{
"cells": [
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"# 文件的应用"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## csv文件 "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"CSV是文本文档，所以对文本进行读写的方法都适用于CSV格式文件的数据处理。而CSV格式的文件里的数据基本上都是由行和列构成的二维数据，可以使用列表嵌套的方法对其进行处理。"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"## 实例 9.5 读文件处理文件中的数据 "
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"文件<a href=\"images/ch8/5.7 score.csv\" target=\"_blank\">5.7 score.csv</a> 中数据如下，读取其中的数据并进行处理。"
]
},
{
"cell_type": "raw",
"metadata": {
"pycharm": {
"name": "#%% raw\n"
}
},
"source": [
"姓名,C语言,Java,Python,C#,C++\n",
"罗明,95,96,85,63,91\n",
"朱佳,75,93,66,85,88\n",
"李思,86,76,96,93,67\n",
"郑君,88,98,76,90,89\n",
"王雪,99,96,91,88,86"
]
},
{
"cell_type": "raw",
"metadata": {},
"source": [
"按要求完成以下操作：\n",
"1. 请读取文件中的数据，每行数据根据逗号切分为列表，输出二维列表。\n",
"2. 计算每位同学的总分附加到列表中各门课程成绩后面\n",
"3. 根据每名同学的总分进行降序排序输出\n",
"4. 将排序后的结果写入到新文件 “9.2 score_total.csv” 中"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [],
"source": [
"# 读文件中的数据为二维列表\n",
"\n",
"score_ls = [] # 创建空列表\n",
"with open('images/ch8/5.7 score.csv','r',encoding='utf-8') as fr:\n",
" for line in fr: # 遍历文件对象\n",
" \tscore_ls.append(line.strip().split(',')) # 文件每行切分为一个列表，split()参数根据文件中的分隔符确定\n",
"print(score_ls) "
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"定义为函数，用列表推导式实现更简洁，类似问题只修改文件名和切分时使用的分隔符即可重用此代码。"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [],
"source": [
"def read_file(filename):\n",
" \"\"\"接收文件名为参数，读取文件中的数据为二维列表，返回二维列表\"\"\"\n",
" with open(filename, 'r', encoding='utf-8') as fr:\n",
" score_ls = [x.strip().split(',') for x in fr]\n",
" return score_ls\n",
"\n",
"\n",
"if __name__ == '__main__':\n",
" score_lst = read_file('images/ch8/5.7 score.csv')\n",
" print(score_lst)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"为每位同学增加总成绩，可以将列表序号为0的元素score[0]拼接上['总分']，对剩余部分列表 score[1:] 进行遍历，每次得到一位同学的列表 x ，切片 x[1:] 为各门课的成绩，用map()函数将每个元素都 映射为整数，再用 sum() 函数对其进行求和并附加到列表中。"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"def read_file(filename):\n",
" \"\"\"接收文件名为参数，读取文件中的数据为二维列表，返回二维列表\"\"\"\n",
" with open(filename, 'r', encoding='utf-8') as fr:\n",
" score_ls = [x.strip().split(',') for x in fr]\n",
" return score_ls\n",
"\n",
"\n",
"def add_total(score_ls):\n",
" \"\"\"接收二维列表，增加总分，返回新的二维列表\"\"\"\n",
" title = score_ls[0] + ['总分'] # 列表拼接，一维列表\n",
" score_total = [title] # 创建新列表，首元素为原列表标题行增加平均成绩\n",
" for x in score_ls[1:]: # 略过标题行进行遍历\n",
" total = sum(map(int, x[1:])) # 切取成绩部分映射为整数，计算总成绩\n",
" score_total.append(x + [str(total)]) # 每个列表拼接字符型平均成绩\n",
" return score_total\n",
"\n",
"\n",
"if __name__ == '__main__':\n",
" score_lst = read_file('images/ch8/5.7 score.csv')\n",
" print(add_total(score_lst))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"将增加了总成绩的列表数据写入到文件中"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"def read_file(filename):\n",
" \"\"\"接收文件名为参数，读取文件中的数据为二维列表，返回二维列表\"\"\"\n",
" with open(filename, 'r', encoding='utf-8') as fr:\n",
" score_ls = [x.strip().split(',') for x in fr]\n",
" return score_ls\n",
"\n",
"\n",
"def add_total(score_ls):\n",
" \"\"\"接收二维列表，增加总分，返回新的二维列表\"\"\"\n",
" title = score_ls[0] + ['总分'] # 列表拼接，一维列表\n",
" score_total = [title] # 创建新列表，首元素为原列表标题行增加平均成绩\n",
