Selecting distinct pandas data frame based on combination of multiple columns value.
I have a data like:
Time locIP remIp locPort remPort numReads numWrites
0 20180529235221 127.0.0.1 127.0.0.1 22 565 36736 36751
1 20180529235221 127.0.0.1 127.0.0.1 22 566 36736 74690
2 20180529235221 127.0.0.1 127.0.0.1 12 567 36736 36749
3 20180529235221 10.8.21.41 10.8.21.34 22 565 36744 36738
4 20180529235221 10.8.21.41 10.8.21.34 22 566 36744 36738
5 20180529235225 127.0.0.1 127.0.0.1 22 565 36788 36751
6 20180529235225 127.0.0.1 127.0.0.1 22 566 36788 74700
7 20180529235225 127.0.0.1 127.0.0.1 12 567 36788 36800
I want to plot time series graph for each combination of (locIP, remIP, LocPort remPort) and numReads.
For this I am looking for different smaller dataframes like:
Time locIP remIp locPort remPort numReads numWrites
0 20180529235221 127.0.0.1 127.0.0.1 22 565 36736 36751
5 20180529235225 127.0.0.1 127.0.0.1 22 565 36736 36751
Another one:
Time locIP remIp locPort remPort numReads numWrites
20180529235221 127.0.0.1 127.0.0.1 22 566 36736 74690
20180529235225 127.0.0.1 127.0.0.1 22 566 36788 74700
I was trying condition on multiple columns:
df1 =df[(df["locIP"] =='127.0.0.1') & (df["remIp"] == '127.0.0.1') & (df['locPort']== '22') & (df['remPort']=='565')]
But Here I have to extract all the combinations in condition variable. Looking for a better way.