I came looking for this thread to point out that this bug is still affecting users: https://stackoverflow.com/q/66389166/4183191

If this bug has been fixed in the repo, perhaps a bugfix release is in order?

Best,
T.

Posted to the bug tracker mailing list by Pascal:

Dear all,

I started using extensively Python and Pandas around one year ago.  Have a look f.i. at
https://pandas.pydata.org/pandas-docs/stable/user_guide/style.html

MultiIndex. Slices. Ability to interact with Excell and LaTeX. To
solve all annoyances with CSV and encoding. Not to mention seaborn

So yes, I fixed dataframe; but quite frankly I stopped using it.
Pandas is lightyear ahead of dataframe in so many aspects.

If someone wish to make a release , I will welcome him / her as the new maintainer.

Regards

Hello,
the purpose of a second line with all chars is to indicate columns type. This line was silently removed.

I changed the behaviour: the second line is removed if
1) all fields are char
and
2) all fields are valid argument for the "cast" function

I'll release shortly a new version

Regards

Pascal

With the attached csv files.

For dataframe with all characters

'name','mask','weapon'
'Leonardo','blue','ninjatos'
'Donatello','purple','bo'
'Michelangelo','orange','nunchaku'
'Raphael','red','sai'

pkg load dataframe
dataframe('dataframe.csv')

ans = dataframe with 3 rows and 3 columns
Src: dataframe.csv
_1         name   mask   weapon
Nr         char   char     char
 1    Donatello purple       bo
 2 Michelangelo orange nunchaku
 3      Raphael    red      sai

The second line is ignored. For a csv file with similar content but a numeric column,

'name','num','weapon'
'Leonardo',12,'ninjatos'
'Donatello',34,'bo'
'Michelangelo',56,'nunchaku'
'Raphael',78,'sai'

loading it yields 4 rows correctly

dataframe('dataframe_with_number.csv')
ans = dataframe with 4 rows and 3 columns
Src: dataframe_with_number.csv
_1         name    num   weapon
Nr         char double     char
 1     Leonardo     12 ninjatos
 2    Donatello     34       bo
 3 Michelangelo     56 nunchaku
 4      Raphael     78      sai