writer = csv.writer(file ,delimiter=',') writer.writerow(list) 1. 2. 3. 4. 5. 6. 结果都在同一行: abc,def,ghi 若是用writer.writerows()方法,结果每个字母都被逗号隔开: a,b,c d,e,f g,h,i 若是想让列表写入csv中按行切出现被逗号分隔的情况,列表应是: [[‘abc’], [‘def’], ...
1 Write list of list to csv in python 1 Writing multiple lists to csv Python 0 Python: write multiple lists to multiple rows in csv 2 Python: Write list of lists to CSV 1 Write multiple rows from several lists into a CSV 2 How to write multiple lists into csv file python3 ...
CSV是一种常用的文件格式,用于存储表格数据,每行数据由逗号分隔,每个字段可以包含文本、数字或日期等类型的数据。 在Python中,可以使用csv模块来实现将列表写入CSV文件的操作。下面是一个示例代码: 代码语言:txt 复制 import csv def write_list_to_csv(data, filename): with open(filename, 'w', newline='...
import csv def save_data(my_list): file_name = 'months.csv' with open(file_name, 'w') as myfile: wr = csv.writer(myfile, quoting=csv.QUOTE_NONE, delimiter=' ') for row in my_list: wr.writerow(map(str, row)) #example: save_data([["March", 1.2, 1.5], ["July", 2.3, ...
在Python中,如果需要将列表数据写入多个CSV文件,并且希望优化这个过程,可以按照以下步骤进行操作: 首先,导入所需的模块:import csv import os 定义一个函数,用于将列表数据写入CSV文件:def write_to_csv(data, filename): with open(filename, 'w', newline='') as file: writer = csv.writer(file) writer...
Python Write List to CSV Using Numpy The Python Numpy library is used for large arrays or multi-dimensional datasets. Its functions allow you to perform some operations on these arrays. Let’s take an example. First, create a list of products with their names and categories, as shown below...
write_excel_file("D:\core\\") 第三种,使用pandas,可以写入到csv或者xlsx格式文件 1 2 3 4 5 6 import pandas as pd result_list = [['1', 1, 1], ['2', 2, 2], ['3', 3, 3]] columns = ["URL", "predict", "score"] dt = pd.DataFrame(result_list, columns=columns) dt.t...
写入数据到CSV文件:最后,我们将数据写入CSV文件。我们可以使用writerow函数将每一行数据写入文件。 # 写入数据到CSV文件forrowindata:writer.writerow(row) 1. 2. 3. 在这个例子中,我们使用一个循环遍历列表中的每一行数据,并使用writerow函数将其写入CSV文件。
with open('/root/list_to_csv.csv', 'w', newline='') as f: writer = csv.writer(f) writer.writerows(list_a) # 读取CSV文件 import csv with open('/root/list_to_csv.csv', 'r') as f: reader = csv.reader(f) result = list(reader) ...