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anyone know pandas ? Don't understand error: NotImplementedError...

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  anyone know pandas ? Don't understand error: NotImplementedError... someone <newsboost@gmail.com> - 2013-04-17 23:08 +0200
    Re: anyone know pandas ? Don't understand error: NotImplementedError... Wayne Werner <wayne@waynewerner.com> - 2013-04-18 08:44 -0500
      Re: anyone know pandas ? Don't understand error: NotImplementedError... Neil Cerutti <neilc@norwich.edu> - 2013-04-18 14:07 +0000
        Re: anyone know pandas ? Don't understand error: NotImplementedError... someone <newsboost@gmail.com> - 2013-04-18 21:30 +0200
      Re: anyone know pandas ? Don't understand error: NotImplementedError... someone <newsboost@gmail.com> - 2013-04-18 20:28 +0200

#43778 — anyone know pandas ? Don't understand error: NotImplementedError...

Hi,

Here's my script (from 
http://brenda.moon.net.au/category/data-visualisation/:

============================
#!/usr/bin/python

import pandas
import datetime
import numpy

datesList = [datetime.date(2011,12,1), \
              datetime.date(2011,12,2), \
              datetime.date(2011,12,3), \
              datetime.date(2011,12,10)]

countsList = numpy.random.randn(len(datesList))
startData = datetime.datetime(2011,12,3)
endData = datetime.datetime(2011,12,8)

def convertListPairToTimeSeries(dList, cList):
     # my dateList had date objects, so convert back to datetime objects
     dListDT = [datetime.datetime.combine(x, datetime.time()) for x in 
dList]
     # found that NaN didn't work if the cList contained int data
     cListL = [float(x) for x in cList]
     #  create the index from the datestimes list
     indx = pandas.Index(dListDT)
     #  create the timeseries
     ts = pandas.Series(cListL, index=indx)
     # fill in missing days
     ts = ts.asfreq(pandas.datetools.DateOffset())
     return ts

print "\nOriginal datesList list:\n", datesList
tSeries = convertListPairToTimeSeries(datesList, countsList)
print "\nPandas timeseries:\n", tSeries

# use slicing to change length of data
tSeriesSlice = tSeries.ix[startData:endData]
print "\nPandas timeseries sliced between", startData.date(), \
   "and", endData.date(), ":\n", tSeriesSlice

# use truncate instead of slicing to change length of data
tSeriesTruncate = tSeries.truncate(before=startData, after=endData)
print "\nPandas timeseries truncated between", startData.date(), \
   "and", endData.date(), ":\n", tSeriesTruncate

# my data had lots of gaps that were actually 0 values, not missing data
# So I used this to fix the NaN outside the known outage
startOutage = datetime.datetime(2011,12,7)
endOutage = datetime.datetime(2011,12,8)
tsFilled = tSeries.fillna(0)
# set the known outage values back to NAN
tsFilled.ix[startOutage:endOutage] = numpy.NAN
print "\nPandas timeseries NaN reset to 0 outside known outage between", \
   startOutage.date(), "and", endOutage.date(), ":\n", tsFilled

print "\nPandas series.tail(1) and series.head(1) are handy for " +\
   "checking ends of list:\n", tsFilled.head(1), tsFilled.tail(1)
print

tsFilled.plot(); # <======  NotImplementedError...!!!
============================


If I run it, I get:
--------------------
...
...
..
2011-12-09    0.000000
2011-12-10    1.431665
Freq: <1 DateOffset>

Pandas series.tail(1) and series.head(1) are handy for checking ends of 
list:
2011-12-01   -0.969533
Freq: <1 DateOffset> 2011-12-10    1.431665
Freq: <1 DateOffset>

