pandas.DataFrame.plot.line

DataFrame.plot.line(x=None, y=None, **kwargs)[source]

Plot Series or DataFrame as lines.

This function is useful to plot lines using DataFrame’s values as coordinates.

Parameters

x:label or position, optional

Allows plotting of one column versus another. If not specified, the index of the DataFrame is used.

y:label or position, optional

Allows plotting of one column versus another. If not specified, all numerical columns are used.

color:str, array-like, or dict, optional

The color for each of the DataFrame’s columns. Possible values are:

• A single color string referred to by name, RGB or RGBA code,

  for instance ‘red’ or ‘#a98d19’.

• A sequence of color strings referred to by name, RGB or RGBA

  code, which will be used for each column recursively. For instance [‘green’,’yellow’] each column’s line will be filled in green or yellow, alternatively. If there is only a single column to be plotted, then only the first color from the color list will be used.

• A dict of the form {column name:color}, so that each column will be

  colored accordingly. For example, if your columns are called a and b, then passing {‘a’: ‘green’, ‘b’: ‘red’} will color lines for column a in green and lines for column b in red.

New in version 1.1.0.

**kwargs

Additional keyword arguments are documented in DataFrame.plot().

Returns

matplotlib.axes.Axes or np.ndarray of them

An ndarray is returned with one matplotlib.axes.Axes per column when subplots=True.

See also

matplotlib.pyplot.plot

Plot y versus x as lines and/or markers.

Examples

>>> s = pd.Series([1, 3, 2])
>>> s.plot.line()
<AxesSubplot: ylabel='Density'>

The following example shows the populations for some animals over the years.

>>> df = pd.DataFrame({
...    'pig': [20, 18, 489, 675, 1776],
...    'horse': [4, 25, 281, 600, 1900]
...    }, index=[1990, 1997, 2003, 2009, 2014])
>>> lines = df.plot.line()

An example with subplots, so an array of axes is returned.

>>> axes = df.plot.line(subplots=True)
>>> type(axes)
<class 'numpy.ndarray'>

Let’s repeat the same example, but specifying colors for each column (in this case, for each animal).

>>> axes = df.plot.line(
...     subplots=True, color={"pig": "pink", "horse": "#742802"}
... )

The following example shows the relationship between both populations.

>>> lines = df.plot.line(x='pig', y='horse')