python - Uppercase precedence in pandas column name assignment -


is there reason why column name assignment in pandas favours uppercase on lower case?

example:

dframe = dataframe({'city':['alma','brian head', 'fox park'],                     'altitude':[3158,3000,2762]})

returns dataframe columns in order altitude, city.

whereas:

dframe = dataframe({'city':['alma','brian head', 'fox park'],                     'altitude':[3158,3000,2762]})

returns dataframe columns in order city,altitude.

is pandas specific or general python behaviour?

you didn't ask this, i'm assuming there implied question how preserve original ordering? if so, here 3 ways:

1) same basic dictionary constructor, wrap in collections.ordereddict (thanks @shx2 correction):

from collections import ordereddict df1 = pd.dataframe( ordereddict([ ('city',['alma','brian head', 'fox park']),                                   ('altitude',[3158,3000,2762]) ]))

2) non-dictionary constructor specifiy data array , column names separately, however, requires row-centric entry rather column-centric dictionary constructor:

lst = [['alma','brian head','fox park'],        [3158,3000,2762]] df2 = pd.dataframe( map(list, zip(*lst)),                     columns = ['city','altitude'] )

3) simplest way specify order after create dataframe (thanks @edchum catching error in original post):

df3 = df[['city','altitude']]

test results same three:

in [149]: all(df1==df2) out[149]: true  in [150]: all(df1==df3) out[150]: true

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