matplotlib-users Mailing List for matplotlib

Wonderful! thank you!
On Fri, Oct 30, 2015 at 4:51 AM, Joshua Klein <mob...@gm...> 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 <que...@gm...>
> 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 <mob...@gm...>
>> 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 <
>>> que...@gm...> 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年01月01日 -0.370800
>>>> 2004年01月01日 -0.498199
>>>> 2005年01月01日 0.246118
>>>> 2006年01月01日 -0.313321
>>>> 2007年01月01日 0.585050
>>>> 2008年01月01日 -0.227976
>>>> 2009年01月01日 0.439337
>>>> 2010年01月01日 0.135607
>>>> 2011年01月01日 0.106105
>>>> 2012年01月01日 -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
>>>>
>>>>
>>>>
>>>> ------------------------------------------------------------------------------
>>>>
>>>> _______________________________________________
>>>> Matplotlib-users mailing list
>>>> Mat...@li...
>>>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>>>>
>>>>
>>>
>>
>

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 <que...@gm...>
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 <mob...@gm...>
> 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 <que...@gm...
>> > 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年01月01日 -0.370800
>>> 2004年01月01日 -0.498199
>>> 2005年01月01日 0.246118
>>> 2006年01月01日 -0.313321
>>> 2007年01月01日 0.585050
>>> 2008年01月01日 -0.227976
>>> 2009年01月01日 0.439337
>>> 2010年01月01日 0.135607
>>> 2011年01月01日 0.106105
>>> 2012年01月01日 -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
>>>
>>>
>>>
>>> ------------------------------------------------------------------------------
>>>
>>> _______________________________________________
>>> Matplotlib-users mailing list
>>> Mat...@li...
>>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>>>
>>>
>>
>

An axes can only belong to one figure at a time. And I also don't think I
have ever seen anyone try and transfer an axes from one figure to another.
You *might* have luck with inset locators from axes_grid:
http://matplotlib.org/examples/axes_grid/inset_locator_demo.html
Cheers!
Ben Root
On Thu, Oct 29, 2015 at 12:07 PM, Alejandro Weinstein <
ale...@gm...> wrote:
> Hi,
>
> I have a previously draw plot that I want to place as an inset in
> another figure. I've tried with passing the previously drawn axes as
> the `axes` parameter to the `add_axes` method of the figure, and also
> tried using the `set_axes` method of the new axes, without success: I
> get the new inset axes, but without the previously drawn plot, in both
> cases.
>
> The following code shows both approaches:
>
> # Passing the inset axes as a parameter to add_axes
> fig_in, ax_in = plt.subplots()
> ax_in.plot([1,2,3])
> fig, ax = plt.subplots()
> ax.plot([1,2,1])
> fig.add_axes([0.72, 0.72, 0.16, 0.16], axes=ax_in)
>
> # Using set_axes
> fig_in, ax_in = plt.subplots()
> ax_in.plot([1,2,3])
> fig, ax = plt.subplots()
> ax.plot([1,2,1])
> ax_new = fig.add_axes([0.72, 0.72, 0.16, 0.16])
> ax_new.set_axes(ax_in)
>
> Any help with this will be appreciated.
>
> Regards,
> Alejandro
>
>
> ------------------------------------------------------------------------------
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>

Hi,
I have a previously draw plot that I want to place as an inset in
another figure. I've tried with passing the previously drawn axes as
the `axes` parameter to the `add_axes` method of the figure, and also
tried using the `set_axes` method of the new axes, without success: I
get the new inset axes, but without the previously drawn plot, in both
cases.
The following code shows both approaches:
 # Passing the inset axes as a parameter to add_axes
 fig_in, ax_in = plt.subplots()
 ax_in.plot([1,2,3])
 fig, ax = plt.subplots()
 ax.plot([1,2,1])
 fig.add_axes([0.72, 0.72, 0.16, 0.16], axes=ax_in)
 # Using set_axes
 fig_in, ax_in = plt.subplots()
 ax_in.plot([1,2,3])
 fig, ax = plt.subplots()
 ax.plot([1,2,1])
 ax_new = fig.add_axes([0.72, 0.72, 0.16, 0.16])
 ax_new.set_axes(ax_in)
Any help with this will be appreciated.
Regards,
Alejandro

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 <mob...@gm...> 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 <que...@gm...>
> 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年01月01日 -0.370800
>> 2004年01月01日 -0.498199
>> 2005年01月01日 0.246118
>> 2006年01月01日 -0.313321
>> 2007年01月01日 0.585050
>> 2008年01月01日 -0.227976
>> 2009年01月01日 0.439337
>> 2010年01月01日 0.135607
>> 2011年01月01日 0.106105
>> 2012年01月01日 -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
>>
>>
>>
>> ------------------------------------------------------------------------------
>>
>> _______________________________________________
>> Matplotlib-users mailing list
>> Mat...@li...
>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>>
>>
>

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 <que...@gm...>
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年01月01日 -0.370800
> 2004年01月01日 -0.498199
> 2005年01月01日 0.246118
> 2006年01月01日 -0.313321
> 2007年01月01日 0.585050
> 2008年01月01日 -0.227976
> 2009年01月01日 0.439337
> 2010年01月01日 0.135607
> 2011年01月01日 0.106105
> 2012年01月01日 -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
>
>
>
> ------------------------------------------------------------------------------
>
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>
>

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年01月01日 -0.370800
2004年01月01日 -0.498199
2005年01月01日 0.246118
2006年01月01日 -0.313321
2007年01月01日 0.585050
2008年01月01日 -0.227976
2009年01月01日 0.439337
2010年01月01日 0.135607
2011年01月01日 0.106105
2012年01月01日 -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