In Python-Pandas How can I multiply a dataframe using datetime index values?
I have a timeline of many days that looks like this ... consecutive lines at intervals of 30 minutes:
a b
2006-05-08 09:30:00 10 13
2006-05-08 10:00:00 11 12
.
.
.
2006-05-08 15:30:00 15 14
2006-05-08 16:00:00 16 15
However, I only care about some specific cases, so I want the df to look like this every day:
2006-05-08 09:30:00 10 13
2006-05-08 11:30:00 14 15
2006-05-08 13:00:00 18 15
2006-05-08 16:00:00 16 15
Meaning, I just want to keep the lines at times (16, 13, 11:30, 9:30), for all different days in the dataframe.
thank
Update:
I went a little further using
hour = df.index.hour
selector = ((hour == 16) | (hour == 13) | (hour == 11) | (hour == 9))
df = df[selector]
However, I need to account for minutes as well, so I tried:
minute = df.index.minute
selector = ((hour == 16) & (minute == 0) | (hour == 3) & (minute == 0) | (hour == 9) & (minute == 30) | (hour == 12) & (minute == 0))
But I am getting error:
ValueError: operands could not be broadcast together with shapes (96310,) (16500,)
+3
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1 answer
import numpy as np
import pandas as pd
N = 100
df = pd.DataFrame(range(N), index=pd.date_range('2000-1-1', freq='30T',
periods=N))
mask = np.in1d((df.index.hour)*100+(df.index.minute), [930, 1130, 1300, 1600])
print(df.loc[mask])
gives
0
2000-01-01 09:30:00 19
2000-01-01 11:30:00 23
2000-01-01 13:00:00 26
2000-01-01 16:00:00 32
2000-01-02 09:30:00 67
2000-01-02 11:30:00 71
2000-01-02 13:00:00 74
2000-01-02 16:00:00 80
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