data = dict(
    labels=['Bananas','Apples','Oranges','Watermelons','Grapes','Kiwis'],
    values=[4000,8000,3000,1600,1000,2500]
)
out = StdCharts.HBar(data)
HTML(out)

"""
Explanation: Horizontal Bar Charts

Best suited for categories comparison

Example 1: default options, "as is"
End of explanation
"""


StdCharts.save(out,'report1.png')

"""
Explanation: You can also save your chart with the save method:
End of explanation
"""


data = dict(
    labels=['Bananas','Apples','Oranges','Watermelons','Grapes','Kiwis'],
    values=[4000,8000,3000,1600,1000,2500]
)
out = StdCharts.HBar(
    data = data,
    width=600,
    color='#996666',
    title='Fruit prices ($)',
    source='Source: Local Market',
    fill='rgb(220, 75, 30)',
    values_sorted=True,
    paper='#f6f6f6',
    locale='en',
    font='Tahoma')
HTML(out)

StdCharts.save(out,'report2.png')

"""
Explanation: Example 2: sample options, sorting enabled
End of explanation
"""


data = dict(
    labels=[2010,2011,2012,2013,2014,2015,2016,2017],
    values=[4000,8000,3000,1600,1000,2500,4300,4200]
)
out = StdCharts.VBar(data=data,paper='#f3f3f3')
HTML(out)

StdCharts.save(out,'report3.png')

"""
Explanation: Vertical Bar Charts

Ideal for a small number of labels or a portion of time dependent values
Fixed width

Example 3: defaults
End of explanation
"""


data = dict(
    labels=['City ABCD','City EFGHM','City OPQRSTUV'],
    values=[200,100,500]
)
out = StdCharts.VBar(data=data,values_sorted=True,color="#446699",fill="#999999")
HTML(out)

StdCharts.save(out,'report4.png')

"""
Explanation: Example 4
End of explanation
"""


