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 valuesas coordinates.

Parameters:

xlabel or position, optional

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

ylabel or position, optional

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

colorstr, 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. Forinstance [‘green’,’yellow’] each column’s line will be filled ingreen or yellow, alternatively. If there is only a single column tobe plotted, then only the first color from the color list will beused.

• A dict of the form {column namecolor}, so that each column will be

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

**kwargs

Additional keyword arguments are documented inDataFrame.plot().

Returns:

matplotlib.axes.Axes or np.ndarray of them

An ndarray is returned with onematplotlib.axes.Axesper column whensubplots=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()

The following example shows the populations for some animalsover 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 foreach 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 bothpopulations.

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