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📜  如何在Python中将 pandas DataFrame 转换为 JSON？

📅  最后修改于: 2022-05-13 01:55:21.919000             🧑  作者: Mango

如何在Python中将 pandas DataFrame 转换为 JSON？

数据分析是当今世界极为重要的工具。数据分析的一个关键方面是数据的有组织的表示。计算机科学中有许多数据结构可以完成这项任务。在本文中，我们讨论了两种这样的数据结构，即。熊猫数据帧和JSON 。此外，我们还将了解如何将 DataFrame 转换为 JSON 格式。

Pandas DataFrame 是数据的表格表示形式，其中列表示单个数据条目中的各种数据点，每一行是唯一的数据条目。而 JSON 是用 JavaScript 对象表示法编写的文本。

注意：更多信息请参考Python |熊猫数据框

将 pandas DataFrame 转换为 JSON

要将 pandas DataFrames 转换为 JSON 格式，我们使用Python中 pandas 库中的函数DataFrame.to_json() 。 to_json函数中有多种自定义可用于实现所需的 JSON 格式。先看看函数接受的参数，再探索自定义

参数：

ParameterValueUse
path_or_bufstring or filename, optionalFile path or object. If not specified, the result is returned as a string.
orient‘split’, ‘records’, ‘index’, ‘columns’, ‘values’, ‘table’, default=’index’Indication of expected JSON string format.
date_formatNone, ‘epoch’, ‘iso’, default=’epoch’Type of date conversion. ‘epoch’ = epoch milliseconds, ‘iso’ = ISO8601. The default depends on the orient. For orient=’table’, the default is ‘iso’. For all other orients, the default is ‘epoch’.
double_precisioninteger value, default=10The number of decimal places to use when encoding floating point values.
force_asciiboolean value, default=TrueForce encoded string to be ASCII.
date_unit‘s’, ‘ms’, ‘us’, ‘ns’, default=’ms’The time unit to encode to, governs timestamp and ISO8601 precision. The values represent second, millisecond, microsecond, and nanosecond respectively.
default_handlercallable functionHandler to call if object cannot otherwise be converted to a suitable format for JSON. Should receive a single argument which is the object to convert and return a serializable object.
linesboolean value, default=FalseIf ‘orient’ is ‘records’ write out line delimited json format. Will throw ValueError if incorrect ‘orient’ since others are not list like.
compression‘infer’, ‘gzip’, ‘bz2’, ‘zip’, ‘xz’, None, default=’infer’A string representing the compression to use in the output file, only used when the first argument is a filename. By default, the compression is inferred from the filename.
indexboolean value, default=TrueWhether to include the index values in the JSON string. Not including the index (index=False) is only supported when orient is ‘split’ or ‘table’.
indentinteger valueLength of whitespace used to indent each record. Optional argument need not be mentioned.

我们现在看几个例子来了解函数DataFrame.to_json 的用法。

示例 1：基本用法

import numpy as np
import pandas as pd
  
  
data = np.array([['1', '2'], ['3', '4']])
  
dataFrame = pd.DataFrame(data, columns = ['col1', 'col2'])
json = dataFrame.to_json()
print(json)

输出 ： 

{"col1":{"0":"1", "1":"3"}, "col2":{"0":"2", "1":"4"}}

示例 2：探索 DataFrame.to_json函数的 'orient' 属性

import numpy as np
import pandas as pd
  
  
data = np.array([['1', '2'], ['3', '4']])
   
dataFrame = pd.DataFrame(data, columns = ['col1', 'col2'])
json = dataFrame.to_json()
print(json)
  
json_split = dataFrame.to_json(orient ='split')
print("json_split = ", json_split, "\n")
   
json_records = dataFrame.to_json(orient ='records')
print("json_records = ", json_records, "\n")
   
json_index = dataFrame.to_json(orient ='index')
print("json_index = ", json_index, "\n")
   
json_columns = dataFrame.to_json(orient ='columns')
print("json_columns = ", json_columns, "\n")
   
json_values = dataFrame.to_json(orient ='values')
print("json_values = ", json_values, "\n")
   
json_table = dataFrame.to_json(orient ='table')
print("json_table = ", json_table, "\n")

输出 ：