Using pandas, I have a DataFrame that looks like this:
Hour Browser Metric1 Metric2 Metric3
2013-08-18 00 IE 1000 500 3000
2013-08-19 00 FF 2000 250 6000
2013-08-20 00 Opera 3000 450 9000
2001-03-21 00 Chrome/29 3000 450 9000
2013-08-21 00 Chrome/29 3000 450 9000
2014-01-22 00 Chrome/29 3000 750 9000
I want to create an array of browsers which have a maximum value of Metric1 > 2000. Is there a best way to do this? You can see basically what I am trying to do with the code below.
browsers = df[df.Metric1.max() > 2000]['Browser'].unique()
You could groupby Browser and take the max:
In [11]: g = df.groupby('Browser')
In [12]: g['Metric1'].max()
Out[12]:
Browser
Chrome/29 3000
FF 2000
IE 1000
Opera 3000
Name: Metric1, dtype: int64
In [13]: over2000 = g['Metric1'].max() > 2000
In [14]: over2000
Out[14]:
Browser
Chrome/29 True
FF False
IE False
Opera True
Name: Metric1, dtype: bool
To get out the array, use this as a boolean mask:
In [15]: over2000[over2000].index.values
Out[15]: array(['Chrome/29', 'Opera'], dtype=object)
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