Mixing
Python: upsampling dataframe from daily to hourly data using ffill()
2
I'm trying to upsample my data from daily to hourly frequency and forward fill missing data.
I start with the following code:
df1 = pd.read_csv("DATA.csv")
df1.head(5)
I then used the following to convert to a datetime string and set the date/time as an index:
df1['DT'] = pd.to_datetime(df1['DT']).dt.strftime('%Y-%m-%d %H:%M:%S')
df1.set_index('DT')
I try to resample hourly as follows:
df1['DT'] = df1.resample('H').ffill()
But I get the following error:
TypeError: Only valid with DatetimeIndex, TimedeltaIndex or
PeriodIndex, but got an instance of 'RangeIndex'
I thought my dtype was already date time as instructed by the pd.to_datetime code above. Nothing I try seems to be working. Can anyone please help me?
My expected output is as follows:
DT VALUE
2016-08-01 00:00:00 0.000000
2016-08-01 01:00:00 0.000000
2016-08-01 02:00:00 0.000000
etc.
The file itself has approximately 1000 rows. The first 50 rows or so are zero so to clarify where there's actual data:
DT VALUE
2018-12-13 00:00:00 24000.000000
2018-12-13 01:00:00 24000.000000
2018-12-13 02:00:00 24000.000000
...
2018-12-13 23:00:00 24000.000000
2018-12-14 00:00:00 26000.000000
2018-12-14 01:00:00 26000.000000
etc.
python pandas
asked Jan 2 at 17:47
GJBGJB
233
add a comment |
2
I'm trying to upsample my data from daily to hourly frequency and forward fill missing data.
I start with the following code:
df1 = pd.read_csv("DATA.csv")
df1.head(5)
I then used the following to convert to a datetime string and set the date/time as an index:
df1['DT'] = pd.to_datetime(df1['DT']).dt.strftime('%Y-%m-%d %H:%M:%S')
df1.set_index('DT')
I try to resample hourly as follows:
df1['DT'] = df1.resample('H').ffill()
But I get the following error:
TypeError: Only valid with DatetimeIndex, TimedeltaIndex or
PeriodIndex, but got an instance of 'RangeIndex'
I thought my dtype was already date time as instructed by the pd.to_datetime code above. Nothing I try seems to be working. Can anyone please help me?
My expected output is as follows:
DT VALUE
2016-08-01 00:00:00 0.000000
2016-08-01 01:00:00 0.000000
2016-08-01 02:00:00 0.000000
etc.
The file itself has approximately 1000 rows. The first 50 rows or so are zero so to clarify where there's actual data:
DT VALUE
2018-12-13 00:00:00 24000.000000
2018-12-13 01:00:00 24000.000000
2018-12-13 02:00:00 24000.000000
...
2018-12-13 23:00:00 24000.000000
2018-12-14 00:00:00 26000.000000
2018-12-14 01:00:00 26000.000000
etc.
python pandas
asked Jan 2 at 17:47
GJBGJB
233
Mention your expected output.
– Abdur Rehman
Jan 2 at 18:14
@AbdurRehman Thanks for your comment, I've updated the original.
– GJB
Jan 2 at 18:28
Mentioncolumn_nameson data to make it more clear. Your actual data has year2018and your expected data has year2016.Is it right or mistyped ?
– Abdur Rehman
Jan 2 at 18:44
Thanks Abdur, I've updated the column names. There's about 3 years worth of data, preceded by mostly zeros. I've clarified it in the question.
– GJB
Jan 2 at 18:49
add a comment |
2
2
2
I'm trying to upsample my data from daily to hourly frequency and forward fill missing data.
I start with the following code:
df1 = pd.read_csv("DATA.csv")
df1.head(5)
I then used the following to convert to a datetime string and set the date/time as an index:
df1['DT'] = pd.to_datetime(df1['DT']).dt.strftime('%Y-%m-%d %H:%M:%S')
df1.set_index('DT')
I try to resample hourly as follows:
df1['DT'] = df1.resample('H').ffill()
But I get the following error:
TypeError: Only valid with DatetimeIndex, TimedeltaIndex or
PeriodIndex, but got an instance of 'RangeIndex'
I thought my dtype was already date time as instructed by the pd.to_datetime code above. Nothing I try seems to be working. Can anyone please help me?
