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I have a pretty large nested dictionary that has some missing values and I am trying to replace these values with values from 7 rows before it if it fits a certain condition. ffill doesn't help because it only fills with the previous value, so I tried without pandas. I'm very sure it is wrong but I honestly dont know what to do. Point of note: the [key] is a string containing a date: '2018-01-11'.
So I am pretty much trying to replace the values of the date with values from the same day but for the previous week.

All help will be appreciated

ideal= (24*60*60)/10
for day, values in (n_dict[house].items()):
 count=len(values)
 percentage_complete = (count/ideal_data) *100
 if percentage_complete < 80:
 n_dict.replace(n_dict[house][key], n_dict[house][key-7])
 print(house, ',',day, ',',percentage_complete)

python-3.x dataframe

share|improve this question

asked Mar 25 at 12:29

BuzbuzBuzbuz

111 bronze badge

add a comment | 

0

I have a pretty large nested dictionary that has some missing values and I am trying to replace these values with values from 7 rows before it if it fits a certain condition. ffill doesn't help because it only fills with the previous value, so I tried without pandas. I'm very sure it is wrong but I honestly dont know what to do. Point of note: the [key] is a string containing a date: '2018-01-11'.
So I am pretty much trying to replace the values of the date with values from the same day but for the previous week.

All help will be appreciated

ideal= (24*60*60)/10
for day, values in (n_dict[house].items()):
 count=len(values)
 percentage_complete = (count/ideal_data) *100
 if percentage_complete < 80:
 n_dict.replace(n_dict[house][key], n_dict[house][key-7])
 print(house, ',',day, ',',percentage_complete)

python-3.x dataframe

share|improve this question

asked Mar 25 at 12:29

BuzbuzBuzbuz

111 bronze badge

add a comment | 

I have a pretty large nested dictionary that has some missing values and I am trying to replace these values with values from 7 rows before it if it fits a certain condition. ffill doesn't help because it only fills with the previous value, so I tried without pandas. I'm very sure it is wrong but I honestly dont know what to do. Point of note: the [key] is a string containing a date: '2018-01-11'.
So I am pretty much trying to replace the values of the date with values from the same day but for the previous week.

All help will be appreciated

ideal= (24*60*60)/10
for day, values in (n_dict[house].items()):
 count=len(values)
 percentage_complete = (count/ideal_data) *100
 if percentage_complete < 80:
 n_dict.replace(n_dict[house][key], n_dict[house][key-7])
 print(house, ',',day, ',',percentage_complete)

python-3.x dataframe

share|improve this question

asked Mar 25 at 12:29

BuzbuzBuzbuz

111 bronze badge

ideal= (24*60*60)/10
for day, values in (n_dict[house].items()):
 count=len(values)
 percentage_complete = (count/ideal_data) *100
 if percentage_complete < 80:
 n_dict.replace(n_dict[house][key], n_dict[house][key-7])
 print(house, ',',day, ',',percentage_complete)

share|improve this question

asked Mar 25 at 12:29

BuzbuzBuzbuz

111 bronze badge

share|improve this question

asked Mar 25 at 12:29

BuzbuzBuzbuz

111 bronze badge

asked Mar 25 at 12:29

BuzbuzBuzbuz

111 bronze badge

asked Mar 25 at 12:29

BuzbuzBuzbuz

111 bronze badge