" for x in score_ls[1:]: # 略过标题行进行遍历\n",
" total = sum(map(int, x[1:])) # 切取成绩部分映射为整数，计算总成绩\n",
" score_total.append(x + [str(total)]) # 每个列表拼接字符型平均成绩\n",
" return score_total\n",
"\n",
"\n",
"def write_file(score_total, filename):\n",
" \"\"\"接收成绩二维列表和写入文件名的字符串，\n",
" 将二维列表中的数据分行写入文件，每个列表中的数据写为一行，用逗号分隔\n",
" 无返回值\"\"\"\n",
" with open(filename, 'w', encoding='utf-8') as fw: # 写模式打开文件\n",
" for line in score_total: # 遍历二维列表\n",
" fw.write(','.join(line) + '\\n') # 子列表元素用逗号拼接为字符串加换行符\n",
" \n",
"\n",
"if __name__ == '__main__':\n",
" score_lst = read_file('images/ch8/5.7 score.csv')\n",
" score_total_ls = add_total(score_lst)\n",
" write_file(score_total_ls, 'score_total.csv')\n",
" print(read_file('score_total.csv'))"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"<font face='楷体' color='red' size=5> 练一练 </font>"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"修改实例9.4的程序，增加一个函数，可以获得文件中所有同学的名字，参考这个代码，获取并输出python课程的成绩的列表。"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [],
"source": [
"def read_file(filename):\n",
" \"\"\"接收文件名为参数，读取文件中的数据为二维列表，返回二维列表\"\"\"\n",
" with open(filename, 'r', encoding='utf-8') as fr:\n",
" score_ls = [x.strip().split(',') for x in fr]\n",
" return score_ls\n",
"\n",
"\n",
"def get_name(score_ls):\n",
" \"\"\"接收二维列表，返回全部学生名字的列表\"\"\"\n",
" return [x[0] for x in score_ls[1:]]\n",
"\n",
"\n",
"if __name__ == '__main__':\n",
" score_lst = read_file('images/ch8/5.7 score.csv')\n",
" print(get_name(score_lst))"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"<font face='楷体' color='red' size=5> 练一练 </font>"
]
},
{
"cell_type": "raw",
"metadata": {
"pycharm": {
"name": "#%% raw\n"
}
},
"source": [
"修改上面的程序，增加一个函数，可以获得文件中所有同学的名字，参考这个代码，获取并输出python课程的成绩的列表。"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [],
"source": [
"# 获取并输出python课程的成绩的列表\n",
"def read_file(filename):\n",
" \"\"\"接收文件名为参数，读取文件中的数据为二维列表，返回二维列表\"\"\"\n",
" with open(filename, 'r', encoding='utf-8') as fr:\n",
" score_ls = [x.strip().split(',') for x in fr]\n",
" return score_ls\n",
"\n",
"\n",
"def get_python(score_ls):\n",
" \"\"\"接收二维列表，返回全部学生python成绩的列表。\n",
" 列表中成绩应为整数\n",
" \"\"\"\n",
" # 补充你的代码\n",
"\n",
"\n",
"\n",
"\n",
"if __name__ == '__main__':\n",
" score_lst = read_file('images/ch8/5.7 score.csv')\n",
" print(get_python(score_lst))"
]
},
{
"cell_type": "raw",
"metadata": {
"pycharm": {
"name": "#%% raw\n"
}
},
"source": [
"输出：\n",
"[85, 66, 96, 76, 91]\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [],
"source": [
"# 获取并输出python课程的成绩的列表\n",
"def read_file(filename):\n",
" \"\"\"接收文件名为参数，读取文件中的数据为二维列表，返回二维列表\"\"\"\n",
" with open(filename, 'r', encoding='utf-8') as fr:\n",
" score_ls = [x.strip().split(',') for x in fr]\n",
" return score_ls\n",
"\n",
"\n",
"def get_python_avg(score_ls):\n",
" \"\"\"接收二维列表，返回全部学生python的平均成绩\"\"\"\n",
" # 补充你的代码\n",
" python = [int(x[3]) for x in score_ls[1:]]\n",
" return sum(python) / len(python)\n",
"\n",
"\n",
"\n",
"if __name__ == '__main__':\n",
" score_lst = read_file('images/ch8/5.7 score.csv')\n",
" print(get_python_avg(score_lst))"
]
},
{
"cell_type": "raw",
"metadata": {
"pycharm": {
"name": "#%% raw\n"
}
},
"source": [
"82.8"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"<font face='楷体' color='red' size=5> 练一练 </font>"
