如何将时间戳添加到数据帧post read\u cvs

Question

读取cvs文件后，如何在数据帧中设置时间戳属性？我有一个测量数据集，但没有时间戳。我知道传感器数据的频率（200 Hz）和开始日期/时间。你知道吗

我试图计算文件中的行数并创建一个时间列。使用pd.插入我已经贴上了这个时间戳。我的问题是，在绘制这些数据时，我的x轴不显示属性化的时间戳，而是显示测量的数量。我的代码：

    #Importing signals 
    data = pd.read_csv('.../monday.txt')
    data.columns = ['l1','l2','l3','l4','l5','l6']

    print("Sensor data: ")
    print(data.head())
    print(data.dtypes)

    nbrMeasurments = sum(1 for line in open('.../monday.txt'))
    data.insert(0, "Time", pd.timedelta_range('11:24:26', 
    periods=nbrMeasurments-1, freq="5L"))

    print("Revised sensor data: ")
    print(data.head())
    print(data.dtypes)

在另一个有时间戳的文件中，pd.read_csv('.../mondayV1.csv',index_col='Date', usecols= [0,1,2], parse_dates=True)中的“index col='Date'”是确保x轴由日期而不是测量编号“x”引用的命令：

                         SYS (mmHg)  DIA (mmHg)
    Date                                       
    2019-08-07 13:06:30         111          61
    2019-08-07 13:07:08         114          64
    2019-08-07 13:07:56         112          63
    2019-08-07 13:08:42         127          81
    2019-08-07 13:09:19         129          83
    Omron data types: 
    SYS (mmHg)    int64
    DIA (mmHg)    int64

在我尝试插入不带时间戳的文件时，“时间”列为vaiable：

                 Time        l1        l2        l3        l4       l5       
    l6
    0        11:24:26  0.787261  0.943828  1.100903  0.835889  2.524946  
    2.252113
    1 11:24:26.005000  0.787068  0.943638  1.100871  0.835882  2.531180  
    2.253063
    2 11:24:26.010000  0.786951  0.943496  1.100779  0.835909  2.531573  
    2.253395
    3 11:24:26.015000  0.786879  0.943553  1.100877  0.835877  2.533841  
    2.254906
    4 11:24:26.020000  0.786682  0.943536  1.100651  0.835674  2.539893  
    2.257780

    Time    timedelta64[ns]
    l1              float64
    l2              float64
    l3              float64
    l4              float64
    ecg             float64
    ppg             float64

如何以最有效的方式将时间分配给此文件？你知道吗

Answer 1

为索引赋值data.insert：

data = pd.read_csv('.../monday.txt')
data.columns = ['l1','l2','l3','l4','l5','l6']

print("Sensor data: ")
print(data.head())
print(data.dtypes)

nbrMeasurments = sum(1 for line in open('.../monday.txt'))
data.index = pd.timedelta_range('11:24:26', periods=nbrMeasurments-1, freq="5L")

#another solution
#data = data.set_index(pd.timedelta_range('11:24:26', periods=nbrMeasurments-1, freq="5L"))
print("Revised sensor data: ")
print(data.head())
print(data.index)

Answer 2

像这样试试data.set_index(keys="Time", inplace=True)：

import pandas as pd
from io import StringIO

data = pd.read_csv(StringIO("""
             Time        l1        l2        l3        l4       l5       l6
0        11:24:26  0.787261  0.943828  1.100903  0.835889  2.524946  2.252113
1 11:24:26.005000  0.787068  0.943638  1.100871  0.835882  2.531180  2.253063
2 11:24:26.010000  0.786951  0.943496  1.100779  0.835909  2.531573  2.253395
3 11:24:26.015000  0.786879  0.943553  1.100877  0.835877  2.533841  2.254906
4 11:24:26.020000  0.786682  0.943536  1.100651  0.835674  2.539893  2.257780"""), sep="\s+")

data.set_index(keys="Time", inplace=True)

print(data)

输出：

                       l1        l2        l3        l4        l5        l6
Time                                                                       
11:24:26         0.787261  0.943828  1.100903  0.835889  2.524946  2.252113
11:24:26.005000  0.787068  0.943638  1.100871  0.835882  2.531180  2.253063
11:24:26.010000  0.786951  0.943496  1.100779  0.835909  2.531573  2.253395
11:24:26.015000  0.786879  0.943553  1.100877  0.835877  2.533841  2.254906
11:24:26.020000  0.786682  0.943536  1.100651  0.835674  2.539893  2.257780