statsmodel.SARIMAX .forecast() method do not execute
I am trying to use SARIMAX model for TS forecasting. However, I got some kind of error i dont know how to handle. My code is simple:
import statsmodels.api as sm
fit = sm.tsa.statespace.SARIMAX(train).fit()
sarima = fit.forecast()
train data looks like
y
ds
2015-01-07 1
2015-01-14 64
2015-01-21 16
2015-01-28 50
2015-02-04 7
I got the error
/usr/local/lib/python3.6/dist-packages/statsmodels/tsa/base/datetools.py in
_date_from_idx(d1, idx, freq)
84 offset. For now, this needs to be taken care of before you get
here.
85 """
---> 86 return _maybe_convert_period(d1) + int(idx) *
_freq_to_pandas[freq]
87
88
TypeError: unsupported operand type(s) for *: 'int' and 'NoneType'
Any ideas what I am doing wrong?
python statsmodels
asked Nov 23 '18 at 15:06
NekitNekit
1
add a comment |
I am trying to use SARIMAX model for TS forecasting. However, I got some kind of error i dont know how to handle. My code is simple:
import statsmodels.api as sm
fit = sm.tsa.statespace.SARIMAX(train).fit()
sarima = fit.forecast()
train data looks like
y
ds
2015-01-07 1
2015-01-14 64
2015-01-21 16
2015-01-28 50
2015-02-04 7
I got the error
/usr/local/lib/python3.6/dist-packages/statsmodels/tsa/base/datetools.py in
_date_from_idx(d1, idx, freq)
84 offset. For now, this needs to be taken care of before you get
here.
85 """
---> 86 return _maybe_convert_period(d1) + int(idx) *
_freq_to_pandas[freq]
87
88
TypeError: unsupported operand type(s) for *: 'int' and 'NoneType'
Any ideas what I am doing wrong?
python statsmodels
asked Nov 23 '18 at 15:06
NekitNekit
1
What is your desired output, the model summary, a plot, or just y hat?
– W.Dodge
Nov 23 '18 at 15:25
@W.Dodge i just want forecast for 50 days, thats yhat
– Nekit
Nov 23 '18 at 15:57
Did you check that all your data is valid? Maybe some of the dates or y values are None. Are you getting this error when fitting or at prediction?
– zsomko
Nov 23 '18 at 16:11
add a comment |
I am trying to use SARIMAX model for TS forecasting. However, I got some kind of error i dont know how to handle. My code is simple:
import statsmodels.api as sm
fit = sm.tsa.statespace.SARIMAX(train).fit()
sarima = fit.forecast()
train data looks like
y
ds
2015-01-07 1
2015-01-14 64
2015-01-21 16
2015-01-28 50
2015-02-04 7
I got the error
/usr/local/lib/python3.6/dist-packages/statsmodels/tsa/base/datetools.py in
_date_from_idx(d1, idx, freq)
84 offset. For now, this needs to be taken care of before you get
here.
85 """
---> 86 return _maybe_convert_period(d1) + int(idx) *
_freq_to_pandas[freq]
87
88
TypeError: unsupported operand type(s) for *: 'int' and 'NoneType'
Any ideas what I am doing wrong?
python statsmodels
asked Nov 23 '18 at 15:06
NekitNekit
1
I am trying to use SARIMAX model for TS forecasting. However, I got some kind of error i dont know how to handle. My code is simple:
import statsmodels.api as sm
fit = sm.tsa.statespace.SARIMAX(train).fit()
sarima = fit.forecast()
train data looks like
y
ds
2015-01-07 1
2015-01-14 64
2015-01-21 16
2015-01-28 50
2015-02-04 7
I got the error
/usr/local/lib/python3.6/dist-packages/statsmodels/tsa/base/datetools.py in
_date_from_idx(d1, idx, freq)
84 offset. For now, this needs to be taken care of before you get
here.
85 """
---> 86 return _maybe_convert_period(d1) + int(idx) *
_freq_to_pandas[freq]
87
88
TypeError: unsupported operand type(s) for *: 'int' and 'NoneType'
Any ideas what I am doing wrong?
python statsmodels
python statsmodels
asked Nov 23 '18 at 15:06
NekitNekit
1
asked Nov 23 '18 at 15:06
NekitNekit
1
asked Nov 23 '18 at 15:06
NekitNekit
1
asked Nov 23 '18 at 15:06
NekitNekit
1
asked Nov 23 '18 at 15:06
NekitNekit
1
1
What is your desired output, the model summary, a plot, or just y hat?
