系统:Windows 7 语言版本:Anaconda3-4.3.0.1-Windows-x86_64 编辑器:pycharm-community-2016.3.2
Part 1:示例
DataFrame
,有4列["time", "pos", "value1", "value2", "value3"]
time
作为列,pos
作为行重组DataFrame
value1
这一列进行了重新布局,以time
作为列,pos
作为行原DataFrame
变形后
Part 2:代码
import pandas as pd
dict_1 = {"time": ["2019-11-2", "2019-11-2", "2019-11-2", "2019-11-3", "2019-11-3", "2019-11-3"], "pos": ["P1", "P2", "P3", "P1", "P2", "P3"], "value1": [11, 22, 33, 44, 55, 66], "value2": [1, 2, 3, 4, 5, 6], "value3": [1, 2, 3, 4, 5, 6]}
df = pd.DataFrame(dict_1, columns=["time", "pos", "value1", "value2", "value3"])df_2 = df.pivot(index="pos", columns='time', values='value1')print(df)print("\n")print(df_2)
代码截图
Part 3:部分代码解读
df.pivot(index="pos", columns='time', values='value1')
index
设置行索引columns
设置列索引values
设置内容df_3 = df.pivot(index="time", columns='pos', values='value1')
,结果如下图pos
的各种统计值,如下图所示调换行列
统计结果