My expected output is as follows:
DT VALUE
2016-08-01 00:00:00 0.000000
2016-08-01 01:00:00 0.000000
2016-08-01 02:00:00 0.000000
etc.
The file itself has approximately 1000 rows. The first 50 rows or so are zero so to clarify where there's actual data:
DT VALUE
2018-12-13 00:00:00 24000.000000
2018-12-13 01:00:00 24000.000000
2018-12-13 02:00:00 24000.000000
...
2018-12-13 23:00:00 24000.000000
2018-12-14 00:00:00 26000.000000
2018-12-14 01:00:00 26000.000000
etc.
python pandas
asked Jan 2 at 17:47
GJBGJB
233
I'm trying to upsample my data from daily to hourly frequency and forward fill missing data.
I start with the following code:
df1 = pd.read_csv("DATA.csv")
df1.head(5)
I then used the following to convert to a datetime string and set the date/time as an index:
df1['DT'] = pd.to_datetime(df1['DT']).dt.strftime('%Y-%m-%d %H:%M:%S')
df1.set_index('DT')
I try to resample hourly as follows:
df1['DT'] = df1.resample('H').ffill()
But I get the following error:
TypeError: Only valid with DatetimeIndex, TimedeltaIndex or
PeriodIndex, but got an instance of 'RangeIndex'
I thought my dtype was already date time as instructed by the pd.to_datetime code above. Nothing I try seems to be working. Can anyone please help me?
My expected output is as follows:
DT VALUE
2016-08-01 00:00:00 0.000000
2016-08-01 01:00:00 0.000000
2016-08-01 02:00:00 0.000000
etc.
The file itself has approximately 1000 rows. The first 50 rows or so are zero so to clarify where there's actual data:
DT VALUE
2018-12-13 00:00:00 24000.000000
2018-12-13 01:00:00 24000.000000
2018-12-13 02:00:00 24000.000000
...
2018-12-13 23:00:00 24000.000000
2018-12-14 00:00:00 26000.000000
2018-12-14 01:00:00 26000.000000
etc.
python pandas
python pandas
asked Jan 2 at 17:47
GJBGJB
233
asked Jan 2 at 17:47
GJBGJB
233
edited Jan 2 at 18:48
GJB
asked Jan 2 at 17:47
GJBGJB
233
asked Jan 2 at 17:47
GJBGJB
233
asked Jan 2 at 17:47
GJBGJB
233
233
Mention your expected output.
– Abdur Rehman
Jan 2 at 18:14
@AbdurRehman Thanks for your comment, I've updated the original.
– GJB
Jan 2 at 18:28
Mentioncolumn_nameson data to make it more clear. Your actual data has year2018and your expected data has year2016.Is it right or mistyped ?
– Abdur Rehman
Jan 2 at 18:44
Thanks Abdur, I've updated the column names. There's about 3 years worth of data, preceded by mostly zeros. I've clarified it in the question.
– GJB
Jan 2 at 18:49
add a comment |
Mention your expected output.
– Abdur Rehman
Jan 2 at 18:14
@AbdurRehman Thanks for your comment, I've updated the original.
– GJB
Jan 2 at 18:28
Mentioncolumn_nameson data to make it more clear. Your actual data has year2018and your expected data has year2016.Is it right or mistyped ?
– Abdur Rehman
Jan 2 at 18:44
Thanks Abdur, I've updated the column names. There's about 3 years worth of data, preceded by mostly zeros. I've clarified it in the question.
– GJB
Jan 2 at 18:49
Mention your expected output.
– Abdur Rehman
Jan 2 at 18:14
Mention your expected output.
– Abdur Rehman
Jan 2 at 18:14
@AbdurRehman Thanks for your comment, I've updated the original.