– W.Dodge
Nov 23 '18 at 15:25
@W.Dodge i just want forecast for 50 days, thats yhat
– Nekit
Nov 23 '18 at 15:57
Did you check that all your data is valid? Maybe some of the dates or y values are None. Are you getting this error when fitting or at prediction?
– zsomko
Nov 23 '18 at 16:11
add a comment |
What is your desired output, the model summary, a plot, or just y hat?
– W.Dodge
Nov 23 '18 at 15:25
@W.Dodge i just want forecast for 50 days, thats yhat
– Nekit
Nov 23 '18 at 15:57
Did you check that all your data is valid? Maybe some of the dates or y values are None. Are you getting this error when fitting or at prediction?
– zsomko
Nov 23 '18 at 16:11
What is your desired output, the model summary, a plot, or just y hat?
– W.Dodge
Nov 23 '18 at 15:25
What is your desired output, the model summary, a plot, or just y hat?
– W.Dodge
Nov 23 '18 at 15:25
@W.Dodge i just want forecast for 50 days, thats yhat
– Nekit
Nov 23 '18 at 15:57
@W.Dodge i just want forecast for 50 days, thats yhat
– Nekit
Nov 23 '18 at 15:57
Did you check that all your data is valid? Maybe some of the dates or y values are None. Are you getting this error when fitting or at prediction?
– zsomko
Nov 23 '18 at 16:11
Did you check that all your data is valid? Maybe some of the dates or y values are None. Are you getting this error when fitting or at prediction?
– zsomko
Nov 23 '18 at 16:11
add a comment |
1 Answer
1
active
oldest
votes
SARIMA is a fairly complex moving average predictive model with many parameters and nuances. You will need to research the details of this approach extensively to be sure that you are utilizing this appropriately. For the sake of simply implementing the model to obtain a result, the following example should help:
Code:
import matplotlib.pyplot as plt
import statsmodels.api as sm
import numpy as np
np.random.seed(100)
data = np.sort(np.random.uniform(0, 1, size=30))
steps_to_predict = 5
model = sm.tsa.statespace.SARIMAX(endog=data,order=(2,0,0),enforce_stationarity=False)
sarima = model.fit()
print(sarima.summary())
# plot
fig, ax = plt.subplots(1,1, figsize=(20,10))
ax.set_xlim(0,40)
ax.plot(train, "ro-", linewidth=2, markersize=12)
ax.plot(list(range(30,35)), sarima.forecast(steps_to_predict), "bo-", linewidth=2, markersize=12)
Output:
*** Note that the observed data is red and the predicted steps are blue.
answered Nov 23 '18 at 16:52
W.DodgeW.Dodge
1,3691921
1
thanks for answer!
– Nekit
Nov 23 '18 at 18:34
add a comment |
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1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
SARIMA is a fairly complex moving average predictive model with many parameters and nuances. You will need to research the details of this approach extensively to be sure that you are utilizing this appropriately. For the sake of simply implementing the model to obtain a result, the following example should help:
Code:
import matplotlib.pyplot as plt
import statsmodels.api as sm
import numpy as np
np.random.seed(100)
data = np.sort(np.random.uniform(0, 1, size=30))
steps_to_predict = 5
model = sm.tsa.statespace.SARIMAX(endog=data,order=(2,0,0),enforce_stationarity=False)
sarima = model.fit()
print(sarima.summary())
# plot
fig, ax = plt.subplots(1,1, figsize=(20,10))
ax.set_xlim(0,40)
ax.plot(train, "ro-", linewidth=2, markersize=12)
ax.plot(list(range(30,35)), sarima.forecast(steps_to_predict), "bo-", linewidth=2, markersize=12)
Output:
*** Note that the observed data is red and the predicted steps are blue.
answered Nov 23 '18 at 16:52
W.DodgeW.Dodge
1,3691921
1
thanks for answer!
