读取json格式为DataFrame(可转为.csv)的实例讲解

yipeiwu_com5年前Python基础

有时候需要读取一定格式的json文件为DataFrame,可以通过json来转换或者pandas中的read_json()。

import pandas as pd
import json
data = pd.DataFrame(json.loads(open('jsonFile.txt','r+').read()))#方法一
dataCopy = pd.read_json('jsonFile.txt',typ='frame') #方法二
pandas.read_json(path_or_buf=None, orient=None, typ='frame', dtype=True, convert_axes=True, convert_dates=True, keep_default_dates=True, numpy=False, precise_float=False, date_unit=None, encoding=None, lines=False)[source]
 Convert a JSON string to pandas object
 Parameters: 
 path_or_buf : a valid JSON string or file-like, default: None
 The string could be a URL. Valid URL schemes include http, ftp, s3, and file. For file URLs, a host is expected. For instance, a local file could be file://localhost/path/to/table.json
 orient : string,
 Indication of expected JSON string format. Compatible JSON strings can be produced by to_json() with a corresponding orient value. The set of possible orients is:
  'split' : dict like {index -> [index], columns -> [columns], data -> [values]}
  'records' : list like [{column -> value}, ... , {column -> value}]
  'index' : dict like {index -> {column -> value}}
  'columns' : dict like {column -> {index -> value}}
  'values' : just the values array
 The allowed and default values depend on the value of the typ parameter.
  when typ == 'series',
  allowed orients are {'split','records','index'}
  default is 'index'
  The Series index must be unique for orient 'index'.
  when typ == 'frame',
  allowed orients are {'split','records','index', 'columns','values'}
  default is 'columns'
  The DataFrame index must be unique for orients 'index' and 'columns'.
  The DataFrame columns must be unique for orients 'index', 'columns', and 'records'.
 typ : type of object to recover (series or frame), default ‘frame'
 dtype : boolean or dict, default True
 If True, infer dtypes, if a dict of column to dtype, then use those, if False, then don't infer dtypes at all, applies only to the data.
 convert_axes : boolean, default True
 Try to convert the axes to the proper dtypes.
 convert_dates : boolean, default True
 List of columns to parse for dates; If True, then try to parse datelike columns default is True; a column label is datelike if
  it ends with '_at',
  it ends with '_time',
  it begins with 'timestamp',
  it is 'modified', or
  it is 'date'
 keep_default_dates : boolean, default True
 If parsing dates, then parse the default datelike columns
 numpy : boolean, default False
 Direct decoding to numpy arrays. Supports numeric data only, but non-numeric column and index labels are supported. Note also that the JSON ordering MUST be the same for each term if numpy=True.
 precise_float : boolean, default False
 Set to enable usage of higher precision (strtod) function when decoding string to double values. Default (False) is to use fast but less precise builtin functionality
 date_unit : string, default None
 The timestamp unit to detect if converting dates. The default behaviour is to try and detect the correct precision, but if this is not desired then pass one of ‘s', ‘ms', ‘us' or ‘ns' to force parsing only seconds, milliseconds, microseconds or nanoseconds respectively.
 lines : boolean, default False
 Read the file as a json object per line.
 New in version 0.19.0.
 encoding : str, default is ‘utf-8'
 The encoding to use to decode py3 bytes.
 New in version 0.19.0.

以上这篇读取json格式为DataFrame(可转为.csv)的实例讲解就是小编分享给大家的全部内容了,希望能给大家一个参考,也希望大家多多支持【听图阁-专注于Python设计】。

相关文章

Django REST framework视图的用法

Django REST framework视图的用法

前言 在了解了REST farmwork封装的视图类之后,我对python的面向对象有了更深刻的理解。 Django RESR framework框架内置的视图类充分发挥了面向对象封装...

python调用系统ffmpeg实现视频截图、http发送

python 调用系统ffmpeg进行视频截图,并进行图片http发送ffmpeg ,视频、图片的各种处理。  最近在做视频、图片的版权等深度学习识别,用到了ffmpeg部...

Python引用计数操作示例

Python引用计数操作示例

本文实例讲述了Python引用计数操作。分享给大家供大家参考,具体如下: 为了简化内存管理,Python通过引用计数机制实现了自动的垃圾回收功能,Python中的每个对象都有一个引用计数...

对Python2与Python3中__bool__方法的差异详解

学习Python面向对象编程的时候,遇到了一个很有意思的小问题。Python的__bool__方法不起作用的问题。 我反复读了我手中的教程,确认了我写的代码应该管用。可是在测试的时候却一...

python数据批量写入ScrolledText的优化方法

如下所示: for i in data[::-1]: self.maintenance_text.insert(tk.END, str(i['payload']) + '\n\n'...