在 Python 中从日志文件中读取数据

Question

我正在尝试从 Python 中的日志文件中读取数据。假设文件名为 data.log。 文件内容如下：

# Performance log
# time, ff, T vector, dist, windnorth, windeast
0.00000000,0.00000000,0.00000000,0.00000000,0.00000000,0.00000000
1.00000000,3.02502604,343260.68655952,384.26845401,-7.70828175,-0.45288215
2.00000000,3.01495320,342124.21684440,767.95286901,-7.71506536,-0.45123853
3.00000000,3.00489957,340989.57100678,1151.05303883,-7.72185550,-0.44959182

我想获取最后两列并将它们放入两个单独的列表中，这样我就会得到如下输出：

list1 = [-7.70828175, -7.71506536, -7.71506536]

list2 = [-0.45288215, -0.45123853, -0.44959182]

我尝试使用以下代码读取数据，如下所示，但我没有单独的列和行，而是得到一整列和三行作为回报。

import matplotlib.pyplot as plt
import pandas as pd
import numpy as np

file = open('data.log', 'r')

df = pd.read_csv('data.log', sep='\\s+')

df = list(df)

print (df[0])

有人可以指出我必须在我的代码中调整什么以获得上述所需的输出吗？

提前致谢！

Answer 1

import pandas as pd 
df = pd.read_csv('sample.txt', skiprows=3, header=None, 
                 names=['time', 'ff', 'T vector', 'dist', 'windnorth', 'windeast'])
spam = list(df['windeast'])
print(spam)
# store a specific column in a list
df['wind_diff'] = df.windnorth - df['windeast'] # two different ways to access columsn
print(df)
print(df['wind_diff'])

输出

[-0.45288215, -0.45123853, -0.44959182]
   time        ff       T vector         dist  windnorth  windeast  wind_diff
0   1.0  3.025026  343260.686560   384.268454  -7.708282 -0.452882  -7.255400
1   2.0  3.014953  342124.216844   767.952869  -7.715065 -0.451239  -7.263827
2   3.0  3.004900  340989.571007  1151.053039  -7.721856 -0.449592  -7.272264
0   -7.255400
1   -7.263827
2   -7.272264
Name: wind_diff, dtype: float64

注意，要在 matplotlib 中创建绘图，您可以直接使用 pandas.Series，无需将其存储在列表中。

Answer 2

错误出现在sep 属性中。如果您删除它，它将使用您需要的默认值（逗号）：

例如

>>> import pandas as pd
>>> import numpy as np
>>> file = open('data.log', 'r')
>>> df = pd.read_csv('data.log')  # or use sep=','
>>> df = list(df)
>>> df[0]
'1.00000000'
>>> df[5]
'-0.45288215'

另外使用skiprows 来获取标题。