pandas.DataFrame.plot.scatter#

DataFrame.plot.scatter(x,y,s=None,c=None,**kwargs)[source]#

Create a scatter plot with varying marker point size and color.

The coordinates of each point are defined by two dataframe columns andfilled circles are used to represent each point. This kind of plot isuseful to see complex correlations between two variables. Points couldbe for instance natural 2D coordinates like longitude and latitude ina map or, in general, any pair of metrics that can be plotted againsteach other.

Parameters:

xint or str

The column name or column position to be used as horizontalcoordinates for each point.

yint or str

The column name or column position to be used as verticalcoordinates for each point.

sstr, scalar or array-like, optional

The size of each point. Possible values are:

• A string with the name of the column to be used for marker’s size.

• A single scalar so all points have the same size.

• A sequence of scalars, which will be used for each point’s sizerecursively. For instance, when passing [2,14] all points sizewill be either 2 or 14, alternatively.

cstr, int or array-like, optional

The color of each point. 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 RGBAcode, which will be used for each point’s color recursively. Forinstance [‘green’,’yellow’] all points will be filled in green oryellow, alternatively.

• A column name or position whose values will be used to color themarker points according to a colormap.

**kwargs

Keyword arguments to pass on toDataFrame.plot().

Returns:

matplotlib.axes.Axes or numpy.ndarray of them

See also

matplotlib.pyplot.scatter

Scatter plot using multiple input data formats.

Examples

Let’s see how to draw a scatter plot using coordinates from the valuesin a DataFrame’s columns.

>>>df=pd.DataFrame([[5.1,3.5,0],[4.9,3.0,0],[7.0,3.2,1],...[6.4,3.2,1],[5.9,3.0,2]],...columns=['length','width','species'])>>>ax1=df.plot.scatter(x='length',...y='width',...c='DarkBlue')

And now with the color determined by a column as well.

>>>ax2=df.plot.scatter(x='length',...y='width',...c='species',...colormap='viridis')