In [68]:
import pandas as pd
from fbprophet import Prophet
df = pd.read_csv('https://raw.githubusercontent.com/facebook/prophet/master/examples/example_wp_log_peyton_manning.csv')
df.head()
Out[68]:
| ds | y | |
|---|---|---|
| 0 | 2007-12-10 | 9.590761 |
| 1 | 2007-12-11 | 8.519590 |
| 2 | 2007-12-12 | 8.183677 |
| 3 | 2007-12-13 | 8.072467 |
| 4 | 2007-12-14 | 7.893572 |
PRACTICING WITH PEYTON¶
In [69]:
m = Prophet()
m.fit(df)
INFO:fbprophet:Disabling daily seasonality. Run prophet with daily_seasonality=True to override this.
Out[69]:
<fbprophet.forecaster.Prophet at 0x7f4f3ad41e80>
In [70]:
future = m.make_future_dataframe(periods=365)
future.tail()
Out[70]:
| ds | |
|---|---|
| 3265 | 2017-01-15 |
| 3266 | 2017-01-16 |
| 3267 | 2017-01-17 |
| 3268 | 2017-01-18 |
| 3269 | 2017-01-19 |
In [71]:
forecast = m.predict(future)
forecast.tail()
Out[71]:
| ds | trend | yhat_lower | yhat_upper | trend_lower | trend_upper | additive_terms | additive_terms_lower | additive_terms_upper | weekly | weekly_lower | weekly_upper | yearly | yearly_lower | yearly_upper | multiplicative_terms | multiplicative_terms_lower | multiplicative_terms_upper | yhat | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 3265 | 2017-01-15 | 7.180847 | 7.484119 | 8.912103 | 6.837290 | 7.526652 | 1.018428 | 1.018428 | 1.018428 | 0.048295 | 0.048295 | 0.048295 | 0.970133 | 0.970133 | 0.970133 | 0.0 | 0.0 | 0.0 | 8.199274 |
| 3266 | 2017-01-16 | 7.179809 | 7.890993 | 9.241308 | 6.834516 | 7.526953 | 1.344435 | 1.344435 | 1.344435 | 0.352287 | 0.352287 | 0.352287 | 0.992148 | 0.992148 | 0.992148 | 0.0 | 0.0 | 0.0 | 8.524244 |
| 3267 | 2017-01-17 | 7.178771 | 7.619836 | 9.010513 | 6.831743 | 7.527199 | 1.132844 | 1.132844 | 1.132844 | 0.119624 | 0.119624 | 0.119624 | 1.013220 | 1.013220 | 1.013220 | 0.0 | 0.0 | 0.0 | 8.311615 |
| 3268 | 2017-01-18 | 7.177733 | 7.420357 | 8.872825 | 6.828543 | 7.527256 | 0.966499 | 0.966499 | 0.966499 | -0.066647 | -0.066647 | -0.066647 | 1.033146 | 1.033146 | 1.033146 | 0.0 | 0.0 | 0.0 | 8.144232 |
| 3269 | 2017-01-19 | 7.176695 | 7.412110 | 8.864867 | 6.825897 | 7.527090 | 0.979396 | 0.979396 | 0.979396 | -0.072284 | -0.072284 | -0.072284 | 1.051680 | 1.051680 | 1.051680 | 0.0 | 0.0 | 0.0 | 8.156091 |
In [72]:
fig1 = m.plot(forecast)
In [73]:
fig2 = m.plot_components(forecast)
PRACTICING WITH ZILLOW¶
In [0]:
df = pd.read_csv('https://raw.githubusercontent.com/danielcaraway/data/master/Zip_Zhvi_SingleFamilyResidence.csv', encoding='latin')
In [0]:
CA = df[df.State == 'CA']
LA = CA[CA.CountyName == 'Los Angeles County']
mine = LA[LA.RegionName == 90039]
In [0]:
# df = mine.copy()
# df_t = df.loc[:, '1997-01':'2018-12'].T
In [77]:
df = mine.copy()
df_t = df.loc[:, '1997-01':'2018-12'].T
df = df_t.copy()
df.reset_index(inplace=True)
# df['ds'] = df[df.columns[1]] + '-01'
df.columns = ['ds','y']
# df['ds'] = df['ds'] + '-01'
df.head()
Out[77]:
| ds | y | |
|---|---|---|
| 0 | 1997-01 | 147935.0 |
| 1 | 1997-02 | 148799.0 |
| 2 | 1997-03 | 149280.0 |
| 3 | 1997-04 | 149552.0 |
| 4 | 1997-05 | 149320.0 |
In [78]:
df.tail()
Out[78]:
| ds | y | |
|---|---|---|
| 259 | 2018-08 | 868462.0 |
| 260 | 2018-09 | 879218.0 |
| 261 | 2018-10 | 888896.0 |
| 262 | 2018-11 | 903051.0 |
| 263 | 2018-12 | 914058.0 |
In [79]:
m = Prophet()
m.fit(df)
future = m.make_future_dataframe(periods=365)
future.tail()
INFO:fbprophet:Disabling weekly seasonality. Run prophet with weekly_seasonality=True to override this. INFO:fbprophet:Disabling daily seasonality. Run prophet with daily_seasonality=True to override this.
Out[79]:
| ds | |
|---|---|
| 624 | 2019-11-27 |
| 625 | 2019-11-28 |
| 626 | 2019-11-29 |
| 627 | 2019-11-30 |
| 628 | 2019-12-01 |
In [80]:
forecast = m.predict(future)
forecast.tail()
fig1 = m.plot(forecast)
In [81]:
# df = pd.read_csv('../examples/example_retail_sales.csv')
m = Prophet(seasonality_mode='multiplicative').fit(df)
future = m.make_future_dataframe(periods=48)
fcst = m.predict(future)
fig = m.plot(fcst)
INFO:fbprophet:Disabling weekly seasonality. Run prophet with weekly_seasonality=True to override this. INFO:fbprophet:Disabling daily seasonality. Run prophet with daily_seasonality=True to override this.
