Splitting dataframe by month on a series in Python

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-3

My dataframe has dates that range from month 1-12 for every set. The data looks like:

 Date AB AK AR DC
 0 2005-01-01 267724 37140 152536 60004
 1 2005-02-01 214444 32710 149821 49280
 2 2005-03-01 205938 27484 141526 41345
 3 2005-04-01 99262 14562 81254 31609
 4 2005-05-01 66059 8172 50241 18705
 5 2005-06-01 33556 4880 27216 11796
 6 2005-07-01 28057 4138 20156 9126
 7 2005-08-01 25466 3892 19005 8262
 8 2005-09-01 26819 3923 18776 9480
 9 2005-10-01 60849 5942 31255 1664
.
.

The Date is in datetime format:

data_res_num.info()
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 164 entries, 0 to 163
Data columns (total 11 columns):
Date 164 non-null datetime64[ns]

But when I try to pass only certain months (10 to 3) with:

df = df.loc[(df['Date'].dt.month > 10) & (df['Date'].dt.month < 4)]

I get an empty frame for df.

I thought it may have been the range but even if I set it == certain month it also gives me an empty frame.

How can I select the range from November - March?

asked Nov 15 '18 at 15:52

HelloToEarth

537215

3

Typo: there are no integers greater than 10 AND less than 3.

– jpp
Nov 15 '18 at 15:56

That's the thing. I also tried df = df.loc[(df['Date'].dt.month == 10) & (df['Date'].dt.month == 4)] and I get the same result and I know 10 and 4 exist.

– HelloToEarth
Nov 15 '18 at 15:58

@jpp pandas will select rows which satisfy either of these column conditions, they don't have to be satisfied simultaneously...

– Dascienz
Nov 15 '18 at 16:02

2

@jpp, Oh duh, he needs a |, my bad! Haha, really embarrassing.

– Dascienz
Nov 15 '18 at 16:03

1

Hey @HelloToEarth, | is an OR operator which means that pandas will select rows which satisfy either condition, however, when you use & which is an AND operator it means that both conditions must be satisfied simultaneously. You can't have a month be greater than 10 and less than 4 at the same time, nor can you have a month that is both equal to 4 and 10 at the same time. Therefore, you need to use the OR operator, |.

– Dascienz
Nov 15 '18 at 16:09

|
show 3 more comments

-3

My dataframe has dates that range from month 1-12 for every set. The data looks like:

 Date AB AK AR DC
 0 2005-01-01 267724 37140 152536 60004
 1 2005-02-01 214444 32710 149821 49280
 2 2005-03-01 205938 27484 141526 41345
 3 2005-04-01 99262 14562 81254 31609
 4 2005-05-01 66059 8172 50241 18705
 5 2005-06-01 33556 4880 27216 11796
 6 2005-07-01 28057 4138 20156 9126
 7 2005-08-01 25466 3892 19005 8262
 8 2005-09-01 26819 3923 18776 9480
 9 2005-10-01 60849 5942 31255 1664
.
.

The Date is in datetime format:

data_res_num.info()
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 164 entries, 0 to 163
Data columns (total 11 columns):
Date 164 non-null datetime64[ns]

But when I try to pass only certain months (10 to 3) with:

df = df.loc[(df['Date'].dt.month > 10) & (df['Date'].dt.month < 4)]

I get an empty frame for df.

I thought it may have been the range but even if I set it == certain month it also gives me an empty frame.

How can I select the range from November - March?

asked Nov 15 '18 at 15:52

HelloToEarth

537215

3

Typo: there are no integers greater than 10 AND less than 3.

– jpp
Nov 15 '18 at 15:56

That's the thing. I also tried df = df.loc[(df['Date'].dt.month == 10) & (df['Date'].dt.month == 4)] and I get the same result and I know 10 and 4 exist.

– HelloToEarth
Nov 15 '18 at 15:58

@jpp pandas will select rows which satisfy either of these column conditions, they don't have to be satisfied simultaneously...

– Dascienz
Nov 15 '18 at 16:02

2

@jpp, Oh duh, he needs a |, my bad! Haha, really embarrassing.

– Dascienz
Nov 15 '18 at 16:03

1

Hey @HelloToEarth, | is an OR operator which means that pandas will select rows which satisfy either condition, however, when you use & which is an AND operator it means that both conditions must be satisfied simultaneously. You can't have a month be greater than 10 and less than 4 at the same time, nor can you have a month that is both equal to 4 and 10 at the same time. Therefore, you need to use the OR operator, |.

