self, *args, scalex=True, scaley=True, data=None, **kwargs)

Source from the content-addressed store, hash-verified

1546 # _process_plot_var_args.
1547 @_docstring.interpd
1548 def plot(self, *args, scalex=True, scaley=True, data=None, **kwargs):
1549 """
1550 Plot y versus x as lines and/or markers.
1551
1552 Call signatures::
1553
1554 plot([x], y, [fmt], *, data=None, **kwargs)
1555 plot([x], y, [fmt], [x2], y2, [fmt2], ..., **kwargs)
1556
1557 The coordinates of the points or line nodes are given by *x*, *y*.
1558
1559 The optional parameter *fmt* is a convenient way for defining basic
1560 formatting like color, marker and linestyle. It's a shortcut string
1561 notation described in the *Notes* section below.
1562
1563 >>> plot(x, y) # plot x and y using default line style and color
1564 >>> plot(x, y, 'bo') # plot x and y using blue circle markers
1565 >>> plot(y) # plot y using x as index array 0..N-1
1566 >>> plot(y, 'r+') # ditto, but with red plusses
1567
1568 You can use `.Line2D` properties as keyword arguments for more
1569 control on the appearance. Line properties and *fmt* can be mixed.
1570 The following two calls yield identical results:
1571
1572 >>> plot(x, y, 'go--', linewidth=2, markersize=12)
1573 >>> plot(x, y, color='green', marker='o', linestyle='dashed',
1574 ... linewidth=2, markersize=12)
1575
1576 When conflicting with *fmt*, keyword arguments take precedence.
1577
1578
1579 **Plotting labelled data**
1580
1581 There's a convenient way for plotting objects with labelled data (i.e.
1582 data that can be accessed by index ``obj['y']``). Instead of giving
1583 the data in *x* and *y*, you can provide the object in the *data*
1584 parameter and just give the labels for *x* and *y*::
1585
1586 >>> plot('xlabel', 'ylabel', data=obj)
1587
1588 All indexable objects are supported. This could e.g. be a `dict`, a
1589 `pandas.DataFrame` or a structured numpy array.
1590
1591
1592 **Plotting multiple sets of data**
1593
1594 There are various ways to plot multiple sets of data.
1595
1596 - The most straight forward way is just to call `plot` multiple times.
1597 Example:
1598
1599 >>> plot(x1, y1, 'bo')
1600 >>> plot(x2, y2, 'go')
1601
1602 - If *x* and/or *y* are 2D arrays, a separate data set will be drawn
1603 for every column. If both *x* and *y* are 2D, they must have the
1604 same shape. If only one of them is 2D with shape (N, m) the other
1605 must have length N and will be used for every data set m.

Callers 15

test_AxesFunction · 0.95
loglogMethod · 0.95
semilogxMethod · 0.95
semilogyMethod · 0.95
xcorrMethod · 0.95
stepMethod · 0.95
stemMethod · 0.95
do_plotMethod · 0.95
ecdfMethod · 0.95
psdMethod · 0.95
csdMethod · 0.95
magnitude_spectrumMethod · 0.95

Calls 2

add_lineMethod · 0.80

Tested by 15

test_AxesFunction · 0.76
test_date_numpyxFunction · 0.36
test_date_not_emptyFunction · 0.36
test_axhlineFunction · 0.36
test_too_many_date_ticksFunction · 0.36
test_RRuleLocatorFunction · 0.36
test_DateFormatterFunction · 0.36
test_offset_changesFunction · 0.36