csv_file = open('new.csv',newline='')
reader = csv.reader(csv_file)
header = next(reader)		# 读取header
print(header)
...
csv_file.close()

# 遍历行数据
for row in reader:		# 此时将不包含header，row是list
    print(reader.line_num,row)	# 打印行号和行数据（行号从1开始，header是1）
    print(','.join(row))	# 将row中的元素用','连起来

# 等价于用列表推导式读取行数据
[print(row) for row in reader]

# 遍历所有行，只输出符合条件的行
for index,row in enumerate(reader):
    if index in [2,3]:
        print(row)

# 切片法，但是数据较大的话不推荐
rows = list(reader)
print(rows[1])

# 使用列表推导式解析列数据，打印第二列的数据
col = [row[2] for row in reader]
print(col)

# 打印数据区域第一行第二列的数据
rows = list(reader)
print(rows[0][1])

csv_file = open('new.csv',newline='')
reader = csv.DictReader(csv_file)
header = reader.fieldnames	# 读取header
print(header)
...
csv_file.close()

# 不带key
for row in reader:	# 此时row是dict
    print(row['name'],row['age'])

# 带key
for row in reader:
    print(row)

# 遍历所有行，只输出符合条件的行
for index,row in enumerate(reader):
    if index in [2,3]:
        print(row)

# 切片法，但是数据较大的话不推荐
rows = list(reader)
print(rows[1])

for row in reader:
    print(row['name'])

# 打印数据区域第一行的name数据
rows = list(reader)
print(rows[0]['name'])

# 写入行数据
csv_file = open('new.csv','w',newline='')
writer = csv.writer(csv_file)
writer.writerow(['name','age','sex','score'])
writer.writerow(['Coco',20,'male',90])
writer.writerows([row1,row2])	# 多行写入数据
csv_file.close()

csv_file = open('new.csv','w',newline='')
fieldnames = ['name','age','sex','score']	# header
writer = csv.DictWriter(csv_file,fieldnames=fieldnames)
writer.writeheader()
writer.writerow({'name':'Bob','age':20,'sex':'male','score':90})
writer.writerows([{'name':'Tom','age':21,'sex':'male','score':95},{'name':'Lucy','age':19,'sex':'female','score':89}])