– Dascienz
Nov 15 '18 at 16:09

|
show 3 more comments

-3

My dataframe has dates that range from month 1-12 for every set. The data looks like:

 Date AB AK AR DC
 0 2005-01-01 267724 37140 152536 60004
 1 2005-02-01 214444 32710 149821 49280
 2 2005-03-01 205938 27484 141526 41345
 3 2005-04-01 99262 14562 81254 31609
 4 2005-05-01 66059 8172 50241 18705
 5 2005-06-01 33556 4880 27216 11796
 6 2005-07-01 28057 4138 20156 9126
 7 2005-08-01 25466 3892 19005 8262
 8 2005-09-01 26819 3923 18776 9480
 9 2005-10-01 60849 5942 31255 1664
.
.

The Date is in datetime format:

data_res_num.info()
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 164 entries, 0 to 163
Data columns (total 11 columns):
Date 164 non-null datetime64[ns]

But when I try to pass only certain months (10 to 3) with:

df = df.loc[(df['Date'].dt.month > 10) & (df['Date'].dt.month < 4)]

I get an empty frame for df.

I thought it may have been the range but even if I set it == certain month it also gives me an empty frame.

How can I select the range from November - March?

asked Nov 15 '18 at 15:52

HelloToEarth

537215

My dataframe has dates that range from month 1-12 for every set. The data looks like:

 Date AB AK AR DC
 0 2005-01-01 267724 37140 152536 60004
 1 2005-02-01 214444 32710 149821 49280
 2 2005-03-01 205938 27484 141526 41345
 3 2005-04-01 99262 14562 81254 31609
 4 2005-05-01 66059 8172 50241 18705
 5 2005-06-01 33556 4880 27216 11796
 6 2005-07-01 28057 4138 20156 9126
 7 2005-08-01 25466 3892 19005 8262
 8 2005-09-01 26819 3923 18776 9480
 9 2005-10-01 60849 5942 31255 1664
.
.

The Date is in datetime format:

data_res_num.info()
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 164 entries, 0 to 163
Data columns (total 11 columns):
Date 164 non-null datetime64[ns]

But when I try to pass only certain months (10 to 3) with:

df = df.loc[(df['Date'].dt.month > 10) & (df['Date'].dt.month < 4)]

I get an empty frame for df.

I thought it may have been the range but even if I set it == certain month it also gives me an empty frame.

How can I select the range from November - March?

python python-3.x python-2.7 pandas dataframe

asked Nov 15 '18 at 15:52

HelloToEarth

537215

asked Nov 15 '18 at 15:52

HelloToEarth

537215

asked Nov 15 '18 at 15:52

HelloToEarth

537215

asked Nov 15 '18 at 15:52

HelloToEarth

537215

asked Nov 15 '18 at 15:52

HelloToEarth

537215

3

Typo: there are no integers greater than 10 AND less than 3.

– jpp
Nov 15 '18 at 15:56

That's the thing. I also tried df = df.loc[(df['Date'].dt.month == 10) & (df['Date'].dt.month == 4)] and I get the same result and I know 10 and 4 exist.

– HelloToEarth
Nov 15 '18 at 15:58

@jpp pandas will select rows which satisfy either of these column conditions, they don't have to be satisfied simultaneously...

– Dascienz
Nov 15 '18 at 16:02

2

@jpp, Oh duh, he needs a |, my bad! Haha, really embarrassing.

– Dascienz
Nov 15 '18 at 16:03

1

Hey @HelloToEarth, | is an OR operator which means that pandas will select rows which satisfy either condition, however, when you use & which is an AND operator it means that both conditions must be satisfied simultaneously. You can't have a month be greater than 10 and less than 4 at the same time, nor can you have a month that is both equal to 4 and 10 at the same time. Therefore, you need to use the OR operator, |.

– Dascienz
Nov 15 '18 at 16:09

|
show 3 more comments

3

Typo: there are no integers greater than 10 AND less than 3.

– jpp
Nov 15 '18 at 15:56

That's the thing. I also tried df = df.loc[(df['Date'].dt.month == 10) & (df['Date'].dt.month == 4)] and I get the same result and I know 10 and 4 exist.

– HelloToEarth
Nov 15 '18 at 15:58

@jpp pandas will select rows which satisfy either of these column conditions, they don't have to be satisfied simultaneously...

