最初to_timedelta
を変換してから抽出することができますhour
:
df['Start_Time'] = pd.to_timedelta(df['Start_Time']+ ':00').dt.components.hours
df['End_Time'] = pd.to_timedelta(df['End_Time']+ ':00').dt.components.hours
print (df)
Day_Part Start_Time End_Time
0 Breakfast 9 11
1 Lunch 12 14
2 Dinner 19 23
int
へsplit
とキャストのもう一つの解決策:
df['Start_Time'] = df['Start_Time'].str.split(':').str[0].astype(int)
df['End_Time'] = df['End_Time'].str.split(':').str[0].astype(int)
print (df)
Day_Part Start_Time End_Time
0 Breakfast 9 11
1 Lunch 12 14
2 Dinner 19 23
extract
キャストとソリューションint
へ:
df['Start_Time'] = df['Start_Time'].str.extract('(\d*):', expand=False).astype(int)
df['End_Time'] = df['End_Time'].str.extract('(\d*):', expand=False).astype(int)
print (df)
Day_Part Start_Time End_Time
0 Breakfast 9 11
1 Lunch 12 14
2 Dinner 19 23
変換
to_datetime
と
ソリューション:
df['Start_Time'] = pd.to_datetime(df['Start_Time'], format='%H:%M').dt.hour
df['End_Time'] = pd.to_datetime(df['End_Time'], format='%H:%M').dt.hour
print (df)
Day_Part Start_Time End_Time
0 Breakfast 9 11
1 Lunch 12 14
2 Dinner 19 23
タイミング:
#[300000 rows x 3 columns]
df = pd.concat([df]*100000).reset_index(drop=True)
print (df)
In [158]: %timeit pd.to_timedelta(df['Start_Time']+ ':00').dt.components.hours
1 loop, best of 3: 7.12 s per loop
In [159]: %timeit df['Start_Time'].str.split(':').str[0].astype(int)
1 loop, best of 3: 415 ms per loop
In [160]: %timeit df['Start_Time'].str.extract('(\d*):', expand=False).astype(int)
1 loop, best of 3: 654 ms per loop
In [166]: %timeit pd.to_datetime(df['Start_Time'], format='%H:%M').dt.hour
1 loop, best of 3: 1.26 s per loop