CODEWITHSUNDEEP
pythonpandas
Ayush
Ayush

Reputation: 95

How to merge multiple column of same data frame

How to merge multiple column values into one column of same data frame and get new column with unique values.

 Column1  Column2  Column3  Column4  Column5
 0    a        1        2        3        4
 1    a        3        4        5
 2    b        6        7        8
 3    c        7        7

Output:

Column A
a
a
b
c
1
3
6
7
2
4
5
8

Upvotes: 2

Views: 160

Answers (2)

b2002
b2002

Reputation: 914

Here is another way to do it if you are ok using numpy. This will handle either nans or empty strings in the original dataframe and is a bit faster than unstack or melt.

import pandas as pd
import numpy as np

df = pd.DataFrame({'Column1': ['a', 'a', 'b', 'c'],
                   'Column2': [1, 3, 6, 7],
                   'Column3': [2, 4, 7, 7],
                   'Column4': [3, 5, 8, np.nan],
                   'Column5': [4, '', '', np.nan]})

u = pd.unique(df.values.flatten(order='F'))
u = u[np.where(~np.isin(u, ['']) & ~pd.isnull(u))[0]]
df1 = pd.DataFrame(u, columns=['A'])

print(df1)

    A
0   a
1   b
2   c
3   1
4   3
5   6
6   7
7   2
8   4
9   5
10  8

Upvotes: 0

jezrael
jezrael

Reputation: 863501

Use unstack or melt for reshape, remove missinf values by dropna and duplicates by drop_duplicates:

df1 = df.unstack().dropna().drop_duplicates().reset_index(drop=True).to_frame('A')

df1 = df.melt(value_name='A')[['A']].dropna().drop_duplicates().reset_index(drop=True)
print (df1)
    A
0   a
1   b
2   c
3   1
4   3
5   6
6   7
7   2
8   4
9   5
10  8

Upvotes: 3

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