系统:Windows 7 语言版本:Anaconda3-4.3.0.1-Windows-x86_64 编辑器:pycharm-community-2016.3.2 pandas:0.19.2
Part 1:目标
Datatables
,前端识别的数据格式有以下特征
- 数据格式为一个列表
- 列表中每一个元素为一个字典,每个字典对应前端表格的一行
- 单个字典的键为前端表格的列名,字典的值为前端表格每列取的值
Df
格式转换为列表
Part 2:代码
import pandas as pd
dict_1 = {"time": ["2019-11-02", "2019-11-03", "2019-11-04", "2019-11-05",
"2019-12-02", "2019-12-03", "2019-12-04", "2019-12-05"],
"pos": ["A", "A", "B", "B", "C", "C", "C", "D"],
"value1": [10, 20, 30, 40, 50, 60, 70, 80]}
df_1 = pd.DataFrame(dict_1, columns=["time", "pos", "value1"])
print("原数据", "\n", df_1, "\n")
print("\n按行输出")
list_fields = df_1.to_dict(orient='records')
print(list_fields)
代码截图
Part 3:部分代码解读
list_fields = df_1.to_dict(orient='records')
,使用了to_dict函数,其中orient=’records’,简单记忆法则,records表示记录,对应数据库的行Part 4:延伸
dict_fields = df_1.to_dict(orient='list')
print(dict_fields)
list对应结果