convert json file to csv using python

Knowledge about json File Parsing in Python, JSON (JavaScript Object Notation) is a lightweight data exchange format. It is based on a subset of JavaScript (Standard ECMA-262 3rd Edition-December 1999. JSON uses a completely language-independent text format, but it also uses

Python script: An Introduction to converting excel into an xml file of testlink Testlink only supports importing data in xml format, but some examples are displayed in excel. Test_link.py: Convert the excel file to the xml file of testlink, so that the excel

Turn from: http://blog.chinaunix.net/uid-9525959-id-3074355.html For more information, refer to the JSON documentation within Python: python>>> Help (JSON)or official documents:Http://docs.python.org/library/json.html#module-json Here's a simple example of

Paste a code to do the data cleaning, When doing data processing, the original file is converted to a certain format when it is processed. Original file data:123.txt 1,3,42,3,51,2,3,52,5 Use Python to convert to a two-dimensional list: #!/usr/bin/env python#coding=utf

One day, using Centos7, when discovering the network configuration, the subnet mask needs to be converted manually, because the CENTOS7 network is configured as follows:NMCLI Connection Enp4s0 Modify Ipv4.methord manual ipv4.address "192.168.1.120/24" Ipv4.gateway "192.168.1.1" Ipv4.dns "2 23.5.5.5 "A configuration item with no subnet mask. Then, write a function that implements the mutual transformation of the subnet mask and the bit length.One: The

This example describes the Python simple read JSON file feature. Share to everyone for your reference, specific as follows: Read_json.json: {"Rule ": {" namespace": "Strategy", "name": "test_exp_1496234234223400", "version": 0, "last_ Modify_time ": 1434234236819000, " log_rate ": 1023300, " schema_version ":" hello_world! " } read

I. Conceptual understanding1, Json.dumps () and json.loads () are JSON format processing functions (so to understand, JSON is a string)(1) the Json.dumps () function is an encoding of a Python data type list in JSON format (so to understand that the json.dumps () function converts a dictionary to a string)(2) the Json.

Use the built-in function raw_input () built-in function, which reads the standard input and assigns the read data to the specified variable. We can use the Int () built-in function to convert a user-entered string to an integer:>>> user = Raw_input ("Enter Login Name:")Enter Login Name:root>>> print "Your Login is:", userYour Login Is:rootThe above example can only be used for text input, and below is an example of entering a numeric string (and conv

20171105 1211/SundayCompanies in order to better fit the mobile phone, the previous use of PX to do a unit of CSS files, all need to convert to use REM to do units, is currently 1rem=37.5px; When developing new projects, it is customary to write style code of PX, complete the restoration of the UI manuscript, then unify into REM to do the unit, Paste the Nodejs code I wrote:var fs = require (' FS ');var path=require (' path ');Console.log ((__dirname)

Brief introduction Many sophisticated software projects have been using generic text configuration and resource files for many years, but no major problems have arisen. As the project expands and complexity increases, so does the need for higher rigor and greater adaptability. With XML and XML applications that use specific standards, you can benefit from cross project and Cross-platform compatibility, robustness, and scalability in areas such as Uni

First, JSON data preparation First, prepare a JSON data, a total of 3,560 items, each with the following structure: This example analyzes the distribution of time zones in this data using the values of the TZ (TimeZone time zone) field. Ii. convert JSON data to

It took some time today to look at how to use Python to process JSON files. As follows:1. Using the module JSON Official document gives 2.6 new added features2. Some basic knowledge of JSONThe data uses Key:value to form, the data is used, and the segmentation. The data can be the base type of the

[Spark] [Python] An example of opening a JSON file in a dataframe way:[email protected] ~]$ cat People.json{"Name": "Alice", "Pcode": "94304"}{"Name": "Brayden", "age": +, "Pcode": "94304"}{"Name": "Carla", "age": +, "Pcoe": "10036"}{"Name": "Diana", "Age": 46}{"Name": "Etienne", "Pcode": "94104"}[Email protected] ~]$[Email protected] ~]$ HDFs dfs-put People.json

This article mainly describes how to use Python to read the JSON file and encode the content into JSON format, for the specific processing of JSON data is not described.#!/usr/bin/env python#-*-encoding:gbk-*-import string,timeimp

serialization (serialization): converts the state information of an object (such as Python's simple data type list, String,dict,tuple,int,float, Unicode) into something that can be stored or transmitted, such as JSON, XML format) process deserialization: reads the state of the object that needs to be deserialized from the storage file or storage area (JSON, XML),

1. Weak supervisionAs the company recently prepared to open a new project, using deep learning to train a model that can be automatically labeled, but the model required training set is more troublesome, to first use ffmpeg from the video to intercept a video, in the use of OPENCV to draw frames to get pictures, so I can only be the semantic segmentation of the JSON fil