Convert object to time Pandas and filter between times

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I have a dataframe with a column containing a series of dtype'o' items:

0         17:32:16

1         17:32:20

2         17:32:24

3         17:32:28

4         17:32:32

5         17:32:36

6         17:32:40

7         17:32:44

8         17:32:48

9         17:32:52

10        17:32:56

11        17:33:00

12        17:33:04

13        17:33:08

14        17:33:12

15        17:33:16

how can I convert it into time in order to filter then between for instance 17:32:30 and 17:33:10?
At the Moment I was trying without success:

df_result['a']=datetime.datetime(df_result['a'], '%H%M%S').time()

any help? thank you in advance

edited Nov 23 '18 at 7:52

petezurich

3,89581936

asked Nov 23 '18 at 7:37

Luca91

1928

add a comment |

I have a dataframe with a column containing a series of dtype'o' items:

0         17:32:16

1         17:32:20

2         17:32:24

3         17:32:28

4         17:32:32

5         17:32:36

6         17:32:40

7         17:32:44

8         17:32:48

9         17:32:52

10        17:32:56

11        17:33:00

12        17:33:04

13        17:33:08

14        17:33:12

15        17:33:16

how can I convert it into time in order to filter then between for instance 17:32:30 and 17:33:10?
At the Moment I was trying without success:

df_result['a']=datetime.datetime(df_result['a'], '%H%M%S').time()

any help? thank you in advance

edited Nov 23 '18 at 7:52

petezurich

3,89581936

asked Nov 23 '18 at 7:37

Luca91

1928

add a comment |

I have a dataframe with a column containing a series of dtype'o' items:

0         17:32:16

1         17:32:20

2         17:32:24

3         17:32:28

4         17:32:32

5         17:32:36

6         17:32:40

7         17:32:44

8         17:32:48

9         17:32:52

10        17:32:56

11        17:33:00

12        17:33:04

13        17:33:08

14        17:33:12

15        17:33:16

how can I convert it into time in order to filter then between for instance 17:32:30 and 17:33:10?
At the Moment I was trying without success:

df_result['a']=datetime.datetime(df_result['a'], '%H%M%S').time()

any help? thank you in advance

edited Nov 23 '18 at 7:52

petezurich

3,89581936

asked Nov 23 '18 at 7:37

Luca91

1928

I have a dataframe with a column containing a series of dtype'o' items:

0         17:32:16

1         17:32:20

2         17:32:24

3         17:32:28

4         17:32:32

5         17:32:36

6         17:32:40

7         17:32:44

8         17:32:48

9         17:32:52

10        17:32:56

11        17:33:00

12        17:33:04

13        17:33:08

14        17:33:12

15        17:33:16

how can I convert it into time in order to filter then between for instance 17:32:30 and 17:33:10?
At the Moment I was trying without success:

df_result['a']=datetime.datetime(df_result['a'], '%H%M%S').time()

any help? thank you in advance

python pandas

edited Nov 23 '18 at 7:52

petezurich

3,89581936

asked Nov 23 '18 at 7:37

Luca91

1928

edited Nov 23 '18 at 7:52

petezurich

3,89581936

asked Nov 23 '18 at 7:37

Luca91

1928

edited Nov 23 '18 at 7:52

petezurich

3,89581936

edited Nov 23 '18 at 7:52

petezurich

3,89581936

edited Nov 23 '18 at 7:52

petezurich

3,89581936

asked Nov 23 '18 at 7:37

Luca91

1928

asked Nov 23 '18 at 7:37

Luca91

1928

asked Nov 23 '18 at 7:37

Luca91

1928

add a comment |

1 Answer
1

active

oldest

votes

Create times by to_datetime with time and then use between with boolean indexing:

from datetime import time



df_result['a'] = pd.to_datetime(df_result['a']).dt.time

df_result = df_result[df_result['a'].between(time(17, 32, 30), time(17, 33, 10))]



print (df_result)

           a

4   17:32:32

5   17:32:36

6   17:32:40

7   17:32:44

8   17:32:48

9   17:32:52

10  17:32:56

11  17:33:00

12  17:33:04

13  17:33:08

Another approach with timedeltas created by to_timedelta:

df_result['a'] = pd.to_timedelta(df_result['a'])

df_result = df_result[df_result['a'].between('17:32:30', '17:33:10')]



print (df_result)

