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?
python python-3.x python-2.7 pandas dataframe
asked Nov 15 '18 at 15:52
HelloToEarthHelloToEarth
537215
|
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?
python python-3.x python-2.7 pandas dataframe
asked Nov 15 '18 at 15:52
HelloToEarthHelloToEarth
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 trieddf = 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 anORoperator which means that pandas will select rows which satisfy either condition, however, when you use&which is anANDoperator 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 theORoperator,|.
– Dascienz
Nov 15 '18 at 16:09
|
show 3 more comments
-3
-3
-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?
python python-3.x python-2.7 pandas dataframe
asked Nov 15 '18 at 15:52
HelloToEarthHelloToEarth
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
python python-3.x python-2.7 pandas dataframe
asked Nov 15 '18 at 15:52
HelloToEarthHelloToEarth
537215
asked Nov 15 '18 at 15:52
HelloToEarthHelloToEarth
537215
asked Nov 15 '18 at 15:52
HelloToEarthHelloToEarth
537215
asked Nov 15 '18 at 15:52
HelloToEarthHelloToEarth
537215
asked Nov 15 '18 at 15:52
HelloToEarthHelloToEarth
537215
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 trieddf = 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 anORoperator which means that pandas will select rows which satisfy either condition, however, when you use&which is anANDoperator 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 theORoperator,|.
– 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 trieddf = 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 anORoperator which means that pandas will select rows which satisfy either condition, however, when you use&which is anANDoperator 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 theORoperator,|.
– Dascienz
Nov 15 '18 at 16:09
3
3
Typo: there are no integers greater than 10 AND less than 3.
– jpp
Nov 15 '18 at 15:56
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
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 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
2
@jpp, Oh duh, he needs a
|, my bad! Haha, really embarrassing.– Dascienz
Nov 15 '18 at 16:03
@jpp, Oh duh, he needs a
|, my bad! Haha, really embarrassing.– Dascienz
Nov 15 '18 at 16:03
1
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
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
1
Try slicing without the use of .loc:
df = df[(df['Date'].dt.month > 10) | (df['Date'].dt.month < 4)]
answered Nov 15 '18 at 15:57
DascienzDascienz
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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Try slicing without the use of .loc:
df = df[(df['Date'].dt.month > 10) | (df['Date'].dt.month < 4)]
answered Nov 15 '18 at 15:57
DascienzDascienz
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 |
1
Try slicing without the use of .loc:
df = df[(df['Date'].dt.month > 10) | (df['Date'].dt.month < 4)]
answered Nov 15 '18 at 15:57
DascienzDascienz
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 |
1
1
1
Try slicing without the use of .loc:
df = df[(df['Date'].dt.month > 10) | (df['Date'].dt.month < 4)]
answered Nov 15 '18 at 15:57
DascienzDascienz
610412
Try slicing without the use of .loc:
df = df[(df['Date'].dt.month > 10) | (df['Date'].dt.month < 4)]
answered Nov 15 '18 at 15:57
DascienzDascienz
610412
edited Nov 15 '18 at 16:03
answered Nov 15 '18 at 15:57
DascienzDascienz
610412
answered Nov 15 '18 at 15:57
DascienzDascienz
610412
answered Nov 15 '18 at 15:57
DascienzDascienz
610412
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
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
@jpp Edited my answer, thanks!
– Dascienz
Nov 15 '18 at 16:04
add a comment |
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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 anORoperator which means that pandas will select rows which satisfy either condition, however, when you use&which is anANDoperator 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 theORoperator,|.– Dascienz
Nov 15 '18 at 16:09