Hello i am relatively new to Python, i have a pandas dataframe looking similar to the one seen below, which i have imported from a txt file:
UnitNamePCU Timestamp PowerREF PowerPCU
F09 2014-11-01 00:20:00 60.73 79.64
F09 2014-11-01 00:30:00 63.15 84.06
F09 2014-11-01 01:00:00 101.06 84.03
F09 2014-11-01 01:10:00 122.79 104.29
F09 2014-11-01 01:20:00 86.57 110.08
F09 2014-11-01 01:40:00 16.74 27.32
F09 2014-11-01 01:50:00 12.59 21.69
F09 2014-11-01 02:20:00 17.42 13.98
My question is how can i sort the data in columns PowerREF and PowerPCU into "bins" saying something like: bin1 = PowerREF < 50, bin2 = 50 < PowerREF < 100. I know i can do something like:
bin1 = [x for x in data.PowerREF if x < 50]
bin2 = [x for x in data.PowerREF if x > 50 and x < 100]
but since the "bin" intervals can change maybe next time its bin1 = x < 100, bin2 = 100 < x < 200. I know the bin intervals before hand and the maximum value of the last bin the limit. So i think i should be able to do something with:
PowerLim = 1500
binInterval = 50
bin = range(0, PowerLim+1, binInterval)
I just dont know how to incorporate it smart and efficiently into the binnin process.
IIUC, you can use pd.cut here:
power_lim = 1500
bins = np.arange(0, power_lim + 1, 50)
pd.cut(df.PowerREF, bins=bins)
F09 (50, 100]
F09 (50, 100]
F09 (100, 150]
F09 (100, 150]
F09 (50, 100]
F09 (0, 50]
F09 (0, 50]
F09 (0, 50]
Name: PowerREF, dtype: category
Categories (30, interval[int64]): [(0, 50] < (50, 100] < (100, 150] < (150, 200] < ... <
(1300, 1350] < (1350, 1400] < (1400, 1450] < (1450, 1500]]