Python将CSV文件转换为数据框

Question

I have a large csv file containing data like:

2018-09, 100, A, 2018-10, 50, M, 2018-11, 69, H,....

and so on. (continuous stream without separate rows)

I would want to convert it into dataframe, which would look something like

Col1     Col2  Col3
2018-09  100   A
2018-10  50    M
2018-11  69    H

This is a simplified version of the actual data. Please advice what would be the best way to approach it.

Edit: To clarify, my csv file doesn't have separate lines for each row. All the data is on one row.

Answer 1

One solution is to split your single row into chunks via the csv module and this algorithm , then feed to pd.DataFrame constructor. Note your dataframe will be of dtype object , so you'll have to cast numeric series types explicitly afterwards.

from io import StringIO
import pandas as pd
import csv

x = StringIO("""2018-09, 100, A, 2018-10, 50, M, 2018-11, 69, H""")

# define chunking algorithm
def chunks(L, n):
    """Yield successive n-sized chunks from l."""
    for i in range(0, len(L), n):
        yield L[i:i + n]

# replace x with open('file.csv', 'r')
with x as fin:
    reader = csv.reader(fin, skipinitialspace=True)
    data = list(chunks(next(iter(reader)), 3))

# read dataframe
df = pd.DataFrame(data)

print(df)

         0    1  2
0  2018-09  100  A
1  2018-10   50  M
2  2018-11   69  H

Answer 2

data = pd.read_csv('tmp.txt', sep=',\s *', header=None).values
pd.DataFrame(data.reshape(-1, 3), columns=['Col1', 'Col2', 'Col3'])

returns

      Col1 Col2 Col3
0  2018-09  100    A
1  2018-10   50    M
2  2018-11   69    H