Stack Overflow Asked by meronpan on December 23, 2021
I am trying to use a mask to filter and show the dates that I am interested in. Here’s my current code:
# mask date range
start_date = '2019-10-01'
end_date = '2019-11-01'
mask1 = (df['StartTime'] >= start_date) & (df['StartTime'] < end_date)
# mask dayofweek
mask2 = (df.StartTime.dt.dayofweek == 0)
mask = mask1 & mask2
#apply mask
df.loc[mask]
The above code shows all dates within the mask1 date range (2019-10-01 to 2019-11-01) for mask2 dayofweek (0 = Monday).
However, I am interested in Monday to Thursday, so I need to adjust mask2.
Here are a few things I’ve tried:
#this doesn't work:
mask2 = (0<=df.StartTime.dt.dayofweek<=3)
#this doesn't work:
mask2 = (df.StartTime.dt.dayofweek == 0) or (df.StartTime.dt.dayofweek == 1) or (df.StartTime.dt.dayofweek == 2) or (df.StartTime.dt.dayofweek == 3)
Could you please show me what’s the best way to do this? Thank you in advance.
One approach by extracting dayofweek
and then using isin
Ex:
df = pd.DataFrame({
"StartTime" : ['2019-10-01', '2019-10-02', '2019-10-03', '2019-10-04', '2019-10-05', '2019-10-06', '2019-10-07', '2019-10-08']
})
df["StartTime"] = pd.to_datetime(df["StartTime"], format="%Y-%m-%d")
df["dayofweek"] = df["StartTime"].dt.dayofweek
print(df[df["dayofweek"].isin([0,1,2])]['StartTime'])
Output:
0 2019-10-01
1 2019-10-02
6 2019-10-07
7 2019-10-08
Name: StartTime, dtype: datetime64[ns]
Answered by Rakesh on December 23, 2021
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