> On 18 Feb 2015, at 10:35, Andrea Ferretti <[hidden email]> wrote:
>
> For an example of what I am talking about, see
>
> http://pandas.pydata.org/pandas-docs/version/0.15.2/io.html#csv-text-files
>
> I agree that this is definitely too much options, but it gets the job
> done for quick and dirty exploration.
>
> The fact is that working with a dump of table on your db, whose
> content you know, requires different tools than exploring the latest
> opendata that your local municipality has put online, using yet
> another messy format.
>
> Enterprise programmers deal more often with the former, data
> scientists with the latter, and I think there is room for both kind of
> tools
>
> 2015-02-18 10:26 GMT+01:00 Andrea Ferretti <[hidden email]>:
>> Thank you Sven. I think this should be emphasized and prominent on the
>> home page*. Still, libraries such as pandas are even more lenient,
>> doing things such as:
>>
>> - autodetecting which fields are numeric in CSV files
>> - allowing to fill missing data based on statistics (for instance, you
>> can say: where the field `age` is missing, use the average age)
>>
>> Probably there is room for something built on top of Neo
>>
>>
>> * by the way, I suggest that the documentation on Neo could benefit
>> from a reorganization. Right now, the first topic  on the NeoJSON
>> paper introduces JSON itself. I would argue that everyone that tries
>> to use the library knows what JSON is already. Still, there is no
>> example of how to read JSON from a file in the whole document.
>>
>> 2015-02-18 10:12 GMT+01:00 Sven Van Caekenberghe <[hidden email]>:
>>>
>>>> On 18 Feb 2015, at 09:52, Andrea Ferretti <[hidden email]> wrote:
>>>>
>>>> Also, these tasks
>>>> often involve consuming data from various sources, such as CSV and
>>>> Json files. NeoCSV and NeoJSON are still a little too rigid for the
>>>> task - libraries like pandas allow to just feed a csv file and try to
>>>> make head or tails of the content without having to define too much of
>>>> a schema beforehand
>>>
>>> Both NeoCSV and NeoJSON can operate in two ways, (1) without the definition of any schema's or (2) with the definition of schema's and mappings. The quick and dirty explore style is most certainly possible.
>>>
>>> 'my-data.csv' asFileReference readStreamDo: [ :in | (NeoCSVReader on: in) upToEnd ].
>>>
>>>  => an array of arrays
>>>
>>> 'my-data.json' asFileReference readStreamDo: [ :in | (NeoJSONReader on: in) next ].
>>>
>>>  => objects structured using dictionaries and arrays
>>>
>>> Sven
>>>
>>>
>