Hi,
Are there any routines to fill in the gaps in an array. The simplest
would be by carrying the last known observation forward.
0,0,10,8,0,0,7,0
0,0,10,8,8,8,7,7
Or by somehow interpolating the missing values based on the previous
and next known observations (mean).
Thanks.
__
On 2/11/09, Robert Kern wrote:
> On Wed, Feb 11, 2009 at 23:24, A B wrote:
>> Hi,
>>
>> I have the following data structure:
>>
>> col1 | col2 | col3
>>
>> 20080101|key1|4
>> 20080201|key1|6
>> 20080301|key1|5
>> 20080301|key2|3.4
ol1'])), dtype=dict(names=['dates',
> 'key1', 'key2'] , types=[long, float, float]))
>
> for i, (date, items) in enumerate(groupby(a, lambda item: item
> ['col1'])):
> data[i][dates] = date
> for col1, col2, col3 in items:
>
Hi,
I have the following data structure:
col1 | col2 | col3
20080101|key1|4
20080201|key1|6
20080301|key1|5
20080301|key2|3.4
20080601|key2|5.6
For each key in the second column, I would like to create an array
where for all unique values in the first column, there will be either
a value or zer
On Wed, Feb 11, 2009 at 6:27 PM, A B wrote:
> On Tue, Feb 10, 2009 at 9:52 PM, Brent Pedersen wrote:
>> On Tue, Feb 10, 2009 at 9:40 PM, A B wrote:
>>> Hi,
>>>
>>> How do I write a loadtxt command to read in the following file and
>>> store
On Tue, Feb 10, 2009 at 9:52 PM, Brent Pedersen wrote:
> On Tue, Feb 10, 2009 at 9:40 PM, A B wrote:
>> Hi,
>>
>> How do I write a loadtxt command to read in the following file and
>> store each data point as the appropriate data type:
>>
>> 12|h|34.5|4
Hi,
How do I write a loadtxt command to read in the following file and
store each data point as the appropriate data type:
12|h|34.5|44.5
14552|bbb|34.5|42.5
Do the strings have to be read in separately from the numbers?
Why would anyone use 'S10' instead of 'string'?
dt = {'names': ('gender',