]
},
{
"cell_type": "raw",
"metadata": {
"pycharm": {
"name": "#%% raw\n"
}
},
"source": [
"修改实例9.4的程序，获得并输出转置的列表"
]
},
{
"cell_type": "raw",
"metadata": {
"pycharm": {
"name": "#%% raw\n"
}
},
"source": [
"提示：\n",
"list(zip(*score_ls)) 可将二维列表中的数据行列转置，得到元素为元组的列表"
]
},
{
"cell_type": "raw",
"metadata": {
"pycharm": {
"name": "#%% raw\n"
}
},
"source": [
"[['姓名', 'C语言', 'Java', 'Python', 'C#', 'C++'], \n",
" ['罗明', '95', '96', '85', '63', '91'], \n",
" ['朱佳', '75', '93', '66', '85', '88'], \n",
" ['李思', '86', '76', '96', '93', '67'], \n",
" ['郑君', '88', '98', '76', '90', '89'], \n",
" ['王雪', '99', '96', '91', '88', '86']]"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"转为"
]
},
{
"cell_type": "raw",
"metadata": {
"pycharm": {
"name": "#%% raw\n"
}
},
"source": [
"[('姓名', '罗明', '朱佳', '李思', '郑君', '王雪'), \n",
"('C语言', '95', '75', '86', '88', '99'), \n",
"('Java', '96', '93', '76', '98', '96'), \n",
"('Python', '85', '66', '96', '76', '91'), \n",
"('C#', '63', '85', '93', '90', '88'), \n",
"('C++', '91', '88', '67', '89', '86')]"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"pycharm": {
"name": "#%%\n"
},
"scrolled": true
},
"outputs": [],
"source": [
"def read_file(filename):\n",
" \"\"\"接收文件名为参数，读取文件中的数据为二维列表，返回行列转置后的二维列表\"\"\"\n",
" # 补充你的代码\n",
"\n",
" \n",
" \n",
"\n",
"if __name__ == '__main__':\n",
" score_lst = read_file('images/ch8/5.7 score.csv')\n",
" print(score_lst)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"<font face='楷体' color='red' size=5> 练一练 </font>"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"附件文件<a href=\"images/ch8/成绩分析综合.csv\" target=\"_blank\">成绩分析综合.csv</a> 中记录了学生实验课的成绩，其中8次实验占总成绩的70%，作业成绩占总成绩的30%，请完成以下任务：\n",
"1. 计算每位同学的总成绩\n",
"2. 在平时成绩后增加总成绩，按总成绩降序排序，总成绩相同时按学号降序排序，写到文件“成绩分析汇总.csv”中\n"
]
},
{
"cell_type": "raw",
"metadata": {
"pycharm": {
"name": "#%% raw\n"
}
},
"source": [
"姓名,学号,实验一,实验二,实验三,实验四,实验五,实验六,实验七,实验八,作业成绩\n",
"叶灿,0121701100312,100,100,100,100,100,100,60,100,96\n",
"朱宇轩,0121701100702,100,100,100,100,100,100,90,100,99\n",
"陈一帆,0121701100730,100,100,100,100,50,100,80,75,89.25\n",
"王璐,0121701100733,100,100,100,100,100,100,100,100,100\n",
"......"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [],
"source": [
"# 此代码为读csv文件到列表中，参考此代码完成题目\n",
"def read_txt(filename):\n",
" \"\"\"读文件到二维列表\"\"\"\n",
" with open(filename, encoding='utf-8') as f:\n",
" return [x.strip().split(',') for x in f]\n",
"\n",
"\n",
"if __name__ == '__main__':\n",
" score = read_txt('images/ch8/成绩分析综合.csv')\n",
" print(score)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [],
"source": [
"def read_csv(filename):\n",
" \"\"\"读文件到二维列表，精简代码\"\"\"\n",
" # 补充你的代码\n",
" \n",
"\n",
"\n",
"def add_total(score_ls):\n",
" \"\"\"接收包含成绩的二维列表，标题行增加“总成绩”列，计算总成绩并附加到列表中，\n",
" 返回增加了总成绩的二维列表。\n",
" \"\"\"\n",
" # 补充你的代码\n",
" \n",
"\n",
"\n",
"def write_file(total_score, filename):\n",
" \"\"\"接收成绩二维列表和写入文件名的字符串，将二维列表中的数据分行写入文件，\n",
" 每个列表中的数据写为一行，用逗号分隔，无返回值。\n",
" \"\"\"\n",
" # 补充你的代码\n",
"\n",
" \n",
" \n",
"if __name__ == '__main__':\n",
" score_lst = read_csv('images/ch8/成绩分析综合.csv') # 读文件到列表\n",
" score_all = add_total(score_lst) \n",
" write_file(score_all, '成绩分析综合2.csv') # 写入到'成绩分析综合2.csv'\n",
