json_lines
时间: 2023-10-02 11:09:28 浏览: 194
Json-lines是一种便于存储结构化数据的格式,可以一次处理一条记录。它常被用来存储日志文件或其他数据。每条Json数据之间存在一个"\n"分隔符。你可以使用json-lines库来读取和写入json-lines文件。 若要读取json-lines文件,你可以使用`json_lines.reader()`方法,并通过一个循环来遍历每一条记录。要写入json-lines文件,你可以使用`jsonlines.open()`方法,并将数据写入文件中。
相关问题
json-c/json_util.h
Sorry, as an AI language model, I cannot provide the full code for json-c/json_util.h as it contains many lines of code. However, I can give you a brief overview of what this header file contains.
json-c is a C library for JSON (JavaScript Object Notation) parsing and serialization. json_util.h is a header file included in the json-c library, which provides utility functions for manipulating JSON objects.
Some of the functions provided in this header file include:
- json_object_get(): retrieves the value of a specific key from a JSON object
- json_object_set_new(): sets the value of a key in a JSON object to a new JSON value
- json_object_object_add(): adds a key-value pair to a JSON object
- json_object_array_add(): adds a JSON value to a JSON array
- json_object_get_type(): returns the type of a JSON value
- json_object_to_json_string(): converts a JSON object to a string in JSON format
- json_object_put(): frees a JSON object and all its child objects
These functions can be used to create, read, update, and delete JSON objects in C programs.
麻烦你记住以下程序# 定义重点国家/地区 locs = ["China", "United States", "European Union", "Russia", "Japan", "United Kingdom", "Singapore"] # 设置要查找的文件夹路径 folder_path = 'C:/dbcovid/result/new_cases/' # 重点国家新增病例数量 all_data = [] #数据导入 for loc in locs: # 查找文件夹中所有的 .json 文件 json_files = glob.glob(folder_path +loc+ '/*.json') # 如果找到了至少一个 .json 文件 if json_files: # 选择第一个文件进行读取 json_file = json_files[0] tmp = pd.read_json(json_file, lines=True).values.squeeze() # turn to NumPy type # 在这里对读取到的数据进行处理 else: # 如果没有找到 .json 文件 print('No .json file found in the folder.') path = "C:/dbcovid/result/new_cases/China/part-00000-52417ca0-fbcb-4866-b14f-90e3f9fc939e-c000.json" all_data.append(tmp) all_data = np.array( [ list(i) + [float("nan")] * (max([len(j) for j in all_data]) - len(i)) for i in all_data ] ) #数据空值处理 for tmp in all_data: if np.isnan(tmp[0]): tmp[0] = 0 for i in range(len(tmp) - 1): if np.isnan(tmp[i + 1]): tmp[i + 1] = tmp[i] #数据平滑 for i in range(len(all_data)): all_data[i] = gaussian_filter1d(all_data[i], sigma=2.5) #保存为dataframe df = pd.DataFrame(all_data).transpose() df.columns = locs #绘图 plt.figure(figsize=(12, 8)) plt.xlabel('Days') plt.ylabel('Number of new cases') sns.lineplot(data=df, dashes=False) plt.show()
好的,以下是你提供的程序:
```python
# 定义重点国家/地区
locs = ["China", "United States", "European Union", "Russia", "Japan", "United Kingdom", "Singapore"]
# 设置要查找的文件夹路径
folder_path = 'C:/dbcovid/result/new_cases/'
# 重点国家新增病例数量
all_data = []
#数据导入
for loc in locs:
# 查找文件夹中所有的 .json 文件
json_files = glob.glob(folder_path +loc+ '/*.json')
# 如果找到了至少一个 .json 文件
if json_files:
# 选择第一个文件进行读取
json_file = json_files[0]
tmp = pd.read_json(json_file, lines=True).values.squeeze() # turn to NumPy type
# 在这里对读取到的数据进行处理
else:
# 如果没有找到 .json 文件
print('No .json file found in the folder.')
path = "C:/dbcovid/result/new_cases/China/part-00000-52417ca0-fbcb-4866-b14f-90e3f9fc939e-c000.json"
all_data.append(tmp)
all_data = np.array(
[
list(i) + [float("nan")] * (max([len(j) for j in all_data]) - len(i))
for i in all_data
]
)
#数据空值处理
for tmp in all_data:
if np.isnan(tmp[0]):
tmp[0] = 0
for i in range(len(tmp) - 1):
if np.isnan(tmp[i + 1]):
tmp[i + 1] = tmp[i]
#数据平滑
for i in range(len(all_data)):
all_data[i] = gaussian_filter1d(all_data[i], sigma=2.5)
#保存为dataframe
df = pd.DataFrame(all_data).transpose()
df.columns = locs
#绘图
plt.figure(figsize=(12, 8))
plt.xlabel('Days')
plt.ylabel('Number of new cases')
sns.lineplot(data=df, dashes=False)
plt.show()
```
请注意,这个程序需要一些额外的依赖库(如 pandas、numpy、matplotlib 和 seaborn),如果你要在自己的电脑上运行它,需要先安装这些库。