In [82]:
fcst
Out[82]:
| ds | trend | yhat_lower | yhat_upper | trend_lower | trend_upper | multiplicative_terms | multiplicative_terms_lower | multiplicative_terms_upper | yearly | yearly_lower | yearly_upper | additive_terms | additive_terms_lower | additive_terms_upper | yhat | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 1997-01-01 | 140047.491970 | 122187.251125 | 156589.993286 | 140047.491970 | 140047.491970 | -0.001828 | -0.001828 | -0.001828 | -0.001828 | -0.001828 | -0.001828 | 0.0 | 0.0 | 0.0 | 139791.432687 |
| 1 | 1997-02-01 | 141835.867074 | 124226.306882 | 157792.323187 | 141835.867074 | 141835.867074 | -0.000150 | -0.000150 | -0.000150 | -0.000150 | -0.000150 | -0.000150 | 0.0 | 0.0 | 0.0 | 141814.531781 |
| 2 | 1997-03-01 | 143451.173619 | 128994.542548 | 160912.284827 | 143451.173619 | 143451.173619 | 0.001271 | 0.001271 | 0.001271 | 0.001271 | 0.001271 | 0.001271 | 0.0 | 0.0 | 0.0 | 143633.507654 |
| 3 | 1997-04-01 | 145239.548723 | 127215.506933 | 161422.985381 | 145239.548723 | 145239.548723 | 0.002450 | 0.002450 | 0.002450 | 0.002450 | 0.002450 | 0.002450 | 0.0 | 0.0 | 0.0 | 145595.329110 |
| 4 | 1997-05-01 | 146970.234308 | 130267.104554 | 164323.678412 | 146970.234308 | 146970.234308 | 0.003117 | 0.003117 | 0.003117 | 0.003117 | 0.003117 | 0.003117 | 0.0 | 0.0 | 0.0 | 147428.370071 |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 307 | 2019-01-14 | 884823.065837 | 851367.278144 | 884940.626978 | 884823.065837 | 884823.065837 | -0.018989 | -0.018989 | -0.018989 | -0.018989 | -0.018989 | -0.018989 | 0.0 | 0.0 | 0.0 | 868020.766237 |
| 308 | 2019-01-15 | 884994.214243 | 851579.017831 | 885911.379416 | 884994.214243 | 884994.214243 | -0.019171 | -0.019171 | -0.019171 | -0.019171 | -0.019171 | -0.019171 | 0.0 | 0.0 | 0.0 | 868027.822692 |
| 309 | 2019-01-16 | 885165.362649 | 851019.984804 | 884712.932237 | 885165.362649 | 885165.362649 | -0.019036 | -0.019036 | -0.019036 | -0.019036 | -0.019036 | -0.019036 | 0.0 | 0.0 | 0.0 | 868315.223924 |
| 310 | 2019-01-17 | 885336.511055 | 851721.103683 | 887087.420135 | 885336.511055 | 885336.511055 | -0.018594 | -0.018594 | -0.018594 | -0.018594 | -0.018594 | -0.018594 | 0.0 | 0.0 | 0.0 | 868874.659050 |
| 311 | 2019-01-18 | 885507.659461 | 852089.311855 | 887635.061339 | 885507.659461 | 885507.659461 | -0.017864 | -0.017864 | -0.017864 | -0.017864 | -0.017864 | -0.017864 | 0.0 | 0.0 | 0.0 | 869689.121422 |
312 rows × 16 columns
In [83]:
len(df)
Out[83]:
264
In [97]:
m = Prophet(seasonality_mode='multiplicative', mcmc_samples=264).fit(df)
future = m.make_future_dataframe(periods=120, freq='M')
fcst = m.predict(future)
fig = m.plot(fcst)
INFO:fbprophet:Disabling weekly seasonality. Run prophet with weekly_seasonality=True to override this. INFO:fbprophet:Disabling daily seasonality. Run prophet with daily_seasonality=True to override this. WARNING:pystan:Rhat above 1.1 or below 0.9 indicates that the chains very likely have not mixed WARNING:pystan:182 of 528 iterations saturated the maximum tree depth of 10 (34.5 %) WARNING:pystan:Run again with max_treedepth larger than 10 to avoid saturation
In [85]:
m = Prophet(seasonality_mode='multiplicative', mcmc_samples=264).fit(df)
future = m.make_future_dataframe(periods=12, freq='M')
fcst = m.predict(future)
fig = m.plot(fcst)
INFO:fbprophet:Disabling weekly seasonality. Run prophet with weekly_seasonality=True to override this. INFO:fbprophet:Disabling daily seasonality. Run prophet with daily_seasonality=True to override this. WARNING:pystan:Rhat above 1.1 or below 0.9 indicates that the chains very likely have not mixed WARNING:pystan:177 of 528 iterations saturated the maximum tree depth of 10 (33.5 %) WARNING:pystan:Run again with max_treedepth larger than 10 to avoid saturation
In [86]:
df
Out[86]:
| ds | y | |
|---|---|---|
| 0 | 1997-01 | 147935.0 |
| 1 | 1997-02 | 148799.0 |
| 2 | 1997-03 | 149280.0 |
| 3 | 1997-04 | 149552.0 |
| 4 | 1997-05 | 149320.0 |
| ... | ... | ... |
| 259 | 2018-08 | 868462.0 |
| 260 | 2018-09 | 879218.0 |
| 261 | 2018-10 | 888896.0 |
| 262 | 2018-11 | 903051.0 |
| 263 | 2018-12 | 914058.0 |
264 rows × 2 columns
In [87]:
m = Prophet()
m.fit(df)
future = m.make_future_dataframe(periods=12, freq='M')
future.tail()
INFO:fbprophet:Disabling weekly seasonality. Run prophet with weekly_seasonality=True to override this. INFO:fbprophet:Disabling daily seasonality. Run prophet with daily_seasonality=True to override this.
