pandas.DataFrame.plot.bar#

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

Vertical bar plot.

A bar plot is a plot that presents categorical data withrectangular bars with lengths proportional to the values that theyrepresent. A bar plot shows comparisons among discrete categories. Oneaxis of the plot shows the specific categories being compared, and theother axis represents a measured value.

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 bar 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 bars forcolumna in green and bars 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

DataFrame.plot.barh

Horizontal bar plot.

DataFrame.plot

Make plots of a DataFrame.

matplotlib.pyplot.bar

Make a bar plot with matplotlib.

Examples

Basic plot.

>>>df=pd.DataFrame({'lab':['A','B','C'],'val':[10,30,20]})>>>ax=df.plot.bar(x='lab',y='val',rot=0)

Plot a whole dataframe to a bar plot. Each column is assigned adistinct color, and each row is nested in a group along thehorizontal axis.

>>>speed=[0.1,17.5,40,48,52,69,88]>>>lifespan=[2,8,70,1.5,25,12,28]>>>index=['snail','pig','elephant',...'rabbit','giraffe','coyote','horse']>>>df=pd.DataFrame({'speed':speed,...'lifespan':lifespan},index=index)>>>ax=df.plot.bar(rot=0)

Plot stacked bar charts for the DataFrame

>>>ax=df.plot.bar(stacked=True)

Instead of nesting, the figure can be split by column withsubplots=True. In this case, anumpy.ndarray ofmatplotlib.axes.Axes are returned.

>>>axes=df.plot.bar(rot=0,subplots=True)>>>axes[1].legend(loc=2)

If you don’t like the default colours, you can specify how you’dlike each column to be colored.

>>>axes=df.plot.bar(...rot=0,subplots=True,color={"speed":"red","lifespan":"green"}...)>>>axes[1].legend(loc=2)

Plot a single column.

>>>ax=df.plot.bar(y='speed',rot=0)

Plot only selected categories for the DataFrame.

>>>ax=df.plot.bar(x='lifespan',rot=0)