python/pandas/numpy(十二)数据加载、存储与文件格式

基本命令

pd.read_csv('1.txt')

只想读几行文本文件

pd.read_csv('1.txt', nrow=5)

要逐块读取文件,需要设置chunksize(行数)

chunker=pd.read_csv('1.txt',chunksize=1000)

写出到文本文件(以逗号分隔的文件)

data.to_csv('1.txt')

当然可以使用其他分隔符

data.to_csv('1.txt', sep='|')

JSON数据

使用json.loads将JSON字符串转化为Python形式

obj='''
{
    "name":"Wes",
    "place_lived":["USA","Spain","Germany"],
    "pet":null,
    "siblings":[{"name":"Young","age":25,"pet":"Zuko"},
                {"name":"Yo","age":24,"pet":"Zuk"}]

}
'''
import json
result=json.loads(obj)
result


{'name': 'Wes',
 'pet': None,
 'place_lived': ['USA', 'Spain', 'Germany'],
 'siblings': [{'age': 25, 'name': 'Young', 'pet': 'Zuko'},
  {'age': 24, 'name': 'Yo', 'pet': 'Zuk'}]}


type(result)
dict

json.dumps则将Python对象转化成JSON对象

asjson=json.dumps(result)
asjson

'{"name": "Wes", "siblings": [{"name": "Young", "pet": "Zuko", "age": 25}, {"name": "Yo", "pet": "Zuk", "age": 24}], "place_lived": ["USA", "Spain", "Germany"], "pet": null}'

type(asjson)
str

将JSON对象放入DataFrame

siblings=DataFrame(result['siblings'])
siblings

    age name    pet
0   25  Young   Zuko
1   24  Yo  Zuk
上一篇:隐私安全计算的认识将永久改变数据的命运


下一篇:BlockingQueue与Condition原理解析