Out[87]:
| ds | |
|---|---|
| 271 | 2019-07-31 |
| 272 | 2019-08-31 |
| 273 | 2019-09-30 |
| 274 | 2019-10-31 |
| 275 | 2019-11-30 |
In [88]:
forecast = m.predict(future)
forecast.tail()
fig1 = m.plot(forecast)
In [89]:
forecast.tail()
Out[89]:
| ds | trend | yhat_lower | yhat_upper | trend_lower | trend_upper | additive_terms | additive_terms_lower | additive_terms_upper | yearly | yearly_lower | yearly_upper | multiplicative_terms | multiplicative_terms_lower | multiplicative_terms_upper | yhat | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 271 | 2019-07-31 | 918473.369818 | 902613.865705 | 938495.782575 | 913448.589808 | 922065.797615 | 2323.096416 | 2323.096416 | 2323.096416 | 2323.096416 | 2323.096416 | 2323.096416 | 0.0 | 0.0 | 0.0 | 920796.466234 |
| 272 | 2019-08-31 | 923759.835346 | 906457.330437 | 942717.089958 | 917444.302157 | 928700.069581 | 316.944131 | 316.944131 | 316.944131 | 316.944131 | 316.944131 | 316.944131 | 0.0 | 0.0 | 0.0 | 924076.779476 |
| 273 | 2019-09-30 | 928875.769727 | 903878.037350 | 942229.923960 | 921240.232748 | 935426.789393 | -5867.834013 | -5867.834013 | -5867.834013 | -5867.834013 | -5867.834013 | -5867.834013 | 0.0 | 0.0 | 0.0 | 923007.935714 |
| 274 | 2019-10-31 | 934162.235255 | 912278.901934 | 950962.684107 | 924779.022588 | 942742.578093 | -1841.329851 | -1841.329851 | -1841.329851 | -1841.329851 | -1841.329851 | -1841.329851 | 0.0 | 0.0 | 0.0 | 932320.905404 |
| 275 | 2019-11-30 | 939278.169636 | 923329.638442 | 962380.444046 | 928995.886814 | 949423.632385 | 3670.706646 | 3670.706646 | 3670.706646 | 3670.706646 | 3670.706646 | 3670.706646 | 0.0 | 0.0 | 0.0 | 942948.876282 |
In [92]:
components_fig = m.plot_components(forecast)
axes = components_fig.get_axes()
axes[0].set_ylabel('TESTING TESTING')
Out[92]:
Text(32.375, 0.5, 'TESTING TESTING')
In [94]:
CA
Out[94]:
| RegionID | RegionName | City | State | Metro | CountyName | SizeRank | 1996-04 | 1996-05 | 1996-06 | 1996-07 | 1996-08 | 1996-09 | 1996-10 | 1996-11 | 1996-12 | 1997-01 | 1997-02 | 1997-03 | 1997-04 | 1997-05 | 1997-06 | 1997-07 | 1997-08 | 1997-09 | 1997-10 | 1997-11 | 1997-12 | 1998-01 | 1998-02 | 1998-03 | 1998-04 | 1998-05 | 1998-06 | 1998-07 | 1998-08 | 1998-09 | 1998-10 | 1998-11 | 1998-12 | ... | 2016-09 | 2016-10 | 2016-11 | 2016-12 | 2017-01 | 2017-02 | 2017-03 | 2017-04 | 2017-05 | 2017-06 | 2017-07 | 2017-08 | 2017-09 | 2017-10 | 2017-11 | 2017-12 | 2018-01 | 2018-02 | 2018-03 | 2018-04 | 2018-05 | 2018-06 | 2018-07 | 2018-08 | 2018-09 | 2018-10 | 2018-11 | 2018-12 | 2019-01 | 2019-02 | 2019-03 | 2019-04 | 2019-05 | 2019-06 | 2019-07 | 2019-08 | 2019-09 | 2019-10 | 2019-11 | 2019-12 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 13 | 97564 | 94109 | San Francisco | CA | San Francisco-Oakland-Hayward | San Francisco County | 14 | 547676.0 | 547569.0 | 536539.0 | 536211.0 | 536288.0 | 544996.0 | 549733.0 | 548116.0 | 548056.0 | 556765.0 | 564078.0 | 568911.0 | 563733.0 | 567592.0 | 576927.0 | 590090.0 | 601843.0 | 607732.0 | 612399.0 | 618075.0 | 624078.0 | 619463.0 | 608251.0 | 598124.0 | 599915.0 | 605774.0 | 612060.0 | 619972.0 | 630063.0 | 639649.0 | 648839.0 | 660816.0 | 673743.0 | ... | 2076723.0 | 2089536.0 | 2116069.0 | 2126269.0 | 2136544.0 | 2130549.0 | 2125238.0 | 2136355.0 | 2157234.0 | 2183082.0 | 2201513.0 | 2223619.0 | 2242654.0 | 2262404.0 | 2273661 | 2288114 | 2296814 | 2319273 | 2340441 | 2367999 | 2377043 | 2406408 | 2437497 | 2468207 | 2497009 | 2527010 | 2560823 | 2571444 | 2588508 | 2602537 | 2603723 | 2596306 | 2594652 | 2619794 | 2639943 | 2653455 | 2659471 | 2673801 | 2688969 | 2717489 |
| 21 | 96107 | 90250 | Hawthorne | CA | Los Angeles-Long Beach-Anaheim | Los Angeles County | 22 | 174520.0 | 174451.0 | 174208.0 | 174168.0 | 174272.0 | 174236.0 | 174011.0 | 173853.0 | 173880.0 | 173809.0 | 173430.0 | 172856.0 | 172239.0 | 171385.0 | 170904.0 | 171034.0 | 171937.0 | 172959.0 | 173708.0 | 174116.0 | 174672.0 | 176446.0 | 178775.0 | 180840.0 | 181787.0 | 182670.0 | 183373.0 | 183753.0 | 184170.0 | 185105.0 | 186263.0 | 187815.0 | 188620.0 | ... | 542639.0 | 549684.0 | 554883.0 | 559601.0 | 565991.0 | 572281.0 | 577192.0 | 580694.0 | 585780.0 | 590338.0 | 592356.0 | 593805.0 | 595088.0 | 598773.0 | 604365 | 610036 | 616579 | 623096 | 630327 | 635907 | 639595 | 642727 | 642779 | 642257 | 642941 | 647773 | 652424 | 654329 | 654836 | 654122 | 653035 | 654325 | 656639 | 660217 | 657600 | 656051 | 656649 | 661550 | 665524 | 670833 |
| 39 | 97771 | 94565 | Pittsburg | CA | San Francisco-Oakland-Hayward | Contra Costa County | 40 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | 519924.0 | 520437.0 | 520271.0 | 521608.0 | 526538.0 | 534053.0 | 540373.0 | 544590.0 | 546909.0 | 545765.0 | 545227.0 | 545969.0 | 550546.0 | 552338.0 | 555309 | 559167 | 570681 | 581688 | 589077 | 588331 | 588979 | 590588 | 593489 | 591277 | 592299 | 591549 | 590131 | 585682 | 587867 | 590192 | 591096 | 588183 | 586736 | 584946 | 584380 | 582565 | 581526 | 579674 | 579779 | 582825 |
