使用python在csv中每一行的末尾附加字典或值列表

Question

I want to append a list of values at the end of each row of a csv file except the header.

I have tried following code but it deletes all the rows from csv file and does not appends any value to the csv file.

import tensorflow
from fer.fer import FER
import cv2
from os import listdir
from os.path import isfile, join
import numpy
import csv



f1 =     open("C:/Yasir/Thesis/4/FaceDetectionLatest/bin/Debug/Data/demoScoringData9.csv",   "a+")
reader = csv.reader(f1)
images = numpy.empty(len(onlyfiles), dtype=object)
for n in range(0, len(onlyfiles)):
    images[n] = cv2.imread( join(mypath,onlyfiles[n]) )
    # cv2.imshow(join(mypath,onlyfiles[n]),0)
    img = cv2.imread( join(mypath,onlyfiles[n]) )
    detector = FER()
    emotion = detector.detect_emotions(img)
    dict = emotion[0]
    emoList = dict['emotions']
    dict_writer = csv.DictWriter(f1, emoList)
    dict_writer.writerow(emoList)

I want to append the following values to a csv file which is already created. I mean the dict values should be appended to each row of csv except the header values like below.

{'angry': 0.15, 'disgust': 0.0, 'fear': 0.05, 'happy': 0.06, 'sad': 0.24, 'surprise': 0.02, 'neutral': 0.49}

I am also sharing the screenshot of my csv file screenshot

Answer 1

Here's a basic example of appending columns to an existing CSV:

data.csv (original)

col1,col2,col3
1,2,3
4,5,6
7,8,9

test.py

import csv

with open('data.csv',newline='') as fin:
    r = csv.DictReader(fin)
    lines = list(r)

with open('data.csv','w',newline='') as fout:
    # Create writer with existing column headers plus new column headers
    w = csv.DictWriter(fout,fieldnames=r.fieldnames + 'angry disgust fear happy sad surprise neutral'.split())
    w.writeheader()

    for line in lines:
        emolist = {'angry': 0.15, 'disgust': 0.0, 'fear': 0.05, 'happy': 0.06, 'sad': 0.24, 'surprise': 0.02, 'neutral': 0.49}
        line.update(emolist)
        w.writerow(line)

data.csv (final)

col1,col2,col3,angry,disgust,fear,happy,sad,surprise,neutral
1,2,3,0.15,0.0,0.05,0.06,0.24,0.02,0.49
4,5,6,0.15,0.0,0.05,0.06,0.24,0.02,0.49
7,8,9,0.15,0.0,0.05,0.06,0.24,0.02,0.49