pandas学习总结系列(二)

IO操作

一般我们获取数据获得输出结果都要和io接触。
pandas一般会有两个方法：

• read_excel()
• to_excel()
  支持csv，json，html，excel，sql等等。

和json相关操作

一般结构化数据比如(dataframe为主)

dfjo = pd.DataFrame(dict(A=range(1, 4), B=range(4, 7), C=range(7, 10)),
                columns=list('ABC'), index=list('xyz'))
 ----------------------
  A  B  C
x  1  4  7
y  2  5  8
z  3  6  9

• 面向列转为json(列为key)

dfjo.to_json(orient="columns")
------------------------
{"A":{"x":1,"y":2,"z":3},"B":{"x":4,"y":5,"z":6},"C":{"x":7,"y":8,"z":9}}

*面向行(key为index)

dfjo.to_json(orient="index")
-----------------------------
{"x":{"A":1,"B":4,"C":7},"y":{"A":2,"B":5,"C":8},"z":{"A":3,"B":6,"C":9}}

• 转为以数组包裹的类型(每一行为一个对象)

dfjo.to_json(orient="records")
----------------------------------------
[{"A":1,"B":4,"C":7},{"A":2,"B":5,"C":8},{"A":3,"B":6,"C":9}]

• 面向值 (不需要key，只需要值)

dfjo.to_json(orient="values")
----------------------------------
[[1,4,7],[2,5,8],[3,6,9]]

• 面向拆分(也就是将这组数据的col，index，data都分出来)

dfjo.to_json(orient="split")
-------------------------------
{"columns":["A","B","C"],"index":["x","y","z"],"data":[[1,4,7],[2,5,8],[3,6,9]]}

读取json

read_json('位置',orient) #orient和写差不多