| 43 | 96027 | 90046 | Los Angeles | CA | Los Angeles-Long Beach-Anaheim | Los Angeles County | 44 | 158703.0 | 158615.0 | 158990.0 | 159599.0 | 160228.0 | 161176.0 | 162302.0 | 163102.0 | 163659.0 | 164005.0 | 164238.0 | 165215.0 | 167196.0 | 168901.0 | 170638.0 | 171418.0 | 173336.0 | 174781.0 | 176926.0 | 178643.0 | 180776.0 | 183543.0 | 186489.0 | 188650.0 | 190057.0 | 192063.0 | 194619.0 | 196076.0 | 197877.0 | 200594.0 | 203909.0 | 206660.0 | 208435.0 | ... | 1125483.0 | 1141019.0 | 1150330.0 | 1161896.0 | 1179904.0 | 1195337.0 | 1208427.0 | 1219575.0 | 1236950.0 | 1248887.0 | 1259457.0 | 1272009.0 | 1291359.0 | 1312526.0 | 1335419 | 1356609 | 1380975 | 1408153 | 1434319 | 1452009 | 1454944 | 1455943 | 1460135 | 1471859 | 1488243 | 1508333 | 1526004 | 1537515 | 1545734 | 1549924 | 1550051 | 1554922 | 1566579 | 1580344 | 1588563 | 1599202 | 1619582 | 1643242 | 1655745 | 1668029 |
| 87 | 97711 | 94501 | Alameda | CA | San Francisco-Oakland-Hayward | Alameda County | 88 | 164594.0 | 164065.0 | 163554.0 | 163687.0 | 164207.0 | 164802.0 | 164966.0 | 164895.0 | 165257.0 | 166068.0 | 167170.0 | 167651.0 | 167925.0 | 168804.0 | 170949.0 | 173937.0 | 176381.0 | 178295.0 | 179198.0 | 179969.0 | 181228.0 | 183009.0 | 185088.0 | 186707.0 | 188432.0 | 189955.0 | 191916.0 | 194937.0 | 198030.0 | 201294.0 | 202926.0 | 204314.0 | 204491.0 | ... | 823270.0 | 832964.0 | 845602.0 | 855472.0 | 862741.0 | 869135.0 | 880611.0 | 888377.0 | 892645.0 | 898715.0 | 900458.0 | 901673.0 | 907587.0 | 917554.0 | 931512 | 947430 | 962747 | 973865 | 980028 | 988153 | 995688 | 997469 | 1003458 | 1013300 | 1019174 | 1023141 | 1024986 | 1021306 | 1013708 | 1011229 | 1019833 | 1029955 | 1038937 | 1043473 | 1051026 | 1051526 | 1054081 | 1050810 | 1050477 | 1058938 |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 30278 | 98009 | 95141 | San Jose | CA | San Jose-Sunnyvale-Santa Clara | Santa Clara County | 30279 | 539482.0 | 532297.0 | 529040.0 | 519340.0 | 509995.0 | 507596.0 | 513339.0 | 521067.0 | 525147.0 | 530192.0 | 533211.0 | 535826.0 | 534342.0 | 538771.0 | 548248.0 | 558472.0 | 563311.0 | 562934.0 | 559622.0 | 551968.0 | 541129.0 | 529191.0 | 523018.0 | 515872.0 | 519279.0 | 523226.0 | 530816.0 | 531179.0 | 531116.0 | 536700.0 | 544999.0 | 555692.0 | 563530.0 | ... | 1085551.0 | 1088423.0 | 1079231.0 | 1067071.0 | 1071790.0 | 1095731.0 | 1111667.0 | 1120839.0 | 1125443.0 | 1135403.0 | 1130279.0 | 1127394.0 | 1124116.0 | 1139792.0 | 1144735 | 1158909 | 1177372 | 1212086 | 1224549 | 1225179 | 1222547 | 1230885 | 1223823 | 1198951 | 1175508 | 1180208 | 1187717 | 1193934 | 1193500 | 1189134 | 1180906 | 1174429 | 1175094 | 1184333 | 1191616 | 1203807 | 1191099 | 1161763 | 1123331 | 1105216 |
| 30350 | 98059 | 95229 | Vallecito | CA | NaN | Calaveras County | 30351 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | 212889.0 | 214869.0 | 217488.0 | 217801.0 | 217860.0 | 220071.0 | 222218.0 | 222219.0 | 218200.0 | 214591.0 | 216916.0 | 220715.0 | 220659.0 | 217588.0 | 213734 | 213025 | 211969 | 212102 | 213038 | 214920 | 215538 | 215920 | 216355 | 215913 | 216553 | 217207 | 219360 | 222307 | 224479 | 226993 | 226685 | 224245 | 220362 | 219113 | 219777 | 221118 | 220298 | 220130 | 219565 | 219973 |
| 30420 | 98400 | 95721 | Twin Bridges | CA | Sacramento--Roseville--Arden-Arcade | El Dorado County | 30421 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | 221106.0 | 222405.0 | 224061.0 | 226694.0 | 229175.0 | 231062.0 | 231671.0 | 229550.0 | 229457.0 | 228371.0 | 231913.0 | 236513.0 | 241288.0 | 241506.0 | 241026 | 241606 | 242682 | 242755 | 243387 | 247102 | 250117 | 251559 | 251094 | 250609 | 251871 | 254712 | 260237 | 266705 | 272689 | 273374 | 274286 | 272306 | 277570 | 283606 | 293289 | 293416 | 288793 | 281784 | 277526 | 273191 |
| 30422 | 98152 | 95375 | Strawberry | CA | Sonora | Tuolumne County | 30423 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | 229014.0 | 230258.0 | 232993.0 | 237994.0 | 242690.0 | 245030.0 | 246624.0 | 248738.0 | 251551.0 | 254167.0 | 256218 | 257939 | 257146 | 256979 | 255471 | 255027 | 254391 | 255432 | 258595 | 262077 | 266299 | 269269 | 270577 | 270238 | 271945 | 274057 | 276549 | 276636 | 276468 | 276629 | 274957 | 272186 | 267689 | 264456 | 263067 | 263347 |
| 30428 | 97209 | 93282 | Tulare | CA | Visalia-Porterville | Tulare County | 30429 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 148858.0 | 150809.0 | 152622.0 | 155571 | 156944 | 157868 | 160666 | 163506 | 164605 | 162217 | 161130 | 160962 | 161256 | 160592 | 159573 | 159334 | 158590 | 158014 | 155349 | 153531 | 153059 | 155689 | 156909 | 157209 | 156855 | 156706 | 156429 | 155899 | 157523 |
1685 rows × 292 columns
In [95]:
LA
Out[95]:
| RegionID | RegionName | City | State | Metro | CountyName | SizeRank | 1996-04 | 1996-05 | 1996-06 | 1996-07 | 1996-08 | 1996-09 | 1996-10 | 1996-11 | 1996-12 | 1997-01 | 1997-02 | 1997-03 | 1997-04 | 1997-05 | 1997-06 | 1997-07 | 1997-08 | 1997-09 | 1997-10 | 1997-11 | 1997-12 | 1998-01 | 1998-02 | 1998-03 | 1998-04 | 1998-05 | 1998-06 | 1998-07 | 1998-08 | 1998-09 | 1998-10 | 1998-11 | 1998-12 | ... | 2016-09 | 2016-10 | 2016-11 | 2016-12 | 2017-01 | 2017-02 | 2017-03 | 2017-04 | 2017-05 | 2017-06 | 2017-07 | 2017-08 | 2017-09 | 2017-10 | 2017-11 | 2017-12 | 2018-01 | 2018-02 | 2018-03 | 2018-04 | 2018-05 | 2018-06 | 2018-07 | 2018-08 | 2018-09 | 2018-10 | 2018-11 | 2018-12 | 2019-01 | 2019-02 | 2019-03 | 2019-04 | 2019-05 | 2019-06 | 2019-07 | 2019-08 | 2019-09 | 2019-10 | 2019-11 | 2019-12 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 21 | 96107 | 90250 | Hawthorne | CA | Los Angeles-Long Beach-Anaheim | Los Angeles County | 22 | 174520.0 | 174451.0 | 174208.0 | 174168.0 | 174272.0 | 174236.0 | 174011.0 | 173853.0 | 173880.0 | 173809.0 | 173430.0 | 172856.0 | 172239.0 | 171385.0 | 170904.0 | 171034.0 | 171937.0 | 172959.0 | 173708.0 | 174116.0 | 174672.0 | 176446.0 | 178775.0 | 180840.0 | 181787.0 | 182670.0 | 183373.0 | 183753.0 | 184170.0 | 185105.0 | 186263.0 | 187815.0 | 188620.0 | ... | 542639.0 | 549684.0 | 554883.0 | 559601.0 | 565991.0 | 572281.0 | 577192.0 | 580694.0 | 585780.0 | 590338.0 | 592356.0 | 593805.0 | 595088.0 | 598773.0 | 604365 | 610036 | 616579 | 623096 | 630327 | 635907 | 639595 | 642727 | 642779 | 642257 | 642941 | 647773 | 652424 | 654329 | 654836 | 654122 | 653035 | 654325 | 656639 | 660217 | 657600 | 656051 | 656649 | 661550 | 665524 | 670833 |
| 43 | 96027 | 90046 | Los Angeles | CA | Los Angeles-Long Beach-Anaheim | Los Angeles County | 44 | 158703.0 | 158615.0 | 158990.0 | 159599.0 | 160228.0 | 161176.0 | 162302.0 | 163102.0 | 163659.0 | 164005.0 | 164238.0 | 165215.0 | 167196.0 | 168901.0 | 170638.0 | 171418.0 | 173336.0 | 174781.0 | 176926.0 | 178643.0 | 180776.0 | 183543.0 | 186489.0 | 188650.0 | 190057.0 | 192063.0 | 194619.0 | 196076.0 | 197877.0 | 200594.0 | 203909.0 | 206660.0 | 208435.0 | ... | 1125483.0 | 1141019.0 | 1150330.0 | 1161896.0 | 1179904.0 | 1195337.0 | 1208427.0 | 1219575.0 | 1236950.0 | 1248887.0 | 1259457.0 | 1272009.0 | 1291359.0 | 1312526.0 | 1335419 | 1356609 | 1380975 | 1408153 | 1434319 | 1452009 | 1454944 | 1455943 | 1460135 | 1471859 | 1488243 | 1508333 | 1526004 | 1537515 | 1545734 | 1549924 | 1550051 | 1554922 | 1566579 | 1580344 | 1588563 | 1599202 | 1619582 | 1643242 | 1655745 | 1668029 |
| 98 | 96015 | 90034 | Los Angeles | CA | Los Angeles-Long Beach-Anaheim | Los Angeles County | 99 | 249808.0 | 249482.0 | 250401.0 | 251056.0 | 251514.0 | 251397.0 | 250283.0 | 249968.0 | 250338.0 | 251984.0 | 252901.0 | 254188.0 | 254578.0 | 255822.0 | 256382.0 | 257680.0 | 260300.0 | 263348.0 | 266764.0 | 268164.0 | 270148.0 | 273509.0 | 278206.0 | 282508.0 | 285693.0 | 289000.0 | 292101.0 | 295544.0 | 299422.0 | 303572.0 | 307245.0 | 311989.0 | 316186.0 | ... | 1098613.0 | 1116683.0 | 1129006.0 | 1141621.0 | 1155358.0 | 1168045.0 | 1176148.0 | 1183092.0 | 1192333.0 | 1199192.0 | 1190123.0 | 1184125.0 | 1188810.0 | 1214663.0 | 1247125 | 1270676 | 1288018 | 1305398 | 1324662 | 1344220 | 1351806 | 1356336 | 1349641 | 1345237 | 1341463 | 1349432 | 1353677 | 1355101 | 1356760 | 1357547 | 1354072 | 1354989 | 1360972 | 1371112 | 1357947 | 1349303 | 1345223 | 1364396 | 1377603 | 1394108 |
| 111 | 96239 | 90805 | Long Beach | CA | Los Angeles-Long Beach-Anaheim | Los Angeles County | 112 | 137817.0 | 137415.0 | 137248.0 | 137198.0 | 137274.0 | 137207.0 | 137069.0 | 136945.0 | 136878.0 | 136589.0 | 136326.0 | 135893.0 | 135554.0 | 134987.0 | 134640.0 | 134405.0 | 134764.0 | 135245.0 | 135914.0 | 136466.0 | 137104.0 | 138896.0 | 140825.0 | 142597.0 | 143056.0 | 143338.0 | 143329.0 | 143061.0 | 142901.0 | 143393.0 | 143855.0 | 144632.0 | 144637.0 | ... | 401058.0 | 406339.0 | 409653.0 | 412212.0 | 415488.0 | 419026.0 | 421879.0 | 423376.0 | 426035.0 | 428631.0 | 430342.0 | 431923.0 | 433537.0 | 436756.0 | 442200 | 447966 | 452898 | 457703 | 462067 | 465877 | 467806 | 469763 | 470023 | 469687 | 468882 | 470758 | 472025 | 472819 | 472463 | 471784 | 470695 | 471657 | 472929 | 475373 | 474002 | 473754 | 474411 | 479144 | 483458 | 488025 |
| 113 | 96193 | 90650 | Norwalk | CA | Los Angeles-Long Beach-Anaheim | Los Angeles County | 114 | 147481.0 | 147182.0 | 146908.0 | 146755.0 | 146450.0 | 146097.0 | 145692.0 | 145414.0 | 145158.0 | 144947.0 | 144763.0 | 144611.0 | 144451.0 | 144117.0 | 143890.0 | 143867.0 | 144347.0 | 144856.0 | 145225.0 | 145311.0 | 145568.0 | 146854.0 | 148378.0 | 149777.0 | 150252.0 | 150679.0 | 151164.0 | 151188.0 | 151347.0 | 151833.0 | 152567.0 | 153598.0 | 154239.0 | ... | 432422.0 | 436375.0 | 438859.0 | 440851.0 | 444237.0 | 447533.0 | 450426.0 | 452110.0 | 454994.0 | 457611.0 | 459918.0 | 461409.0 | 462772.0 | 464739.0 | 468851 | 473157 | 477343 | 482122 | 486469 | 489710 | 490805 | 492170 | 492651 | 492327 | 491356 | 492278 | 493275 | 493810 | 493767 | 492713 | 491619 | 492074 | 492861 | 493873 | 491980 | 491376 | 492376 | 495968 | 499044 | 503135 |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 17380 | 96039 | 90058 | Los Angeles | CA | Los Angeles-Long Beach-Anaheim | Los Angeles County | 17381 | 118410.0 | 117991.0 | 120237.0 | 123068.0 | 127823.0 | 131013.0 | 131861.0 | 131357.0 | 131468.0 | 132496.0 | 132925.0 | 133579.0 | 134290.0 | 134600.0 | 132810.0 | 129681.0 | 127333.0 | 127130.0 | 128622.0 | 129086.0 | 129405.0 | 129024.0 | 129748.0 | 130886.0 | 131032.0 | 131435.0 | 131179.0 | 131632.0 | 131597.0 | 129796.0 | 126555.0 | 124734.0 | 125675.0 | ... | 303186.0 | 309476.0 | 314694.0 | 317294.0 | 320170.0 | 321963.0 | 326344.0 | 327113.0 | 330430.0 | 330553.0 | 333203.0 | 335117.0 | 338396.0 | 342555.0 | 346213 | 350278 | 353972 | 359593 | 364425 | 370712 | 373992 | 377692 | 378990 | 380787 | 379822 | 378925 | 378148 | 379070 | 380114 | 380890 | 380543 | 381035 | 381737 | 384453 | 385104 | 386134 | 386642 | 389196 | 391344 | 395551 |
