ValueError when using pandas date_range in for loop
0
I have an original dataset with projects containing data about its start date, end date, total value. I calculate dayvalue (dagwaarde) by dividing total value with amount of days.
I want to fill a dataset with data 1-1-2018 to 1-1-2020 with the sum of all day values of all projects for each day.
It all works, except for this piece:
df_date_range = pd.date_range(begin,einde)
which give this error: ValueError: NaTType does not support time
This is the code I use:
#Original DF with data about projects: startdatum (start), einddatum (end), dagwaarde (day value).
#Day value is total value ('Value') / amount of days
Pipedrive['einddatum'] = pd.to_datetime(Pipedrive['einddatum'])
Pipedrive['startdatum'] = pd.to_datetime(Pipedrive['startdatum'])
Pipedrive['Days'] = Pipedrive['einddatum'].sub(Pipedrive['startdatum'], axis =0)
Pipedrive.head()
Pipedrive['Days'] = Pipedrive['Days'] / np.timedelta64(1, 'D')
Pipedrive['dagwaarde'] = Pipedrive['Value'] / Pipedrive['Days']
#Create DF to work with
Pipedrive_IN = Pipedrive[["stage_order_nr","dagwaarde",'einddatum', 'startdatum', 'Days' ]]
#make a list of all begin and end dates you want to have filled
begin = '2018-01-01' # start date
einde = '2020-01-01' # end date
#make a DF with a timedate index
datetimeindex = pd.date_range(begin,einde)
df_dates = pd.DataFrame(datetimeindex, columns=['date'])
df_dates = df_dates.set_index('date')
df_dates = df_dates.fillna(0)
for index, value in Pipedrive_IN.iterrows():
begin = value.startdatum # start date
einde = value.einddatum # end date
dagwaarde = value.dagwaarde # dagwaarde
#make DF with timedate index
df_date_range = pd.date_range(begin,einde)
df_proj = pd.DataFrame(df_date_range, columns=['date'])
df_proj['dagwaarde'] = dagwaarde
df_proj = df_proj.set_index('date')
df_proj=df_proj.dropna()
print(df_proj.head())
#add original DF to df_dates
df_dates = df_dates.join(df_proj,lsuffix='', rsuffix=index)
df_dates = df_dates.fillna(0)
print(df_dates.head(20))
#print result
df_dates['total']=df_dates.sum(axis=1)
print(df_dates.head(50))
python-3.x pandas for-loop date-range
asked Dec 28 '18 at 7:34
MikeMike
15
add a comment |
0
I have an original dataset with projects containing data about its start date, end date, total value. I calculate dayvalue (dagwaarde) by dividing total value with amount of days.
I want to fill a dataset with data 1-1-2018 to 1-1-2020 with the sum of all day values of all projects for each day.
It all works, except for this piece:
df_date_range = pd.date_range(begin,einde)
which give this error: ValueError: NaTType does not support time
This is the code I use:
#Original DF with data about projects: startdatum (start), einddatum (end), dagwaarde (day value).
#Day value is total value ('Value') / amount of days
Pipedrive['einddatum'] = pd.to_datetime(Pipedrive['einddatum'])
Pipedrive['startdatum'] = pd.to_datetime(Pipedrive['startdatum'])
Pipedrive['Days'] = Pipedrive['einddatum'].sub(Pipedrive['startdatum'], axis =0)
Pipedrive.head()
Pipedrive['Days'] = Pipedrive['Days'] / np.timedelta64(1, 'D')
Pipedrive['dagwaarde'] = Pipedrive['Value'] / Pipedrive['Days']
#Create DF to work with
Pipedrive_IN = Pipedrive[["stage_order_nr","dagwaarde",'einddatum', 'startdatum', 'Days' ]]
#make a list of all begin and end dates you want to have filled
begin = '2018-01-01' # start date
einde = '2020-01-01' # end date
#make a DF with a timedate index
datetimeindex = pd.date_range(begin,einde)
df_dates = pd.DataFrame(datetimeindex, columns=['date'])
df_dates = df_dates.set_index('date')
df_dates = df_dates.fillna(0)
for index, value in Pipedrive_IN.iterrows():
begin = value.startdatum # start date
einde = value.einddatum # end date
dagwaarde = value.dagwaarde # dagwaarde
#make DF with timedate index
df_date_range = pd.date_range(begin,einde)
df_proj = pd.DataFrame(df_date_range, columns=['date'])
df_proj['dagwaarde'] = dagwaarde
df_proj = df_proj.set_index('date')
df_proj=df_proj.dropna()
print(df_proj.head())
#add original DF to df_dates
df_dates = df_dates.join(df_proj,lsuffix='', rsuffix=index)
df_dates = df_dates.fillna(0)
print(df_dates.head(20))
#print result
df_dates['total']=df_dates.sum(axis=1)
print(df_dates.head(50))
python-3.x pandas for-loop date-range
asked Dec 28 '18 at 7:34
MikeMike
15
add a comment |
0
0
0
1
I have an original dataset with projects containing data about its start date, end date, total value. I calculate dayvalue (dagwaarde) by dividing total value with amount of days.