– Nekit
Nov 23 '18 at 18:34
add a comment |
SARIMA is a fairly complex moving average predictive model with many parameters and nuances. You will need to research the details of this approach extensively to be sure that you are utilizing this appropriately. For the sake of simply implementing the model to obtain a result, the following example should help:
Code:
import matplotlib.pyplot as plt
import statsmodels.api as sm
import numpy as np
np.random.seed(100)
data = np.sort(np.random.uniform(0, 1, size=30))
steps_to_predict = 5
model = sm.tsa.statespace.SARIMAX(endog=data,order=(2,0,0),enforce_stationarity=False)
sarima = model.fit()
print(sarima.summary())
# plot
fig, ax = plt.subplots(1,1, figsize=(20,10))
ax.set_xlim(0,40)
ax.plot(train, "ro-", linewidth=2, markersize=12)
ax.plot(list(range(30,35)), sarima.forecast(steps_to_predict), "bo-", linewidth=2, markersize=12)
Output:
*** Note that the observed data is red and the predicted steps are blue.
answered Nov 23 '18 at 16:52
W.DodgeW.Dodge
1,3691921
1
thanks for answer!
– Nekit
Nov 23 '18 at 18:34
add a comment |
SARIMA is a fairly complex moving average predictive model with many parameters and nuances. You will need to research the details of this approach extensively to be sure that you are utilizing this appropriately. For the sake of simply implementing the model to obtain a result, the following example should help:
Code:
import matplotlib.pyplot as plt
import statsmodels.api as sm
import numpy as np
np.random.seed(100)
data = np.sort(np.random.uniform(0, 1, size=30))
steps_to_predict = 5
model = sm.tsa.statespace.SARIMAX(endog=data,order=(2,0,0),enforce_stationarity=False)
sarima = model.fit()
print(sarima.summary())
# plot
fig, ax = plt.subplots(1,1, figsize=(20,10))
ax.set_xlim(0,40)
ax.plot(train, "ro-", linewidth=2, markersize=12)
ax.plot(list(range(30,35)), sarima.forecast(steps_to_predict), "bo-", linewidth=2, markersize=12)
Output:
*** Note that the observed data is red and the predicted steps are blue.
answered Nov 23 '18 at 16:52
W.DodgeW.Dodge
1,3691921
SARIMA is a fairly complex moving average predictive model with many parameters and nuances. You will need to research the details of this approach extensively to be sure that you are utilizing this appropriately. For the sake of simply implementing the model to obtain a result, the following example should help:
Code:
import matplotlib.pyplot as plt
import statsmodels.api as sm
import numpy as np
np.random.seed(100)
data = np.sort(np.random.uniform(0, 1, size=30))
steps_to_predict = 5
model = sm.tsa.statespace.SARIMAX(endog=data,order=(2,0,0),enforce_stationarity=False)
sarima = model.fit()
print(sarima.summary())
# plot
fig, ax = plt.subplots(1,1, figsize=(20,10))
ax.set_xlim(0,40)
ax.plot(train, "ro-", linewidth=2, markersize=12)
ax.plot(list(range(30,35)), sarima.forecast(steps_to_predict), "bo-", linewidth=2, markersize=12)
Output:
*** Note that the observed data is red and the predicted steps are blue.
answered Nov 23 '18 at 16:52
W.DodgeW.Dodge
1,3691921
edited Nov 23 '18 at 23:27
answered Nov 23 '18 at 16:52
W.DodgeW.Dodge
1,3691921
answered Nov 23 '18 at 16:52
W.DodgeW.Dodge
1,3691921
answered Nov 23 '18 at 16:52
W.DodgeW.Dodge
1,3691921
1,3691921
1
thanks for answer!
– Nekit
Nov 23 '18 at 18:34
add a comment |
1
thanks for answer!
– Nekit
Nov 23 '18 at 18:34
1
1
thanks for answer!
– Nekit
Nov 23 '18 at 18:34
thanks for answer!
– Nekit
Nov 23 '18 at 18:34
add a comment |
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What is your desired output, the model summary, a plot, or just y hat?
– W.Dodge
Nov 23 '18 at 15:25
@W.Dodge i just want forecast for 50 days, thats yhat
– Nekit
Nov 23 '18 at 15:57
Did you check that all your data is valid? Maybe some of the dates or y values are None. Are you getting this error when fitting or at prediction?
– zsomko
Nov 23 '18 at 16:11