| 18217 | 97331 | 93553 | Pearblossom | CA | Los Angeles-Long Beach-Anaheim | Los Angeles County | 18218 | 87664.0 | 86997.0 | 86637.0 | 86620.0 | 87675.0 | 88586.0 | 90216.0 | 90976.0 | 92204.0 | 91754.0 | 91262.0 | 91141.0 | 92380.0 | 92480.0 | 90945.0 | 89145.0 | 88096.0 | 88948.0 | 89429.0 | 89987.0 | 89813.0 | 90803.0 | 91127.0 | 91897.0 | 91799.0 | 91988.0 | 93062.0 | 94090.0 | 95298.0 | 95325.0 | 95357.0 | 96074.0 | 97123.0 | ... | 227607.0 | 231888.0 | 232896.0 | 232554.0 | 234151.0 | 235742.0 | 237003.0 | 238851.0 | 241674.0 | 246895.0 | 248675.0 | 249350.0 | 249220.0 | 251599.0 | 256143 | 258672 | 261423 | 262936 | 264584 | 267527 | 270417 | 274536 | 275100 | 275549 | 274737 | 274805 | 275723 | 276405 | 278666 | 278833 | 279837 | 280583 | 282099 | 284206 | 282677 | 281829 | 280265 | 281574 | 282796 | 283995 |
| 21032 | 97324 | 93544 | Llano | CA | Los Angeles-Long Beach-Anaheim | Los Angeles County | 21033 | 128101.0 | 126755.0 | 125668.0 | 125506.0 | 125855.0 | 127261.0 | 128071.0 | 129294.0 | 129966.0 | 130057.0 | 129332.0 | 128861.0 | 130453.0 | 132076.0 | 132959.0 | 132990.0 | 133831.0 | 136108.0 | 139067.0 | 140720.0 | 141234.0 | 139489.0 | 138698.0 | 140070.0 | 142403.0 | 143346.0 | 142333.0 | 140317.0 | 139114.0 | 139062.0 | 139361.0 | 139690.0 | 140228.0 | ... | 226474.0 | 229057.0 | 230557.0 | 231687.0 | 234412.0 | 237353.0 | 240098.0 | 243184.0 | 245577.0 | 247074.0 | 245587.0 | 244377.0 | 245162.0 | 247782.0 | 252035 | 254843 | 256340 | 257642 | 259744 | 263473 | 267284 | 271525 | 272349 | 272932 | 272444 | 273310 | 274497 | 275870 | 279848 | 282579 | 284081 | 284885 | 285527 | 287123 | 285334 | 285154 | 285197 | 288154 | 289016 | 289770 |
| 22563 | 399675 | 91008 | Bradbury | CA | Los Angeles-Long Beach-Anaheim | Los Angeles County | 22564 | 299236.0 | 299338.0 | 297435.0 | 295414.0 | 291656.0 | 290623.0 | 292183.0 | 294484.0 | 297310.0 | 298133.0 | 302957.0 | 306087.0 | 310376.0 | 310012.0 | 310798.0 | 310823.0 | 312884.0 | 314229.0 | 315463.0 | 314338.0 | 314685.0 | 315376.0 | 318706.0 | 321743.0 | 325285.0 | 326808.0 | 327076.0 | 327002.0 | 328575.0 | 332404.0 | 336472.0 | 343414.0 | 352301.0 | ... | 1184504.0 | 1193048.0 | 1198569.0 | 1203923.0 | 1209900.0 | 1215592.0 | 1217751.0 | 1223244.0 | 1228543.0 | 1234276.0 | 1220389.0 | 1209054.0 | 1199230.0 | 1210158.0 | 1221662 | 1232501 | 1242322 | 1258584 | 1272872 | 1285892 | 1286602 | 1289543 | 1292734 | 1298696 | 1304408 | 1306182 | 1313124 | 1321300 | 1333949 | 1340705 | 1340088 | 1339797 | 1341705 | 1347899 | 1336720 | 1322992 | 1310898 | 1316338 | 1319847 | 1322469 |
| 29616 | 97339 | 93563 | Valyermo | CA | Los Angeles-Long Beach-Anaheim | Los Angeles County | 29617 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | 210391.0 | 208975.0 | 207852.0 | 206735.0 | 208193.0 | 210037.0 | 212655.0 | 212863.0 | 213990.0 | 214615.0 | 214177.0 | 214457.0 | 214366.0 | 216703.0 | 219395 | 220129 | 220932 | 220555 | 222510 | 226429 | 230833 | 237241 | 243458 | 248587 | 250603 | 250190 | 249598 | 249665 | 251241 | 252341 | 253674 | 253702 | 253460 | 251749 | 246804 | 244706 | 244372 | 246366 | 244359 | 239410 |
274 rows × 292 columns
In [0]:
# for
# m = Prophet(seasonality_mode='multiplicative', mcmc_samples=264).fit(df)
# future = m.make_future_dataframe(periods=120, freq='M')
# fcst = m.predict(future)
# fig = m.plot(fcst)
def prophet_predict_prices_for(df, location_name):
df_t = df.loc[:, '1997-01':'2017-12'].T
df_t['avg'] = df_t.mean(numeric_only=True, axis=1)
df_t.reset_index(inplace=True)
columns = ['index', 'avg']
df = pd.DataFrame(df_t, columns = columns)
df = df.rename(index=str, columns={"avg": "y", "index": "ds"})
# m = Prophet()
# m.fit(df)
m = Prophet(seasonality_mode='multiplicative', mcmc_samples=264).fit(df)
future = m.make_future_dataframe(periods=120, freq='M')
# future = m.make_future_dataframe(periods=12, freq='M')
forecast = m.predict(future)
print("====",location_name,"====")
forcast_fig = m.plot(forecast)
f_axes = forcast_fig.get_axes()
f_axes[0].set_xlabel('DATE')
f_axes[0].set_ylabel(location_name)
In [0]:
glendale = LA[LA.City == 'Glendale']
In [109]:
df = glendale.copy()
for zipcode in set(df['RegionName']):
region_df = df[df['RegionName'] == zipcode]
prophet_predict_prices_for(region_df, str(zipcode))
INFO:fbprophet:Disabling weekly seasonality. Run prophet with weekly_seasonality=True to override this. INFO:fbprophet:Disabling daily seasonality. Run prophet with daily_seasonality=True to override this. WARNING:pystan:Rhat above 1.1 or below 0.9 indicates that the chains very likely have not mixed WARNING:pystan:468 of 528 iterations saturated the maximum tree depth of 10 (88.6 %) WARNING:pystan:Run again with max_treedepth larger than 10 to avoid saturation INFO:fbprophet:Disabling weekly seasonality. Run prophet with weekly_seasonality=True to override this. INFO:fbprophet:Disabling daily seasonality. Run prophet with daily_seasonality=True to override this.