" print(read_csv('成绩分析综合2.csv')) # 再次调用读文件的函数，参数为新写入的文件名，查看是否写入成功\n",
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"## JSON文件 "
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%%\n"
}
},
"source": [
"JSON的编码过程是将一个Python对象转为JSON格式数据， \n",
"主要使用json.dumps(obj)和json.dump(obj,fp)两个方法。"
]
},
{
"cell_type": "raw",
"metadata": {
"pycharm": {
"name": "#%%\n"
}
},
"source": [
"json.dumps(obj, *, ensure_ascii=True, indent=None, sort_keys=False)\n",
"json.dump(obj, fp, *, ensure_ascii=True, indent=None, sort_keys=False)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"| 方法 | 描述 |\n",
"| :---- | :---- |\n",
"| json.dumps(obj) | 将Python 数据类型obj对象编码成JSON数据，写入内存。 |\n",
"| json.dump(obj,fp) | 将Python 数据类型obj对象编码成JSON数据，写入磁盘文件对象fp中。 |"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"json 中默认ensure_ascii=True， 会将中文等非ASCII 字符转为unicode 编码（形如\\uXXXX），设置ensure_ascii=False 可以禁止JSON 将中文转为unicode 编码，保持中文原样输出。 \n",
"Python中的字典数据转为JSON 默认不排序。可设置sort_keys=True使转换结果按照字典升序排序（a-z）。 \n",
"indent 参数可用来对JSON 数据进行格式化输出，默认值为None，不做格式化处理，可设一个大于0 的整数表示缩进量，例如indent=4。输出的数据被格式化之后，变得可读性更好。"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"JSON的**解码**过程是将JSON格式数据转为Python对象,Python 的原始类型与JSON类型会相互转换。 \n",
"主要使用json.loads(s)和json.load(fp)两个方法。\n"
]
},
{
"cell_type": "raw",
"metadata": {},
"source": [
"json.load(fp)\n",
"json.loads(s)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"| 方法 | 描述 |\n",
"| :---- | :---- |\n",
"| json.loads(s) | 将字符串s中的JSON数据解码为Python 数据类型，其他格式数据会转为unicode格式。 |\n",
"| json.load(fp) | 将磁盘文件对象fp中的JSON数据解码为Python 数据类型，其他格式数据会转为unicode格式。 |\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"将csv文件\"成绩分析综合.csv\"转为json文件"
]
},
{
"cell_type": "raw",
"metadata": {},
"source": [
"1. 将文件读为二维列表\n",
"2. 遍历二维列表序号1以后的元素\n",
" 2.1 用zip()将二维列表序号为 0 的子列表分别与后续的子列表组合并用dict()转为字典类型\n",
"3. 用dumps()将字典转为json格式数据写入json文件\n"
]
},
{
"cell_type": "raw",
"metadata": {},
"source": [
"读\"成绩分析综合.json\"为列表"
]
},
{
"cell_type": "raw",
"metadata": {},
"source": [
"1. 读文件创建文件对象fp\n",
" 1.1 用json.load(fp)将文件内中的数据读为python数据类型\n",
"2. 返回读取的结果"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import json\n",
"\n",
"\n",
"def read_csv(filename):\n",
" \"\"\"读文件到二维列表，返回二维列表\"\"\"\n",
" with open(filename, \"r\", encoding='utf-8') as f:\n",
" return [x.strip().split(',') for x in f]\n",
"\n",
"\n",
"def to_json(score_ls):\n",
" \"\"\"将二维列表标题行的元素与子列表中的元素一一组合，\n",
" 禁止JSON 将中文转为unicode 编码，保持中文原样输出。\n",
" 对JSON 数据进行格式化输出，缩进4个字符，\n",
" 返回json格式数据\"\"\"\n",
" score_dic = []\n",
" for i in range(1, len(score_ls)):\n",
" score_dic.append(dict(zip(score_ls[0], score_ls[i])))\n",
" return json.dumps(score_dic, ensure_ascii=False, indent=4)\n",
"\n",
"\n",
"def write_to_json(score_ls):\n",
" \"\"\"将二维列表标题行的元素与子列表中的元素一一组合，\n",
" 禁止JSON 将中文转为unicode 编码，保持中文原样输出。\n",
" 对JSON 数据进行格式化输出，缩进4个字符，\n",
" 写入json格式文件\"\"\"\n",
" score_dic = []\n",
" for i in range(1, len(score_ls)):\n",
" score_dic.append(dict(zip(score_ls[0], score_ls[i])))\n",
" with open('成绩分析综合.json','w',encoding='utf-8') as score_json:\n",
" json.dump(score_dic,score_json, ensure_ascii=False, indent=4)\n",
"\n",
"\n",
"def read_json_to_ls(filename):\n",
" \"\"\"读json文件，返回元素为字典类型的列表\"\"\"\n",
" with open(filename, \"r\", encoding='utf8') as f:\n",
" score_dic_ls = json.load(f)\n",