          a

4  17:32:32

5  17:32:36

6  17:32:40

7  17:32:44

8  17:32:48

9  17:32:52

10 17:32:56

11 17:33:00

12 17:33:04

13 17:33:08

edited Nov 23 '18 at 7:53

answered Nov 23 '18 at 7:40

jezrael

361k26327408

add a comment |

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1 Answer
1

active

oldest

votes

1 Answer
1

active

oldest

votes

Create times by to_datetime with time and then use between with boolean indexing:

from datetime import time



df_result['a'] = pd.to_datetime(df_result['a']).dt.time

df_result = df_result[df_result['a'].between(time(17, 32, 30), time(17, 33, 10))]



print (df_result)

           a

4   17:32:32

5   17:32:36

6   17:32:40

7   17:32:44

8   17:32:48

9   17:32:52

10  17:32:56

11  17:33:00

12  17:33:04

13  17:33:08

Another approach with timedeltas created by to_timedelta:

df_result['a'] = pd.to_timedelta(df_result['a'])

df_result = df_result[df_result['a'].between('17:32:30', '17:33:10')]



print (df_result)

          a

4  17:32:32

5  17:32:36

6  17:32:40

7  17:32:44

8  17:32:48

9  17:32:52

10 17:32:56

11 17:33:00

12 17:33:04

13 17:33:08

edited Nov 23 '18 at 7:53

answered Nov 23 '18 at 7:40

jezrael

361k26327408

add a comment |

Create times by to_datetime with time and then use between with boolean indexing:

from datetime import time



df_result['a'] = pd.to_datetime(df_result['a']).dt.time

df_result = df_result[df_result['a'].between(time(17, 32, 30), time(17, 33, 10))]



print (df_result)

           a

4   17:32:32

5   17:32:36

6   17:32:40

7   17:32:44

8   17:32:48

9   17:32:52

10  17:32:56

11  17:33:00

12  17:33:04

13  17:33:08

Another approach with timedeltas created by to_timedelta:

df_result['a'] = pd.to_timedelta(df_result['a'])

df_result = df_result[df_result['a'].between('17:32:30', '17:33:10')]



print (df_result)

          a

4  17:32:32

5  17:32:36

6  17:32:40

7  17:32:44

8  17:32:48

9  17:32:52

10 17:32:56

11 17:33:00

12 17:33:04

13 17:33:08

edited Nov 23 '18 at 7:53

answered Nov 23 '18 at 7:40

jezrael

361k26327408

add a comment |

Create times by to_datetime with time and then use between with boolean indexing:

from datetime import time



df_result['a'] = pd.to_datetime(df_result['a']).dt.time

df_result = df_result[df_result['a'].between(time(17, 32, 30), time(17, 33, 10))]



print (df_result)

           a

4   17:32:32

5   17:32:36

6   17:32:40

7   17:32:44

8   17:32:48

9   17:32:52

10  17:32:56

11  17:33:00

12  17:33:04

13  17:33:08

Another approach with timedeltas created by to_timedelta:

df_result['a'] = pd.to_timedelta(df_result['a'])

df_result = df_result[df_result['a'].between('17:32:30', '17:33:10')]



print (df_result)

          a

4  17:32:32

5  17:32:36

6  17:32:40

7  17:32:44

8  17:32:48

9  17:32:52

10 17:32:56

11 17:33:00

12 17:33:04

13 17:33:08

edited Nov 23 '18 at 7:53

answered Nov 23 '18 at 7:40

jezrael

361k26327408

Create times by to_datetime with time and then use between with boolean indexing:

from datetime import time



df_result['a'] = pd.to_datetime(df_result['a']).dt.time

df_result = df_result[df_result['a'].between(time(17, 32, 30), time(17, 33, 10))]



print (df_result)

           a

4   17:32:32

5   17:32:36

6   17:32:40

7   17:32:44

8   17:32:48

9   17:32:52

10  17:32:56

11  17:33:00

12  17:33:04

13  17:33:08

Another approach with timedeltas created by to_timedelta:

df_result['a'] = pd.to_timedelta(df_result['a'])

df_result = df_result[df_result['a'].between('17:32:30', '17:33:10')]



print (df_result)

          a

4  17:32:32

5  17:32:36

6  17:32:40

7  17:32:44

8  17:32:48

9  17:32:52

10 17:32:56

11 17:33:00

12 17:33:04

13 17:33:08

edited Nov 23 '18 at 7:53

answered Nov 23 '18 at 7:40

jezrael

361k26327408

edited Nov 23 '18 at 7:53

answered Nov 23 '18 at 7:40

jezrael

361k26327408

answered Nov 23 '18 at 7:40

jezrael

361k26327408

answered Nov 23 '18 at 7:40

jezrael

361k26327408

add a comment |

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