– GJB
Jan 2 at 18:28
@AbdurRehman Thanks for your comment, I've updated the original.
– GJB
Jan 2 at 18:28
Mention
column_names on data to make it more clear. Your actual data has year 2018 and your expected data has year 2016.Is it right or mistyped ?– Abdur Rehman
Jan 2 at 18:44
Mention
column_names on data to make it more clear. Your actual data has year 2018 and your expected data has year 2016.Is it right or mistyped ?– Abdur Rehman
Jan 2 at 18:44
Thanks Abdur, I've updated the column names. There's about 3 years worth of data, preceded by mostly zeros. I've clarified it in the question.
– GJB
Jan 2 at 18:49
Thanks Abdur, I've updated the column names. There's about 3 years worth of data, preceded by mostly zeros. I've clarified it in the question.
– GJB
Jan 2 at 18:49
add a comment |
2 Answers
2
active
oldest
votes
0
Try assign it back
df1=df1.set_index('DT')
Or
df1.set_index('DT',inplace=True)
answered Jan 2 at 17:50
Wen-BenWen-Ben
121k83571
Hi W-B, thanks for your answer. I tried this out but unfortunately I'm still receiving the same error.
– GJB
Jan 2 at 18:01
df1.VALUE.resample('H').ffill() does this have errors @GJB
– Wen-Ben
Jan 2 at 18:10
I now get the issue AttributeError: 'DataFrame' object has no attribute 'VALUE'
– GJB
Jan 2 at 18:34
My mistake, I made a typo: TypeError: Only valid with DatetimeIndex, TimedeltaIndex or PeriodIndex, but got an instance of 'RangeIndex'
– GJB
Jan 2 at 18:42
add a comment |
0
I am assuming some initial rows of your dataset as you mentioned,
DT VALUE
0 2016-08-01 0
1 2016-08-02 0
2 2016-08-03 0
3 2016-08-04 0
4 2016-08-05 0
5 2016-08-06 0
6 2016-08-07 0
7 2016-08-08 0
8 2016-08-09 0
Then, make index on DT like this,
df = df.set_index('DT')
df
Output:
VALUE
DT
2016-08-01 0
2016-08-02 0
2016-08-03 0
2016-08-04 0
2016-08-05 0
2016-08-06 0
2016-08-07 0
2016-08-08 0
2016-08-09 0
Now, resample your dataframe,
df = df.resample('H').ffill()
df
Output: showing some initial values of output,
VALUE
DT
2016-08-01 00:00:00 0
2016-08-01 01:00:00 0
2016-08-01 02:00:00 0
2016-08-01 03:00:00 0
2016-08-01 04:00:00 0
2016-08-01 05:00:00 0
2016-08-01 06:00:00 0
2016-08-01 07:00:00 0
2016-08-01 08:00:00 0
2016-08-01 09:00:00 0
2016-08-01 10:00:00 0
answered Jan 2 at 18:59
Abdur RehmanAbdur Rehman
626511
@GJB let me know this worked for you or you have any other queries.
– Abdur Rehman
Jan 3 at 11:30
Hi Abdur, I got the following error: index must be monotonic increasing or decreasing
– GJB
Jan 4 at 11:40
I found the error- there was an errant NaN in the data right at the end. Many thanks Abdur.
– GJB
Jan 4 at 14:59
add a comment |
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2 Answers
2
active
oldest
votes
2 Answers
2
active
oldest
votes
active
oldest
votes
active
oldest
votes
0
Try assign it back
df1=df1.set_index('DT')
Or
df1.set_index('DT',inplace=True)
answered Jan 2 at 17:50
Wen-BenWen-Ben
121k83571
Hi W-B, thanks for your answer. I tried this out but unfortunately I'm still receiving the same error.
