Create pandas dataframe from .txt file with data per row

Question

I have a .txt file with data ordered as below:

R11
R12
R13
R14
R15
R16
R17
R18
R19
R20

I need to iterate over rows in the textfile to fill the columns per row. In other words, the data need to be transformed to a pandas DataFrame looking like this:

| Column1 | Column2 | Column3 | Column4 | Column5 |
|---------|---------|---------|---------|---------|
| R11     | R12     | R13     | R14     | R15     |
| R16     | R17     | R18     | R19     | R20     |

My code starts with the following. After running, I now have a list of all rows called data, but how to get a pandas DataFrame as above as output?

with open('data.txt','r') as file:
    data = file.read().split('\n')

Answer 1

You can read text file using pd.read_csvand name column name

pd.DataFrame(pd.read_csv('data.txt', names=[0]).values.reshape(-1,5), columns = ['Column1','Column2', 'Column3', 'Column4', 'Column4'])

Answer 2

You are almost there! After reading the data in as a list you can split the list in chunk of 5s and then pass it in the pd.DataFrame()

with open('data.txt','r') as file:
    data = file.read().split('\n')

# split the list in chunks of 5s
chunks = [data[x:x+5] for x in range(0, len(data), 5)]

# pass the chunks in pd.DataFrame and specify the columns names of the OP:
pd.DataFrame(chunks, columns=["Column1", "Column2", "Column3", "Column4", "Column5"])

P.S. I assumed there was a typo in the last column as it appears to be named again Column4, but here I named it Column5. You can always name it Column4 if this is what you needed.