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
结果如图
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": ["P1", "P2", "P3", "P4", "P5", "P6", "P7", "P8"], "value1": [0.5, 0.8, 1.0, 2, 3, 5, 6, 7]}
df_1 = pd.DataFrame(dict_1, columns=["time", "pos", "value1"])df_1.set_index("pos", inplace=True)
print(df_1)print("\n")
for index, row in df_1.iterrows(): print(index) print(row["time"]) print(row["value1"]) print("\n")
代码截图
Part 3:部分代码解读
for index, row in df_1.iterrows():
,其中index为行索引的值,row表示这一行的一个Series,通过type函数获取其数据类型,如下图所示print(type(index))
print(type(row))