pandas.Series.plot.barh   Series.plot.barh(x=None, y=None, **kwargs)[source]
 
Make a horizontal bar plot. A horizontal bar plot is a plot that presents quantitative data with rectangular bars with lengths proportional to the values that they represent. A bar plot shows comparisons among discrete categories. One axis of the plot shows the specific categories being compared, and the other axis represents a measured value.  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 bar 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 bars for column a in green and bars 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  DataFrame.plot.bar

Vertical bar plot.  DataFrame.plot

Make plots of DataFrame using matplotlib.  matplotlib.axes.Axes.bar

Plot a vertical bar plot using matplotlib.    Examples Basic example 
>>> df = pd.DataFrame({'lab': ['A', 'B', 'C'], 'val': [10, 30, 20]})
>>> ax = df.plot.barh(x='lab', y='val')
     Plot a whole DataFrame to a horizontal bar plot 
>>> 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.barh()
     Plot stacked barh charts for the DataFrame 
>>> ax = df.plot.barh(stacked=True)
     We can specify colors for each column 
>>> ax = df.plot.barh(color={"speed": "red", "lifespan": "green"})
     Plot a column of the DataFrame to a horizontal bar plot 
>>> 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.barh(y='speed')
     Plot DataFrame versus the desired column 
>>> 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.barh(x='lifespan')