Reputation: 1695
Lets say i Have 3 Pandas DF
DF1
Words Score
The Man 2
The Girl 4
Df2
Words2 Score2
The Boy 6
The Mother 7
Df3
Words3 Score3
The Son 3
The Daughter 4
Right now, I have them concatenated together so that it becomes 6 columns in one DF. That's all well and good but I was wondering, is there a pandas function to stack them vertically into TWO columns and change the headers?
So to make something like this?
Family Members Score
The Man 2
The Girl 4
The Boy 6
The Mother 7
The Son 3
The Daughter 4
everything I'm reading here http://pandas.pydata.org/pandas-docs/stable/merging.html seems to only have "horizontal" methods of joining DF!
Upvotes: 13
Views: 26024
Reputation: 60060
As long as you rename the columns so that they're the same in each dataframe, pd.concat()
should work fine:
# I read in your data as df1, df2 and df3 using:
# df1 = pd.read_clipboard(sep='\s\s+')
# Example dataframe:
Out[8]:
Words Score
0 The Man 2
1 The Girl 4
all_dfs = [df1, df2, df3]
# Give all df's common column names
for df in all_dfs:
df.columns = ['Family_Members', 'Score']
pd.concat(all_dfs).reset_index(drop=True)
Out[16]:
Family_Members Score
0 The Man 2
1 The Girl 4
2 The Boy 6
3 The Mother 7
4 The Son 3
5 The Daughter 4
Upvotes: 23