Convert list to a 1-column panda dataframe

Question

I have a file with many lines. I am reading each line, splitting each word/number and storing in a list. After this, I am trying to convert this list into a 1-column panda Dataframe.

However after running my code I am getting only one row full of lists. What I need is 1 column with variable number of rows with some value.

Here is the code snippet I wrote:

for line1 in file:
    test_set=[]

    test_set.append(next(file).split())

    df1 = DataFrame({'test_set': [test_set]})

My output is something like:

              test_set
0  [[1, 0, 0, 0, 0, 0, 1, 1, 1, 0]]

But what I want is:

    test_set
0 1
1 0
2 0
3 0
4 0
5 0
6 1
7 1
8 1
9 0

Any suggestions what I'm doing wrong or how can I implement this? Thanks.

Input Data Sample snippet

id1 id2 id3 id4
0 1 0 1 
1 1 0 0

id10 id5 id6 id7
1 1 0 1 
1 0 0 1

.
.
.

Answer 1

You want this instead:

df1 = DataFrame({'test_set': test_set})

There is no need to wrap the list again in another list, by doing that you're effectively stating your df data is a list with a single element which is another list.

EDIT

looking at your input data you can just load it and then construct your df as a single column like so:

In [134]:
# load the data
import io
import pandas as pd
t="""id1 id2 id3 id4
0 1 0 1 
1 1 0 0"""
df = pd.read_csv(io.StringIO(t), sep='\s+')
df

Out[134]:
   id1  id2  id3  id4
0    0    1    0    1
1    1    1    0    0

Now transpose the df and perform a list comprehension, this will construct your lists and concatenate them using pd.concat:

In [142]:    
pd.concat([df.T[x] for x in df.T], ignore_index=True)

Out[142]:
0    0
1    1
2    0
3    1
4    1
5    1
6    0
7    0
dtype: int64