I have log files, which have many lines in the form of :
LogLevel [13/10/2015 00:30:00.650] [Message Text]
My goal is to convert each line in the log file into a nice Data frame. I have tired to do that, by splitting the lines on the [ character, however I am still not getting a neat dataframe.
My code:
level = []
time = []
text = []
with open(filename) as inf:
for line in inf:
parts = line.split('[')
if len(parts) > 1:
level = parts[0]
time = parts[1]
text = parts[2]
print (parts[0],parts[1],parts[2])
s1 = pd.Series({'Level':level, 'Time': time, 'Text':text})
df = pd.DataFrame(s1).reset_index()
Heres my printed Data frame:
Info 10/08/16 10:56:09.843] In Function CCatalinaPrinter::ItemDescription()]
Info 10/08/16 10:56:09.843] Sending UPC Description Message ]
How can I improve this to strip the whitespace and the other ']' character
Thank you
You can use read_csv
with separator \s*\[
- whitespaces with [
:
import pandas as pd
from pandas.compat import StringIO
temp=u"""LogLevel [13/10/2015 00:30:00.650] [Message Text]
LogLevel [13/10/2015 00:30:00.650] [Message Text]
LogLevel [13/10/2015 00:30:00.650] [Message Text]
LogLevel [13/10/2015 00:30:00.650] [Message Text]"""
#after testing replace StringIO(temp) to filename
df = pd.read_csv(StringIO(temp), sep="\s*\[", names=['Level','Time','Text'], engine='python')
Then remove ]
by strip
and convert column Time
to_datetime
:
df.Time = pd.to_datetime(df.Time.str.strip(']'), format='%d/%m/%Y %H:%M:%S.%f')
df.Text = df.Text.str.strip(']')
print (df)
Level Time Text
0 LogLevel 2015-10-13 00:30:00.650 Message Text
1 LogLevel 2015-10-13 00:30:00.650 Message Text
2 LogLevel 2015-10-13 00:30:00.650 Message Text
3 LogLevel 2015-10-13 00:30:00.650 Message Text
print (df.dtypes)
Level object
Time datetime64[ns]
Text object
dtype: object
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