Wonderful! thank you!

On Fri, Oct 30, 2015 at 4:51 AM, Joshua Klein <mobiuskl...@gmail.com> wrote:

> My mistake, I thought you were using a DataFrame, not a Series. Instead do
> this
>
> colors = ['r' if row > 0 else 'b' for i, row in meantempanomaly.iteritems()]
> meantempanomaly.plot(kind='bar', color=colors)
>
> ​
>
> On Thu, Oct 29, 2015 at 5:43 AM, questions anon <questions.a...@gmail.com>
> wrote:
>
>> Thanks for taking the time to respond
>>
>> I am receiving the error:
>> AttributeError: 'Series' object has no attribute 'iterrow'
>>
>> I will look into this further.
>> thank you
>>
>>
>> On Thu, Oct 29, 2015 at 2:31 PM, Joshua Klein <mobiuskl...@gmail.com>
>> wrote:
>>
>>> The pandas plot function doesn’t take colors as it does ‘x’ or ‘y’, but
>>> it lets you pass color information just as you would with raw matplotlib
>>> code, which means you can pass it a sequence of colors which match the
>>> length of your sequence of drawn observations.
>>>
>>> # compute color codes using a ternary expression in a list comprehension 
>>> over the DataFrame
>>> colors = ['r' if row.anomaly > 0 else 'b' for i, row in 
>>> meantempanomaly.iterrows()]
>>> meantempanomaly.plot(kind='bar', color=colors)
>>>
>>> ​
>>>
>>> On Wed, Oct 28, 2015 at 9:54 PM, questions anon <
>>> questions.a...@gmail.com> wrote:
>>>
>>>> I have calculated annual temperature anomaly and I would like to plot
>>>> as a bar plot with all values positive make red and all values negative
>>>> make blue
>>>>
>>>> I am using pandas and the time series data in this example are called
>>>> 'anomaly'
>>>>
>>>> mybarplot=anomaly.plot(kind='bar')
>>>>
>>>> the data look like this:
>>>>
>>>> time
>>>> 2003-01-01   -0.370800
>>>> 2004-01-01   -0.498199
>>>> 2005-01-01    0.246118
>>>> 2006-01-01   -0.313321
>>>> 2007-01-01    0.585050
>>>> 2008-01-01   -0.227976
>>>> 2009-01-01    0.439337
>>>> 2010-01-01    0.135607
>>>> 2011-01-01    0.106105
>>>> 2012-01-01   -0.102002
>>>> Freq: AS-JAN, dtype: float64
>>>>
>>>> is there some simple way of writing:
>>>> meantempanomaly.plot(kind='bar', anomaly>0:'r', anomaly<0:'b' )
>>>>
>>>> Any feedback will be greatly appreciated
>>>>
>>>>
>>>>
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>>>>
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>>>>
>>>>
>>>
>>
>
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