==== 91201 ====
WARNING:pystan:Rhat above 1.1 or below 0.9 indicates that the chains very likely have not mixed WARNING:pystan:496 of 528 iterations saturated the maximum tree depth of 10 (93.9 %) WARNING:pystan:Run again with max_treedepth larger than 10 to avoid saturation INFO:fbprophet:Disabling weekly seasonality. Run prophet with weekly_seasonality=True to override this. INFO:fbprophet:Disabling daily seasonality. Run prophet with daily_seasonality=True to override this.
==== 91202 ====
WARNING:pystan:Rhat above 1.1 or below 0.9 indicates that the chains very likely have not mixed WARNING:pystan:402 of 528 iterations saturated the maximum tree depth of 10 (76.1 %) WARNING:pystan:Run again with max_treedepth larger than 10 to avoid saturation INFO:fbprophet:Disabling weekly seasonality. Run prophet with weekly_seasonality=True to override this. INFO:fbprophet:Disabling daily seasonality. Run prophet with daily_seasonality=True to override this.
==== 91203 ====
WARNING:pystan:Rhat above 1.1 or below 0.9 indicates that the chains very likely have not mixed WARNING:pystan:444 of 528 iterations saturated the maximum tree depth of 10 (84.1 %) WARNING:pystan:Run again with max_treedepth larger than 10 to avoid saturation INFO:fbprophet:Disabling weekly seasonality. Run prophet with weekly_seasonality=True to override this. INFO:fbprophet:Disabling daily seasonality. Run prophet with daily_seasonality=True to override this.
==== 91204 ====
WARNING:pystan:Rhat above 1.1 or below 0.9 indicates that the chains very likely have not mixed WARNING:pystan:477 of 528 iterations saturated the maximum tree depth of 10 (90.3 %) WARNING:pystan:Run again with max_treedepth larger than 10 to avoid saturation INFO:fbprophet:Disabling weekly seasonality. Run prophet with weekly_seasonality=True to override this. INFO:fbprophet:Disabling daily seasonality. Run prophet with daily_seasonality=True to override this.
==== 91205 ====
WARNING:pystan:Rhat above 1.1 or below 0.9 indicates that the chains very likely have not mixed WARNING:pystan:471 of 528 iterations saturated the maximum tree depth of 10 (89.2 %) WARNING:pystan:Run again with max_treedepth larger than 10 to avoid saturation INFO:fbprophet:Disabling weekly seasonality. Run prophet with weekly_seasonality=True to override this. INFO:fbprophet:Disabling daily seasonality. Run prophet with daily_seasonality=True to override this.
==== 91206 ====
WARNING:pystan:Rhat above 1.1 or below 0.9 indicates that the chains very likely have not mixed WARNING:pystan:379 of 528 iterations saturated the maximum tree depth of 10 (71.8 %) WARNING:pystan:Run again with max_treedepth larger than 10 to avoid saturation INFO:fbprophet:Disabling weekly seasonality. Run prophet with weekly_seasonality=True to override this. INFO:fbprophet:Disabling daily seasonality. Run prophet with daily_seasonality=True to override this.
==== 91207 ====
WARNING:pystan:Rhat above 1.1 or below 0.9 indicates that the chains very likely have not mixed WARNING:pystan:459 of 528 iterations saturated the maximum tree depth of 10 (86.9 %) WARNING:pystan:Run again with max_treedepth larger than 10 to avoid saturation
==== 91208 ====
INFO:fbprophet:Disabling weekly seasonality. Run prophet with weekly_seasonality=True to override this. INFO:fbprophet:Disabling daily seasonality. Run prophet with daily_seasonality=True to override this. WARNING:pystan:Rhat above 1.1 or below 0.9 indicates that the chains very likely have not mixed WARNING:pystan:481 of 528 iterations saturated the maximum tree depth of 10 (91.1 %) WARNING:pystan:Run again with max_treedepth larger than 10 to avoid saturation
==== 91214 ====
In [111]:
df = mine.copy()
df_t = df.loc[:, '1997-01':'2018-12'].T
df = df_t.copy()
df.reset_index(inplace=True)
# df['ds'] = df[df.columns[1]] + '-01'
df.columns = ['ds','y']
# df['ds'] = df['ds'] + '-01'
df.head()
Out[111]:
| ds | y | |
|---|---|---|
| 0 | 1997-01 | 147935.0 |
| 1 | 1997-02 | 148799.0 |
| 2 | 1997-03 | 149280.0 |
| 3 | 1997-04 | 149552.0 |
| 4 | 1997-05 | 149320.0 |
In [112]:
m = Prophet()
m.fit(df)
future = m.make_future_dataframe(periods=120, freq='M')
fcst = m.predict(future)
fig = m.plot(fcst)
INFO:fbprophet:Disabling weekly seasonality. Run prophet with weekly_seasonality=True to override this. INFO:fbprophet:Disabling daily seasonality. Run prophet with daily_seasonality=True to override this.