I want to fill a dataset with data 1-1-2018 to 1-1-2020 with the sum of all day values of all projects for each day.
It all works, except for this piece:
df_date_range = pd.date_range(begin,einde)
which give this error: ValueError: NaTType does not support time
This is the code I use:
#Original DF with data about projects: startdatum (start), einddatum (end), dagwaarde (day value).
#Day value is total value ('Value') / amount of days
Pipedrive['einddatum'] = pd.to_datetime(Pipedrive['einddatum'])
Pipedrive['startdatum'] = pd.to_datetime(Pipedrive['startdatum'])
Pipedrive['Days'] = Pipedrive['einddatum'].sub(Pipedrive['startdatum'], axis =0)
Pipedrive.head()
Pipedrive['Days'] = Pipedrive['Days'] / np.timedelta64(1, 'D')
Pipedrive['dagwaarde'] = Pipedrive['Value'] / Pipedrive['Days']
#Create DF to work with
Pipedrive_IN = Pipedrive[["stage_order_nr","dagwaarde",'einddatum', 'startdatum', 'Days' ]]
#make a list of all begin and end dates you want to have filled
begin = '2018-01-01' # start date
einde = '2020-01-01' # end date
#make a DF with a timedate index
datetimeindex = pd.date_range(begin,einde)
df_dates = pd.DataFrame(datetimeindex, columns=['date'])
df_dates = df_dates.set_index('date')
df_dates = df_dates.fillna(0)
for index, value in Pipedrive_IN.iterrows():
begin = value.startdatum # start date
einde = value.einddatum # end date
dagwaarde = value.dagwaarde # dagwaarde
#make DF with timedate index
df_date_range = pd.date_range(begin,einde)
df_proj = pd.DataFrame(df_date_range, columns=['date'])
df_proj['dagwaarde'] = dagwaarde
df_proj = df_proj.set_index('date')
df_proj=df_proj.dropna()
print(df_proj.head())
#add original DF to df_dates
df_dates = df_dates.join(df_proj,lsuffix='', rsuffix=index)
df_dates = df_dates.fillna(0)
print(df_dates.head(20))
#print result
df_dates['total']=df_dates.sum(axis=1)
print(df_dates.head(50))
python-3.x pandas for-loop date-range
asked Dec 28 '18 at 7:34
MikeMike
15
I have an original dataset with projects containing data about its start date, end date, total value. I calculate dayvalue (dagwaarde) by dividing total value with amount of days.
I want to fill a dataset with data 1-1-2018 to 1-1-2020 with the sum of all day values of all projects for each day.
It all works, except for this piece:
df_date_range = pd.date_range(begin,einde)
which give this error: ValueError: NaTType does not support time
This is the code I use:
#Original DF with data about projects: startdatum (start), einddatum (end), dagwaarde (day value).
#Day value is total value ('Value') / amount of days
Pipedrive['einddatum'] = pd.to_datetime(Pipedrive['einddatum'])
Pipedrive['startdatum'] = pd.to_datetime(Pipedrive['startdatum'])
Pipedrive['Days'] = Pipedrive['einddatum'].sub(Pipedrive['startdatum'], axis =0)
Pipedrive.head()
Pipedrive['Days'] = Pipedrive['Days'] / np.timedelta64(1, 'D')
Pipedrive['dagwaarde'] = Pipedrive['Value'] / Pipedrive['Days']
#Create DF to work with
Pipedrive_IN = Pipedrive[["stage_order_nr","dagwaarde",'einddatum', 'startdatum', 'Days' ]]
#make a list of all begin and end dates you want to have filled
begin = '2018-01-01' # start date
einde = '2020-01-01' # end date
#make a DF with a timedate index
datetimeindex = pd.date_range(begin,einde)
df_dates = pd.DataFrame(datetimeindex, columns=['date'])
df_dates = df_dates.set_index('date')
df_dates = df_dates.fillna(0)
for index, value in Pipedrive_IN.iterrows():
begin = value.startdatum # start date
einde = value.einddatum # end date
dagwaarde = value.dagwaarde # dagwaarde
#make DF with timedate index
df_date_range = pd.date_range(begin,einde)
df_proj = pd.DataFrame(df_date_range, columns=['date'])
df_proj['dagwaarde'] = dagwaarde
df_proj = df_proj.set_index('date')
df_proj=df_proj.dropna()
print(df_proj.head())
#add original DF to df_dates
df_dates = df_dates.join(df_proj,lsuffix='', rsuffix=index)
df_dates = df_dates.fillna(0)
print(df_dates.head(20))
#print result
df_dates['total']=df_dates.sum(axis=1)
print(df_dates.head(50))
python-3.x pandas for-loop date-range
python-3.x pandas for-loop date-range
asked Dec 28 '18 at 7:34
MikeMike
15
asked Dec 28 '18 at 7:34
MikeMike
15
asked Dec 28 '18 at 7:34
MikeMike
15
asked Dec 28 '18 at 7:34
MikeMike
15
asked Dec 28 '18 at 7:34
MikeMike
15
15
add a comment |
add a comment |
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