Pandas get data from a list of column names

Question

I have a pandas dataframe: df and list of column names: columns like so:

df = pd.DataFrame({
    'A': ['b','b','c','d'],
    'C': ['b1','b2','c1','d2'],
    'B': list(range(4))})

columns = ['A','B']

Now I want to get all the data from these columns of the dataframe in one single series like so:

b
0
b
1
c
2
d
4

This is what I tried:

srs = pd.Series()
srs.append(df[column].values for column in columns)

But it is throwing this error:

TypeError: cannot concatenate object of type '<class 'generator'>'; only Series and DataFrame objs are valid

How can I fix this issue?

Could you add a small input/output example?

Dani Mesejo
– Dani Mesejo

2020-12-11 13:25:43 +00:00
Commented Dec 11, 2020 at 13:25 — Dani Mesejo
– Dani Mesejo, Commented Dec 11, 2020 at 13:25
@DaniMesejo added sample input/output

Ankur
– Ankur

2020-12-11 13:31:21 +00:00
Commented Dec 11, 2020 at 13:31 — Ankur
– Ankur, Commented Dec 11, 2020 at 13:31

jezrael · Accepted Answer · 2020-12-11 13:33:52Z

3

I think you can use numpy.ravel:

srs = pd.Series(np.ravel(df[columns]))
print (srs)
0    b
1    0
2    b
3    1
4    c
5    2
6    d
7    3
dtype: object

Or DataFrame.stack with Series.reset_index and drop=True:

srs = df[columns].stack().reset_index(drop=True)

If order should be changed is possible use DataFrame.melt:

srs = df[columns].melt()['value']
print (srs)
0    b
1    b
2    c
3    d
4    0
5    1
6    2
7    3
Name: value, dtype: object

edited Dec 11, 2020 at 13:33

answered Dec 11, 2020 at 13:23

jezrael

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Comments

Dani Mesejo · Accepted Answer · 2020-12-11 13:35:44Z

1

You could do:

from itertools import chain

import pandas as pd
df = pd.DataFrame({
    'A': ['b','b','c','d'],
    'C': ['b1','b2','c1','d2'],
    'B': list(range(4))})

columns = ['A','B']

res = pd.Series(chain.from_iterable(df[columns].to_numpy()))
print(res)

Output

0    b
1    0
2    b
3    1
4    c
5    2
6    d
7    3
dtype: object

answered Dec 11, 2020 at 13:35

Dani Mesejo

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