– GJB
Jan 2 at 18:01
df1.VALUE.resample('H').ffill() does this have errors @GJB
– Wen-Ben
Jan 2 at 18:10
I now get the issue AttributeError: 'DataFrame' object has no attribute 'VALUE'
– GJB
Jan 2 at 18:34
My mistake, I made a typo: TypeError: Only valid with DatetimeIndex, TimedeltaIndex or PeriodIndex, but got an instance of 'RangeIndex'
– GJB
Jan 2 at 18:42
add a comment |
0
Try assign it back
df1=df1.set_index('DT')
Or
df1.set_index('DT',inplace=True)
answered Jan 2 at 17:50
Wen-BenWen-Ben
121k83571
Hi W-B, thanks for your answer. I tried this out but unfortunately I'm still receiving the same error.
– GJB
Jan 2 at 18:01
df1.VALUE.resample('H').ffill() does this have errors @GJB
– Wen-Ben
Jan 2 at 18:10
I now get the issue AttributeError: 'DataFrame' object has no attribute 'VALUE'
– GJB
Jan 2 at 18:34
My mistake, I made a typo: TypeError: Only valid with DatetimeIndex, TimedeltaIndex or PeriodIndex, but got an instance of 'RangeIndex'
– GJB
Jan 2 at 18:42
add a comment |
0
0
0
Try assign it back
df1=df1.set_index('DT')
Or
df1.set_index('DT',inplace=True)
answered Jan 2 at 17:50
Wen-BenWen-Ben
121k83571
Try assign it back
df1=df1.set_index('DT')
Or
df1.set_index('DT',inplace=True)
answered Jan 2 at 17:50
Wen-BenWen-Ben
121k83571
answered Jan 2 at 17:50
Wen-BenWen-Ben
121k83571
answered Jan 2 at 17:50
Wen-BenWen-Ben
121k83571
answered Jan 2 at 17:50
Wen-BenWen-Ben
121k83571
121k83571
Hi W-B, thanks for your answer. I tried this out but unfortunately I'm still receiving the same error.
– GJB
Jan 2 at 18:01
df1.VALUE.resample('H').ffill() does this have errors @GJB
– Wen-Ben
Jan 2 at 18:10
I now get the issue AttributeError: 'DataFrame' object has no attribute 'VALUE'
– GJB
Jan 2 at 18:34
My mistake, I made a typo: TypeError: Only valid with DatetimeIndex, TimedeltaIndex or PeriodIndex, but got an instance of 'RangeIndex'
– GJB
Jan 2 at 18:42
add a comment |
Hi W-B, thanks for your answer. I tried this out but unfortunately I'm still receiving the same error.
– GJB
Jan 2 at 18:01
df1.VALUE.resample('H').ffill() does this have errors @GJB
– Wen-Ben
Jan 2 at 18:10
I now get the issue AttributeError: 'DataFrame' object has no attribute 'VALUE'
– GJB
Jan 2 at 18:34
My mistake, I made a typo: TypeError: Only valid with DatetimeIndex, TimedeltaIndex or PeriodIndex, but got an instance of 'RangeIndex'
– GJB
Jan 2 at 18:42
Hi W-B, thanks for your answer. I tried this out but unfortunately I'm still receiving the same error.
– GJB
Jan 2 at 18:01
Hi W-B, thanks for your answer. I tried this out but unfortunately I'm still receiving the same error.
