Reputation: 1518
I want to append a Series to a DataFrame where Series's index matches DataFrame's columns using pd.concat
, but it gives me surprises:
df = pd.DataFrame(columns=['a', 'b'])
sr = pd.Series(data=[1,2], index=['a', 'b'], name=1)
pd.concat([df, sr], axis=0)
Out[11]:
a b 0
a NaN NaN 1.0
b NaN NaN 2.0
What I expected is of course:
df.append(sr)
Out[14]:
a b
1 1 2
It really surprises me that pd.concat
is not index-columns aware. So is it true that if I want to concat a Series as a new row to a DF, then I can only use df.append
instead?
Upvotes: 9
Views: 3024
Reputation: 11
"df.loc[1] = sr" will drop the column if it isn't in df
df = pd.DataFrame(columns = ['a','b'])
sr = pd.Series({'a':1,'b':2,'c':3})
df.loc[1] = sr
df will be like:
a b
1 1 2
Upvotes: 1
Reputation: 863301
Need DataFrame
from Series
by to_frame
and transpose:
a = pd.concat([df, sr.to_frame(1).T])
print (a)
a b
1 1 2
Detail:
print (sr.to_frame(1).T)
a b
1 1 2
Or use setting with enlargement:
df.loc[1] = sr
print (df)
a b
1 1 2
Upvotes: 11