" return score_dic_ls\n",
"\n",
"\n",
"if __name__ == '__main__':\n",
" score_lst = read_csv('images/ch8/成绩分析综合.csv')\n",
" # print(to_json(score_lst))\n",
" write_to_json(score_lst)\n",
" print(read_json_to_ls('成绩分析综合.json'))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"scrolled": false
},
"outputs": [],
"source": [
"def read_json(filename):\n",
" \"\"\"读json文件，以字符串形式输出，查看写入文件的格式\"\"\"\n",
" with open(filename, \"r\", encoding='utf8') as f:\n",
" print(f.read())\n",
"\n",
"\n",
"if __name__ == '__main__':\n",
" read_json('成绩分析综合.json')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 借用eval()实现json转csv\n",
"eval()可以将字符串转为python数据类型，所以可以先用read()将json文件内容读取为字符串，再用eval()转为列表，再转csv文件"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"with open('成绩分析综合.json',encoding='utf-8') as fr:\n",
" txt = fr.read() # txt为字符串\n",
"\n",
"txt_py = eval(txt) # txt_py为元素为字典的列表\n",
"title = list(txt_py[0].keys()) # title为标题列表\n",
"score = [list(i.values()) for i in txt_py] # score为值的列表\n",
"score_ls = [title]+score # score_ls为标题+值的列表\n",
"\n",
"with open('成绩分析综合.csv','w',encoding='utf-8') as fw:\n",
" for lst in score_ls: # 遍历列表\n",
" fw.write(','.join(lst)+'\\n') # 将列表用逗号拼接为字符串并写入文件"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## os库常用方法 "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"| 方法 | 描述 |\n",
"| :---- | :---- |\n",
"| os.getcwd() | 获取当前工作路径 |\n",
"| os.chdir(path) | 将当前工作路径修改为path，如os.chdir(r'c:\\\\Users') |\n",
"| os.path.exist(name) | 判断name文件夹或文件是否存在，存在返回True，否则返回False |\n",
"| os.mkdir(pathname) | 新建一个名为pathname的文件夹 |\n",
"| os.rmdir(pathname) | 删除空文件夹pathname，文件夹不为空则报OSError错误 |\n",
"| os.path.isdir(path) | 判断path是否是文件夹，是则返回True，否则返回False |\n",
"| os.path.getsize(file) | 文件file存在，返回其大小(byte为单位)，不存在则报错 |\n",
"| os.remove(filename) | 删除文件 filename，文件不存在则报错 |\n",
"| os.path.isfile(filename) | 返回filename是否是文件，是返回True，否则返回False |\n",
"| os.listdir(path) | 以列表形式返回path路径下的所有文件名，不包括子路径中的文件名 |\n",
"| os.walk(path) | 返回类型为生成器，包含数据为若干包含文件和文件夹名的元组数据 |\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"inputHidden": true
},
"outputs": [],
"source": [
"# getcwd() 获取当前工作目录\n",
"\n",
"import os\n",
"\n",
"result = os.getcwd() \n",
"print(result)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import os\n",
"\n",
"\n",
"result = os.listdir('/home/jovyan/work')\n",
"print(result)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"<a href=\"images/ch8/5.7 score.csv\" target=\"_blank\">5.7 score.csv</a> \n",
"<a href=\"images/ch8/成绩分析综合.csv\" target=\"_blank\">成绩分析综合.csv</a> "
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"\n",
"data = np.genfromtxt('images/ch8/成绩分析综合.csv',delimiter=',',encoding='utf-8',dtype=str)\n",
"# 数据的标题行中有#，其后面的内容默认会被当成注释而忽略掉，导致标题行与数据行的列数不同而出错，可以用comments标明注释符\n",
"print(data)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"\n",
"data = np.genfromtxt('images/ch8/5.7 score.csv',delimiter=',',encoding='utf-8',dtype=str,comments=None)\n",
"# 数据的标题行中有#，其后面的内容默认会被当成注释而忽略掉，导致标题行与数据行的列数不同而出错，可以用comments标明注释符\n",
"print(data)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.5"
}
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"nbformat": 4,
"nbformat_minor": 2
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