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Loosing series names, when concatenating into DataFrame #2489

gbakalian opened this Issue Dec 11, 2012 · 1 comment


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gbakalian commented Dec 11, 2012

In the version 9.1, when we are concatenating pandas.Series, we would expect the columns name of the created DataFrame to be the ones of the Series which were concatenated together. Nevertheless the series' names are lost, and the columns are simply 0, 1, 2 ...

Error shown below:

Out[14]: '0.9.1rc1'

s1 = pd.TimeSeries(randn(5), index=pd.date_range('01-Jan-2013', periods=5, freq='D'), name='A')

s2 = pd.TimeSeries(randn(5), index=pd.date_range('01-Jan-2013', periods=5, freq='D'), name='B')

series = [s1, s2]

pd.concat(series, axis=1)

_32.columns = map(lambda s:, series)



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wesm Dec 12, 2012


I thought this worked. Marked as bug to investigate


wesm commented Dec 12, 2012

I thought this worked. Marked as bug to investigate

@ghost ghost assigned wesm Dec 14, 2012

@wesm wesm closed this in 90cddee Dec 14, 2012

yarikoptic added a commit to neurodebian/pandas that referenced this issue Dec 20, 2012

Merge commit 'v0.10.0b1-65-g6cadd6c' into debian
* commit 'v0.10.0b1-65-g6cadd6c':
  BUG: workaround numpy issue in 1.6.2 on certain distros
  BUG: use "for" as keyword to test against
  ENH: option names must valid, non-keyword python identifiers
  TST: option names must valid, non-keyword python identifiers
  BUG: make sure pd.options style access triggers warnings and callbacks as needed
  ENH: provide attribute style access to options via pd.options
  REF: rename option key "print" to "display"
  BUG: use Series name attributes for colnames in concat with axis=1. close pandas-dev#2489
  ENH: add max_cols as keyword in pandas-dev#2524
  BUG: allow users to set the max number of columns before per column info is hidden away pandas-dev#2524
  BUG: DataFrame.from_dict does not work with dict of sequence and orient=index pandas-dev#2496
  ENH: uses bool(crit(x)) rather then crit(x)
  DOC: add FAQ section on monkey-patching
  BUG: diff should cast n to int pandas-dev#2523
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