– Dascienz
Nov 15 '18 at 16:02

2

@jpp, Oh duh, he needs a |, my bad! Haha, really embarrassing.

– Dascienz
Nov 15 '18 at 16:03

1

Hey @HelloToEarth, | is an OR operator which means that pandas will select rows which satisfy either condition, however, when you use & which is an AND operator it means that both conditions must be satisfied simultaneously. You can't have a month be greater than 10 and less than 4 at the same time, nor can you have a month that is both equal to 4 and 10 at the same time. Therefore, you need to use the OR operator, |.

– Dascienz
Nov 15 '18 at 16:09

Typo: there are no integers greater than 10 AND less than 3.

– jpp
Nov 15 '18 at 15:56

That's the thing. I also tried df = df.loc[(df['Date'].dt.month == 10) & (df['Date'].dt.month == 4)] and I get the same result and I know 10 and 4 exist.

– HelloToEarth
Nov 15 '18 at 15:58

@jpp pandas will select rows which satisfy either of these column conditions, they don't have to be satisfied simultaneously...

– Dascienz
Nov 15 '18 at 16:02

@jpp, Oh duh, he needs a |, my bad! Haha, really embarrassing.

– Dascienz
Nov 15 '18 at 16:03

Hey @HelloToEarth, | is an OR operator which means that pandas will select rows which satisfy either condition, however, when you use & which is an AND operator it means that both conditions must be satisfied simultaneously. You can't have a month be greater than 10 and less than 4 at the same time, nor can you have a month that is both equal to 4 and 10 at the same time. Therefore, you need to use the OR operator, |.

– Dascienz
Nov 15 '18 at 16:09

|
show 3 more comments

1 Answer
1

active

oldest

votes

Try slicing without the use of .loc:

df = df[(df['Date'].dt.month > 10) | (df['Date'].dt.month < 4)]

edited Nov 15 '18 at 16:03

answered Nov 15 '18 at 15:57

Dascienz

610412

This is incorrect. The problem is a typo, see comments to the question.

– jpp
Nov 15 '18 at 15:58

@jpp Edited my answer, thanks!

– Dascienz
Nov 15 '18 at 16:04

add a comment |

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1 Answer
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1 Answer
1

active

oldest

votes

Try slicing without the use of .loc:

df = df[(df['Date'].dt.month > 10) | (df['Date'].dt.month < 4)]

edited Nov 15 '18 at 16:03

answered Nov 15 '18 at 15:57

Dascienz

610412

This is incorrect. The problem is a typo, see comments to the question.

– jpp
Nov 15 '18 at 15:58

@jpp Edited my answer, thanks!

– Dascienz
Nov 15 '18 at 16:04

add a comment |

Try slicing without the use of .loc:

df = df[(df['Date'].dt.month > 10) | (df['Date'].dt.month < 4)]

edited Nov 15 '18 at 16:03

answered Nov 15 '18 at 15:57

Dascienz

610412

This is incorrect. The problem is a typo, see comments to the question.

– jpp
Nov 15 '18 at 15:58

@jpp Edited my answer, thanks!

– Dascienz
Nov 15 '18 at 16:04

add a comment |

Try slicing without the use of .loc:

df = df[(df['Date'].dt.month > 10) | (df['Date'].dt.month < 4)]

edited Nov 15 '18 at 16:03

answered Nov 15 '18 at 15:57

Dascienz

610412

Try slicing without the use of .loc:

df = df[(df['Date'].dt.month > 10) | (df['Date'].dt.month < 4)]

edited Nov 15 '18 at 16:03

answered Nov 15 '18 at 15:57

Dascienz

610412

edited Nov 15 '18 at 16:03

answered Nov 15 '18 at 15:57

Dascienz

610412

answered Nov 15 '18 at 15:57

Dascienz

610412

answered Nov 15 '18 at 15:57

Dascienz

610412

This is incorrect. The problem is a typo, see comments to the question.

– jpp
Nov 15 '18 at 15:58

@jpp Edited my answer, thanks!

– Dascienz
Nov 15 '18 at 16:04

add a comment |

This is incorrect. The problem is a typo, see comments to the question.

– jpp
Nov 15 '18 at 15:58

@jpp Edited my answer, thanks!

– Dascienz
Nov 15 '18 at 16:04

This is incorrect. The problem is a typo, see comments to the question.

– jpp
Nov 15 '18 at 15:58

@jpp Edited my answer, thanks!

– Dascienz
Nov 15 '18 at 16:04

add a comment |

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