计算来自同一列的时间戳值之间的差异

Question

我正在将 Blf 文件转换为 Tab 分隔文件。我能够从下面列表中的文件中提取所有有用的信息。我想计算一列中时间戳值之间的差异。到目前为止，请找到我的代码：

import can
import csv
import datetime
import pandas as pd

filename = open('C:\\Users\\shraddhasrivastav\\Downloads\\BLF File\\output.csv', "w")
log = can.BLFReader('C:\\Users\\shraddhasrivastav\\Downloads\\BLF File\\test.blf')

# print ("We are here!")
log_output = []

for msg in log:
    msg = str(msg).split()
    #print (msg)

    data_list = msg[7:(7 + int(msg[6]))]

    log_output_entry = [(msg[1]), msg[3], msg[6], " ".join(data_list), msg[-1]]
    log_output_entry.insert(1, 'ID=')
    test_entry = " \t ".join(log_output_entry)  # join the list and remove string quotes in the csv file

    filename.write(test_entry + '\n')

df = pd.DataFrame(log_output)
df.columns = ['Timestamp', 'ID', 'DLC','Channel']

filename.close()  # Close the file outside the loop

到目前为止我得到的输出如下：

在我的第一列下，我想要时间戳值之间的差异（示例 - 第 2 行值 - 第 1 行时间戳值......第 4 行时间戳值 - 第 3 行时间戳值......等等...... . 我应该在我的代码中添加什么来实现这一点？

下面是我希望文件的时间戳字段看起来如何的屏幕截图。 （计算连续行之间的差异）

enter image description here

Answer 1

你可以使用pandas.DataFrame.shift:

df['Time Delta'] = df['Timestamp'] - df['Timestamp'].shift(periods=1, axis=0)

请记住，您当前拥有的文件似乎在您写入的文本文件中的列之间具有可变长度，因此可能很难直接插入 pandas。也许以下会起作用：

import can
import csv
import datetime
import pandas as pd

#filename = open('C:\\Users\\shraddhasrivastav\\Downloads\\BLF File\\output.csv', "w")
log = can.BLFReader('C:\\Users\\shraddhasrivastav\\Downloads\\BLF File\\test.blf')

# print ("We are here!")
log_output = []

for msg in log:
    msg = str(msg).split()
    #print (msg)

    data_list = msg[7:(7 + int(msg[6]))]

    log_output_entry = [(msg[1]), msg[3], msg[6], " ".join(data_list), msg[-1]]
    log_output_entry.insert(1, 'ID=')
    assert len(log_output_entry)==4
    log_output.append(log_output_entry)
    #test_entry = " \t ".join(log_output_entry)  # join the list and remove string quotes in the csv file

    #filename.write(test_entry + '\n')

df = pd.DataFrame(log_output)
df.columns = ['Timestamp', 'ID', 'DLC','Channel']
df['Timestamp'] = pd.to_datetime(df['Timestamp'],unit='s')
df['Time Delta'] = df['Timestamp'] - df['Timestamp'].shift(periods=1, axis=0)
df.to_csv('C:\\Users\\shraddhasrivastav\\Downloads\\BLF File\\output_df.csv')

#filename.close()  # Close the file outside the loop