如何在不使用熊猫的情况下将 append 列从 csv 文件到另一个 csv 文件？

Question

I want to append a column from 'b.csv' file and put it into 'a.csv' file but it only add a letter and not the whole string. I tried searching in google but there's no answer. I want to put the column under the headline "number". This is my code:

f = open('b.csv')
default_text = f.read()
with open('a.csv', 'r') as read_obj, \
        open('output_1.csv', 'w', newline='') as write_obj:
    csv_reader = reader(read_obj)
    csv_writer = writer(write_obj)
    for row in csv_reader:
        row.append(default_text[8])
        csv_writer.writerow(row)

This is the info in 'a.csv'

name,age,course,school,number
Leo,18,BSIT,STI
Rommel,23,BSIT,STI
Gaby,33,BSIT,STI
Ranel,31,BSIT,STI

This is the info in 'b.csv'

1212121
1094534
1345684
1093245

Answer 1

You can just concat rows read from both CSV file and pass it immediately to writer:

import csv
from operator import concat

with open(r'a.csv') as f1, \
        open(r'b.csv') as f2, \
        open(r'output_1.csv', 'w', newline='') as out:
    f1_reader = csv.reader(f1)
    f2_reader = csv.reader(f2)
    writer = csv.writer(out)
    writer.writerow(next(f1_reader))  # write column names
    writer.writerows(map(concat, f1_reader, f2_reader))

So we initialize csv.reader() for both CSV files and csv.writer() for output. As first file ( a.csv ) contains column names, we read it using next() and pass to .writerow() to write them into output without any modifications. Then using map() we can iterate over both readers simultaneously applyingoperator.concat() which concatenate rows returned from both reader. We can pass it directly to .writerows() and let it consume generator returned by map() .

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Answer 2

If only pandas cannot be used, then it's convenient to use Table helper from convtools library ( github ).

from convtools.contrib.tables import Table
from convtools import conversion as c

(
    Table.from_csv("tmp/1.csv", header=True)
    # this step wouldn't be needed if your first file wouldn't have missing
    # "number" column
    .drop("number")
    .zip(Table.from_csv("tmp/2.csv", header=["number"]))
    .into_csv("tmp/results.csv")
)