– GJB
Jan 2 at 18:01
df1.VALUE.resample('H').ffill() does this have errors @GJB
– Wen-Ben
Jan 2 at 18:10
df1.VALUE.resample('H').ffill() does this have errors @GJB
– Wen-Ben
Jan 2 at 18:10
I now get the issue AttributeError: 'DataFrame' object has no attribute 'VALUE'
– GJB
Jan 2 at 18:34
I now get the issue AttributeError: 'DataFrame' object has no attribute 'VALUE'
– GJB
Jan 2 at 18:34
My mistake, I made a typo: TypeError: Only valid with DatetimeIndex, TimedeltaIndex or PeriodIndex, but got an instance of 'RangeIndex'
– GJB
Jan 2 at 18:42
My mistake, I made a typo: TypeError: Only valid with DatetimeIndex, TimedeltaIndex or PeriodIndex, but got an instance of 'RangeIndex'
– GJB
Jan 2 at 18:42
add a comment |
0
I am assuming some initial rows of your dataset as you mentioned,
DT VALUE
0 2016-08-01 0
1 2016-08-02 0
2 2016-08-03 0
3 2016-08-04 0
4 2016-08-05 0
5 2016-08-06 0
6 2016-08-07 0
7 2016-08-08 0
8 2016-08-09 0
Then, make index on DT like this,
df = df.set_index('DT')
df
Output:
VALUE
DT
2016-08-01 0
2016-08-02 0
2016-08-03 0
2016-08-04 0
2016-08-05 0
2016-08-06 0
2016-08-07 0
2016-08-08 0
2016-08-09 0
Now, resample your dataframe,
df = df.resample('H').ffill()
df
Output: showing some initial values of output,
VALUE
DT
2016-08-01 00:00:00 0
2016-08-01 01:00:00 0
2016-08-01 02:00:00 0
2016-08-01 03:00:00 0
2016-08-01 04:00:00 0
2016-08-01 05:00:00 0
2016-08-01 06:00:00 0
2016-08-01 07:00:00 0
2016-08-01 08:00:00 0
2016-08-01 09:00:00 0
2016-08-01 10:00:00 0
answered Jan 2 at 18:59
Abdur RehmanAbdur Rehman
626511
@GJB let me know this worked for you or you have any other queries.
– Abdur Rehman
Jan 3 at 11:30
Hi Abdur, I got the following error: index must be monotonic increasing or decreasing
– GJB
Jan 4 at 11:40
I found the error- there was an errant NaN in the data right at the end. Many thanks Abdur.
– GJB
Jan 4 at 14:59
add a comment |
0
I am assuming some initial rows of your dataset as you mentioned,
DT VALUE
0 2016-08-01 0
1 2016-08-02 0
2 2016-08-03 0
3 2016-08-04 0
4 2016-08-05 0
5 2016-08-06 0
6 2016-08-07 0
7 2016-08-08 0
8 2016-08-09 0
Then, make index on DT like this,
df = df.set_index('DT')
df
Output:
VALUE
DT
2016-08-01 0
2016-08-02 0
2016-08-03 0
2016-08-04 0
2016-08-05 0
2016-08-06 0
2016-08-07 0
2016-08-08 0
2016-08-09 0
Now, resample your dataframe,
df = df.resample('H').ffill()
df
Output: showing some initial values of output,
VALUE
DT
2016-08-01 00:00:00 0
2016-08-01 01:00:00 0
2016-08-01 02:00:00 0
2016-08-01 03:00:00 0
2016-08-01 04:00:00 0
2016-08-01 05:00:00 0
2016-08-01 06:00:00 0
2016-08-01 07:00:00 0
2016-08-01 08:00:00 0
2016-08-01 09:00:00 0
2016-08-01 10:00:00 0
answered Jan 2 at 18:59
Abdur RehmanAbdur Rehman
626511
@GJB let me know this worked for you or you have any other queries.
– Abdur Rehman
Jan 3 at 11:30
Hi Abdur, I got the following error: index must be monotonic increasing or decreasing
– GJB
Jan 4 at 11:40
I found the error- there was an errant NaN in the data right at the end. Many thanks Abdur.