Traceback (most recent call last):
   File "./pandas_example.py", line 57, in <module>
     tsFilled.plot();
   File "/usr/lib/pymodules/python2.7/pandas/tools/plotting.py", line 
985, in plot_series
     plot_obj.generate()
   File "/usr/lib/pymodules/python2.7/pandas/tools/plotting.py", line 
376, in generate
     self._make_plot()
   File "/usr/lib/pymodules/python2.7/pandas/tools/plotting.py", line 
623, in _make_plot
     if self.use_index and self._use_dynamic_x():
   File "/usr/lib/pymodules/python2.7/pandas/tools/plotting.py", line 
619, in _use_dynamic_x
     return (freq is not None) and self._is_dynamic_freq(freq)
   File "/usr/lib/pymodules/python2.7/pandas/tools/plotting.py", line 
602, in _is_dynamic_freq
     freq = freq.rule_code
   File "/usr/lib/pymodules/python2.7/pandas/tseries/offsets.py", line 
214, in rule_code
     raise NotImplementedError
NotImplementedError
--------------------

Can anyone tell why this error appears and how to fix it?

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#43825

On Wed, 17 Apr 2013, someone wrote:

>  File "/usr/lib/pymodules/python2.7/pandas/tseries/offsets.py", line 214, in 
> rule_code
>    raise NotImplementedError
> NotImplementedError
> --------------------
>
> Can anyone tell why this error appears and how to fix it?

I don't know anything about pandas, but my recommendation?

   $ vim /usr/lib/pymodules/python2.7/pandas/tseries/offsets.py

(or nano or emacs - whatever editor you're comfortable with).

Go to line 214, and take a look-see at what you find. My guess is it will 
be something like:

def rule_code():
     raise NotImplementedError()



Which is terribly unhelpful.

HTH,
Wayne

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#43831

On 2013-04-18, Wayne Werner <wayne@waynewerner.com> wrote:
> On Wed, 17 Apr 2013, someone wrote:
>
>>  File "/usr/lib/pymodules/python2.7/pandas/tseries/offsets.py", line 214, in 
>> rule_code
>>    raise NotImplementedError
>> NotImplementedError
>> --------------------
>>
>> Can anyone tell why this error appears and how to fix it?
>
> I don't know anything about pandas, but my recommendation?
>
>    $ vim /usr/lib/pymodules/python2.7/pandas/tseries/offsets.py
>
> (or nano or emacs - whatever editor you're comfortable with).
>
> Go to line 214, and take a look-see at what you find. My guess is it will 
> be something like:
>
> def rule_code():
>      raise NotImplementedError()
>
> Which is terribly unhelpful.

It most likely means that the program is instantiating an
abstract base class when it should be using one of its subclasses
instead, e.g., BusinessDay, MonthEnd, MonthBegin,
BusinessMonthEnd, etc.

http://pandas.pydata.org/pandas-docs/dev/timeseries.html

-- 
Neil Cerutti

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#43856

On 04/18/2013 04:07 PM, Neil Cerutti wrote:
> On 2013-04-18, Wayne Werner <wayne@waynewerner.com> wrote:
>> On Wed, 17 Apr 2013, someone wrote:
....

>> Go to line 214, and take a look-see at what you find. My guess is it will
>> be something like:
>>
>> def rule_code():
>>       raise NotImplementedError()
>>
>> Which is terribly unhelpful.
>
> It most likely means that the program is instantiating an
> abstract base class when it should be using one of its subclasses
> instead, e.g., BusinessDay, MonthEnd, MonthBegin,
> BusinessMonthEnd, etc.
>
> http://pandas.pydata.org/pandas-docs/dev/timeseries.html

Hi Neil and Wayne,

Thank you very much for your suggestions... I now found out something: 
In the function:

def convertListPairToTimeSeries(dList, cList):
     ...
     ...
     #  create the timeseries
     ts = pandas.Series(cListL, index=indx)
     # fill in missing days
     #ts = ts.asfreq(pandas.datetools.DateOffset())
     return ts

I had to out-comment the last line before the return-statement (not sure 
what that line is supposed to do, in the first case)...

