Markos writes:
[...]
>>> Please, any comments or tip?
>> data = pd.read_csv ('table.csv', sep = ',', skiprows = 1, decimal=b',',
>> skipinitialspace=True)
>>
> Thank you for the tip.
>
> I didn't realize that I could avoid formatting problems in the dataframe
> or array simply by using the read_
Em 22-09-2019 13:10, Piet van Oostrum escreveu:
Markos writes:
Hi,
I have a table.csv file with the following structure:
, Polyarene conc ,, mg L-1 ,,,
Spectrum, Py, Ace, Anth,
1, "0,456", "0,120", "0,168"
2, "0,456", "0,040", "0,280"
3, "0,152", "0,200", "0,280"
I open as dataframe
On 9/22/19 7:05 PM, Markos wrote:
>
> Em 22-09-2019 13:10, Piet van Oostrum escreveu:
>> Markos writes:
>>
>>> Hi,
>>>
>>> I have a table.csv file with the following structure:
>>>
>>> , Polyarene conc ,, mg L-1 ,,,
>>> Spectrum, Py, Ace, Anth,
>>> 1, "0,456", "0,120", "0,168"
>>> 2, "0,456",
Em 22-09-2019 13:10, Piet van Oostrum escreveu:
Markos writes:
Hi,
I have a table.csv file with the following structure:
, Polyarene conc ,, mg L-1 ,,,
Spectrum, Py, Ace, Anth,
1, "0,456", "0,120", "0,168"
2, "0,456", "0,040", "0,280"
3, "0,152", "0,200", "0,280"
I open as dataframe wi
Markos writes:
> Hi,
>
> I have a table.csv file with the following structure:
>
> , Polyarene conc ,, mg L-1 ,,,
> Spectrum, Py, Ace, Anth,
> 1, "0,456", "0,120", "0,168"
> 2, "0,456", "0,040", "0,280"
> 3, "0,152", "0,200", "0,280"
>
> I open as dataframe with the command:
>
> data = pd.rea
On 9/22/19, Albert-Jan Roskam wrote:
>
> Do you think it's a deliberate design choice that decimal and thousands
> where used here as params, and not a 'locale' param? It seems nice to be
> able to specify e.g. locale='dutch' and then all the right lc_numeric,
> lc_monetary, lc_time where used. Or
On 22Sep2019 07:39, Albert-Jan Roskam wrote:
On 22 Sep 2019 04:27, Cameron Simpson wrote:
On 21Sep2019 20:42, Markos wrote:
I have a table.csv file with the following structure:
, Polyarene conc ,, mg L-1 ,,,
Spectrum, Py, Ace, Anth,
1, "0,456", "0,120", "0,168"
2, "0,456", "0,040", "0,2
On 22 Sep 2019 04:27, Cameron Simpson wrote:
On 21Sep2019 20:42, Markos wrote:
>I have a table.csv file with the following structure:
>
>, Polyarene conc ,, mg L-1 ,,,
>Spectrum, Py, Ace, Anth,
>1, "0,456", "0,120", "0,168"
>2, "0,456", "0,040", "0,280"
>3, "0,152", "0,200", "0,280"
>
>I
On 21Sep2019 20:42, Markos wrote:
I have a table.csv file with the following structure:
, Polyarene conc ,, mg L-1 ,,,
Spectrum, Py, Ace, Anth,
1, "0,456", "0,120", "0,168"
2, "0,456", "0,040", "0,280"
3, "0,152", "0,200", "0,280"
I open as dataframe with the command:
data = pd.read_csv ('
On 2019-09-22 00:42, Markos wrote:
Hi,
I have a table.csv file with the following structure:
, Polyarene conc ,, mg L-1 ,,,
Spectrum, Py, Ace, Anth,
1, "0,456", "0,120", "0,168"
2, "0,456", "0,040", "0,280"
3, "0,152", "0,200", "0,280"
I open as dataframe with the command:
data = pd.read_
Hi,
I have a table.csv file with the following structure:
, Polyarene conc ,, mg L-1 ,,,
Spectrum, Py, Ace, Anth,
1, "0,456", "0,120", "0,168"
2, "0,456", "0,040", "0,280"
3, "0,152", "0,200", "0,280"
I open as dataframe with the command:
data = pd.read_csv ('table.csv', sep = ',', skiprow
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