– GJB
Jan 4 at 14:59
add a comment |
0
0
0
I am assuming some initial rows of your dataset as you mentioned,
DT VALUE
0 2016-08-01 0
1 2016-08-02 0
2 2016-08-03 0
3 2016-08-04 0
4 2016-08-05 0
5 2016-08-06 0
6 2016-08-07 0
7 2016-08-08 0
8 2016-08-09 0
Then, make index on DT like this,
df = df.set_index('DT')
df
Output:
VALUE
DT
2016-08-01 0
2016-08-02 0
2016-08-03 0
2016-08-04 0
2016-08-05 0
2016-08-06 0
2016-08-07 0
2016-08-08 0
2016-08-09 0
Now, resample your dataframe,
df = df.resample('H').ffill()
df
Output: showing some initial values of output,
VALUE
DT
2016-08-01 00:00:00 0
2016-08-01 01:00:00 0
2016-08-01 02:00:00 0
2016-08-01 03:00:00 0
2016-08-01 04:00:00 0
2016-08-01 05:00:00 0
2016-08-01 06:00:00 0
2016-08-01 07:00:00 0
2016-08-01 08:00:00 0
2016-08-01 09:00:00 0
2016-08-01 10:00:00 0
answered Jan 2 at 18:59
Abdur RehmanAbdur Rehman
626511
I am assuming some initial rows of your dataset as you mentioned,
DT VALUE
0 2016-08-01 0
1 2016-08-02 0
2 2016-08-03 0
3 2016-08-04 0
4 2016-08-05 0
5 2016-08-06 0
6 2016-08-07 0
7 2016-08-08 0
8 2016-08-09 0
Then, make index on DT like this,
df = df.set_index('DT')
df
Output:
VALUE
DT
2016-08-01 0
2016-08-02 0
2016-08-03 0
2016-08-04 0
2016-08-05 0
2016-08-06 0
2016-08-07 0
2016-08-08 0
2016-08-09 0
Now, resample your dataframe,
df = df.resample('H').ffill()
df
Output: showing some initial values of output,
VALUE
DT
2016-08-01 00:00:00 0
2016-08-01 01:00:00 0
2016-08-01 02:00:00 0
2016-08-01 03:00:00 0
2016-08-01 04:00:00 0
2016-08-01 05:00:00 0
2016-08-01 06:00:00 0
2016-08-01 07:00:00 0
2016-08-01 08:00:00 0
2016-08-01 09:00:00 0
2016-08-01 10:00:00 0
answered Jan 2 at 18:59
Abdur RehmanAbdur Rehman
626511
answered Jan 2 at 18:59
Abdur RehmanAbdur Rehman
626511
answered Jan 2 at 18:59
Abdur RehmanAbdur Rehman
626511
answered Jan 2 at 18:59
Abdur RehmanAbdur Rehman
626511
626511
@GJB let me know this worked for you or you have any other queries.
– Abdur Rehman
Jan 3 at 11:30
Hi Abdur, I got the following error: index must be monotonic increasing or decreasing
– GJB
Jan 4 at 11:40
I found the error- there was an errant NaN in the data right at the end. Many thanks Abdur.
– GJB
Jan 4 at 14:59
add a comment |
@GJB let me know this worked for you or you have any other queries.
– Abdur Rehman
Jan 3 at 11:30
Hi Abdur, I got the following error: index must be monotonic increasing or decreasing
– GJB
Jan 4 at 11:40
I found the error- there was an errant NaN in the data right at the end. Many thanks Abdur.
– GJB
Jan 4 at 14:59
@GJB let me know this worked for you or you have any other queries.
– Abdur Rehman
Jan 3 at 11:30
@GJB let me know this worked for you or you have any other queries.
– Abdur Rehman
Jan 3 at 11:30
Hi Abdur, I got the following error: index must be monotonic increasing or decreasing
– GJB
Jan 4 at 11:40
Hi Abdur, I got the following error: index must be monotonic increasing or decreasing
– GJB
Jan 4 at 11:40
I found the error- there was an errant NaN in the data right at the end. Many thanks Abdur.
– GJB
Jan 4 at 14:59
I found the error- there was an errant NaN in the data right at the end. Many thanks Abdur.
– GJB
Jan 4 at 14:59
add a comment |
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Mention your expected output.
– Abdur Rehman
Jan 2 at 18:14
@AbdurRehman Thanks for your comment, I've updated the original.
– GJB
Jan 2 at 18:28
Mention
column_nameson data to make it more clear. Your actual data has year2018and your expected data has year2016.Is it right or mistyped ?– Abdur Rehman
Jan 2 at 18:44
Thanks Abdur, I've updated the column names. There's about 3 years worth of data, preceded by mostly zeros. I've clarified it in the question.
– GJB
Jan 2 at 18:49