Now the program runs, but no plot is seen. Then I found out that I had 
to add:

import matplotlib.pyplot as plt

in the top of the program and add the following in the bottom of the 
program:

plt.show()


Final program:
==================
#!/usr/bin/python

import pandas
import datetime
import numpy
import ipdb
import matplotlib.pyplot as plt

datesList = [datetime.date(2011,12,1), \
              datetime.date(2011,12,2), \
              datetime.date(2011,12,3), \
              datetime.date(2011,12,10)]

countsList = numpy.random.randn(len(datesList))
startData = datetime.datetime(2011,12,3)
endData = datetime.datetime(2011,12,8)

def convertListPairToTimeSeries(dList, cList):
     # my dateList had date objects, so convert back to datetime objects
     dListDT = [datetime.datetime.combine(x, datetime.time()) for x in 
dList]
     # found that NaN didn't work if the cList contained int data
     cListL = [float(x) for x in cList]
     #  create the index from the datestimes list
     indx = pandas.Index(dListDT)
     #  create the timeseries
     ts = pandas.Series(cListL, index=indx)
     # fill in missing days
     #ts = ts.asfreq(pandas.datetools.DateOffset())
     return ts

print "\nOriginal datesList list:\n", datesList
tSeries = convertListPairToTimeSeries(datesList, countsList)
print "\nPandas timeseries:\n", tSeries

# use slicing to change length of data
tSeriesSlice = tSeries.ix[startData:endData]
print "\nPandas timeseries sliced between", startData.date(), \
   "and", endData.date(), ":\n", tSeriesSlice

# use truncate instead of slicing to change length of data
tSeriesTruncate = tSeries.truncate(before=startData, after=endData)
print "\nPandas timeseries truncated between", startData.date(), \
   "and", endData.date(), ":\n", tSeriesTruncate

# my data had lots of gaps that were actually 0 values, not missing data
# So I used this to fix the NaN outside the known outage
startOutage = datetime.datetime(2011,12,7)
endOutage = datetime.datetime(2011,12,8)
tsFilled = tSeries.fillna(0)
# set the known outage values back to NAN
tsFilled.ix[startOutage:endOutage] = numpy.NAN
print "\nPandas timeseries NaN reset to 0 outside known outage between", \
   startOutage.date(), "and", endOutage.date(), ":\n", tsFilled

print "\nPandas series.tail(1) and series.head(1) are handy for " +\
   "checking ends of list:\n", tsFilled.head(1), tsFilled.tail(1)
print
tsFilled.plot()
plt.show()
==================

This seem to work, although I don't fully understand it, as I'm pretty 
new to pandas...

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#43851

On 04/18/2013 03:44 PM, Wayne Werner wrote:
> On Wed, 17 Apr 2013, someone wrote:
>
>>  File "/usr/lib/pymodules/python2.7/pandas/tseries/offsets.py", line
>> 214, in rule_code
>>    raise NotImplementedError
>> NotImplementedError
>> --------------------
>>
>> Can anyone tell why this error appears and how to fix it?
>
> I don't know anything about pandas, but my recommendation?
>
>    $ vim /usr/lib/pymodules/python2.7/pandas/tseries/offsets.py
>
> (or nano or emacs - whatever editor you're comfortable with).
>
> Go to line 214, and take a look-see at what you find. My guess is it
> will be something like:
>
> def rule_code():
>      raise NotImplementedError()
>
>
>
> Which is terribly unhelpful.

Oh, yes - you're completely right:

    # line 211 (empty line)
     @property # line 212
     def rule_code(self): # line 213
         raise NotImplementedError # line 214
    # line 215 (empty line)

Below and above this "rule_code" is code belonging to some other 
functions... hmmm... I also tried to look in:

/usr/lib/pymodules/python2.7/pandas/tools/plotting.py

But I'm very unfamiliar with pandas, so everything looks "correct" to me 
- because I don't understand the data structure, I think I cannot see 
what is wrong...

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