CODEWITHSUNDEEP
pythonpandas
Matthew
Matthew

Reputation: 67

How can I concatenate vertically multiple columns in pandas

I'm trying to add a new column to a dataframe, and fill up that column with multiple other columns in the dataframe concatenated together. How can I do this with the fact that this new column will have a different length than the rest of the columns in the dataframe?

For example:

df = pd.DataFrame([[1, 2], [1, 3], [4, 6]], columns=['A', 'B'])

I would want to create a column C in the dataframe that reads 1,1,4,2,3,6 (except vertically) 

print (df)
   A  B  C
0  1  2  1 
1  1  3  1
2  4  6  4
3        2
4        3
5        6

Upvotes: 2

Views: 10553

Answers (3)

Fedir Baronenko
Fedir Baronenko

Reputation: 23

If you have a long list of columns that you need to stack vertically - you can use the following syntax, rather than naming them all inside pd.concat():

pd.concat([df.loc[:, col] for col in df.columns], axis = 0, ignore_index=True)

Upvotes: 1

MaxU - stand with Ukraine
MaxU - stand with Ukraine

Reputation: 210962

Slightly modified Anton's solution (will work for any number of columns):

In [99]: df = pd.DataFrame(np.random.randint(0,10,(3,4)), columns=list('ABCD'))

In [100]: df
Out[100]:
   A  B  C  D
0  9  6  9  6
1  1  2  0  8
2  5  0  4  8

In [105]: pd.concat([df, df.T.stack().reset_index(name='new')['new']], axis=1)
Out[105]:
      A    B    C    D  new
0   9.0  6.0  9.0  6.0    9
1   1.0  2.0  0.0  8.0    1
2   5.0  0.0  4.0  8.0    5
3   NaN  NaN  NaN  NaN    6
4   NaN  NaN  NaN  NaN    2
5   NaN  NaN  NaN  NaN    0
6   NaN  NaN  NaN  NaN    9
7   NaN  NaN  NaN  NaN    0
8   NaN  NaN  NaN  NaN    4
9   NaN  NaN  NaN  NaN    6
10  NaN  NaN  NaN  NaN    8
11  NaN  NaN  NaN  NaN    8

Upvotes: 8

Anton vBR
Anton vBR

Reputation: 18914

How about this:

df1 = pd.DataFrame.from_dict({'A':[1,1,4],'B':[2,3,6]})

concatvalues = np.concatenate([df1.A.values,df1.B.values])

df2 = pd.concat([df1,pd.DataFrame(concatvalues)], ignore_index=True, axis=1)
df2.columns = np.append(df1.columns.values, "concat")

print(df2)

prints

    A   B   concat
0   1.0 2.0 1
1   1.0 3.0 1
2   4.0 6.0 4
3   NaN NaN 2
4   NaN NaN 3
5   NaN NaN 6

Upvotes: 2

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