In [113]:
fcst
Out[113]:
| ds | trend | yhat_lower | yhat_upper | trend_lower | trend_upper | additive_terms | additive_terms_lower | additive_terms_upper | yearly | yearly_lower | yearly_upper | multiplicative_terms | multiplicative_terms_lower | multiplicative_terms_upper | yhat | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 1997-01-01 | 1.403879e+05 | 1.224807e+05 | 1.550072e+05 | 1.403879e+05 | 1.403879e+05 | -863.332396 | -863.332396 | -863.332396 | -863.332396 | -863.332396 | -863.332396 | 0.0 | 0.0 | 0.0 | 1.395246e+05 |
| 1 | 1997-02-01 | 1.421767e+05 | 1.247782e+05 | 1.592319e+05 | 1.421767e+05 | 1.421767e+05 | -719.485451 | -719.485451 | -719.485451 | -719.485451 | -719.485451 | -719.485451 | 0.0 | 0.0 | 0.0 | 1.414573e+05 |
| 2 | 1997-03-01 | 1.437924e+05 | 1.271982e+05 | 1.610423e+05 | 1.437924e+05 | 1.437924e+05 | 66.933588 | 66.933588 | 66.933588 | 66.933588 | 66.933588 | 66.933588 | 0.0 | 0.0 | 0.0 | 1.438594e+05 |
| 3 | 1997-04-01 | 1.455813e+05 | 1.295119e+05 | 1.623841e+05 | 1.455813e+05 | 1.455813e+05 | 314.960898 | 314.960898 | 314.960898 | 314.960898 | 314.960898 | 314.960898 | 0.0 | 0.0 | 0.0 | 1.458962e+05 |
| 4 | 1997-05-01 | 1.473124e+05 | 1.322133e+05 | 1.647389e+05 | 1.473124e+05 | 1.473124e+05 | 687.660365 | 687.660365 | 687.660365 | 687.660365 | 687.660365 | 687.660365 | 0.0 | 0.0 | 0.0 | 1.480000e+05 |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 379 | 2028-07-31 | 1.479180e+06 | 1.080462e+06 | 1.917491e+06 | 1.082229e+06 | 1.906088e+06 | 880.118140 | 880.118140 | 880.118140 | 880.118140 | 880.118140 | 880.118140 | 0.0 | 0.0 | 0.0 | 1.480060e+06 |
| 380 | 2028-08-31 | 1.484466e+06 | 1.077554e+06 | 1.922085e+06 | 1.084508e+06 | 1.918488e+06 | -253.024316 | -253.024316 | -253.024316 | -253.024316 | -253.024316 | -253.024316 | 0.0 | 0.0 | 0.0 | 1.484213e+06 |
| 381 | 2028-09-30 | 1.489582e+06 | 1.074314e+06 | 1.929589e+06 | 1.085996e+06 | 1.932973e+06 | -3027.946570 | -3027.946570 | -3027.946570 | -3027.946570 | -3027.946570 | -3027.946570 | 0.0 | 0.0 | 0.0 | 1.486554e+06 |
| 382 | 2028-10-31 | 1.494869e+06 | 1.078185e+06 | 1.943399e+06 | 1.082751e+06 | 1.947499e+06 | -1111.523930 | -1111.523930 | -1111.523930 | -1111.523930 | -1111.523930 | -1111.523930 | 0.0 | 0.0 | 0.0 | 1.493757e+06 |
| 383 | 2028-11-30 | 1.499985e+06 | 1.083240e+06 | 1.950976e+06 | 1.080330e+06 | 1.958310e+06 | 1934.287311 | 1934.287311 | 1934.287311 | 1934.287311 | 1934.287311 | 1934.287311 | 0.0 | 0.0 | 0.0 | 1.501919e+06 |
384 rows × 16 columns
In [142]:
m = Prophet()
m.fit(df)
invest_price = df.tail(1)
future = m.make_future_dataframe(periods=60, freq='M')
fcst = m.predict(future)
sell_price = fcst.tail(1)
print(sell_price['trend'].values[0] - invest_price['y'].values[0])
fig = m.plot(fcst)
INFO:fbprophet:Disabling weekly seasonality. Run prophet with weekly_seasonality=True to override this. INFO:fbprophet:Disabling daily seasonality. Run prophet with daily_seasonality=True to override this.
274366.1740152382
In [0]:
invest_price = df.tail(1)
In [0]:
sell_price = fcst.tail(1)
In [141]:
sell_price['trend'].values[0] - invest_price['y'].values[0]
Out[141]:
274366.1740152382
In [138]:
type(sell_price['trend'])
Out[138]:
pandas.core.series.Series
In [139]:
sell_price['trend'].values[0]
Out[139]:
1188424.1740152382
In [140]:
sell_price
Out[140]:
| ds | trend | yhat_lower | yhat_upper | trend_lower | trend_upper | additive_terms | additive_terms_lower | additive_terms_upper | yearly | yearly_lower | yearly_upper | multiplicative_terms | multiplicative_terms_lower | multiplicative_terms_upper | yhat | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 323 | 2023-11-30 | 1.188424e+06 | 1.041552e+06 | 1.332581e+06 | 1.039249e+06 | 1.325371e+06 | 3670.706646 | 3670.706646 | 3670.706646 | 3670.706646 | 3670.706646 | 3670.706646 | 0.0 | 0.0 | 0.0 | 1.192095e+06 |
In [0]:
def get_investment_difference(df, zip_name):
df_t = df.loc[:, '1997-01':'2017-12'].T
df_t['avg'] = df_t.mean(numeric_only=True, axis=1)
df_t.reset_index(inplace=True)
columns = ['index', 'avg']
df = pd.DataFrame(df_t, columns = columns)
df = df.rename(index=str, columns={"avg": "y", "index": "ds"})
m = Prophet()
m.fit(df)
invest_price = df.tail(1)
future = m.make_future_dataframe(periods=60, freq='M')
fcst = m.predict(future)
sell_price = fcst.tail(1)
print('++++++++',zip_name)
print(sell_price['trend'].values[0] - invest_price['y'].values[0])
fig = m.plot(fcst)
In [149]:
df = glendale.copy()
for zipcode in set(df['RegionName']):
region_df = df[df['RegionName'] == zipcode]
get_investment_difference(region_df, str(zipcode))
INFO:fbprophet:Disabling weekly seasonality. Run prophet with weekly_seasonality=True to override this. INFO:fbprophet:Disabling daily seasonality. Run prophet with daily_seasonality=True to override this. INFO:fbprophet:Disabling weekly seasonality. Run prophet with weekly_seasonality=True to override this. INFO:fbprophet:Disabling daily seasonality. Run prophet with daily_seasonality=True to override this.
++++++++ 91201 236843.65637025773
INFO:fbprophet:Disabling weekly seasonality. Run prophet with weekly_seasonality=True to override this. INFO:fbprophet:Disabling daily seasonality. Run prophet with daily_seasonality=True to override this.
++++++++ 91202 244537.5453543407
INFO:fbprophet:Disabling weekly seasonality. Run prophet with weekly_seasonality=True to override this. INFO:fbprophet:Disabling daily seasonality. Run prophet with daily_seasonality=True to override this.
++++++++ 91203 218796.04965441872
INFO:fbprophet:Disabling weekly seasonality. Run prophet with weekly_seasonality=True to override this. INFO:fbprophet:Disabling daily seasonality. Run prophet with daily_seasonality=True to override this.
++++++++ 91204 254380.26474907843
INFO:fbprophet:Disabling weekly seasonality. Run prophet with weekly_seasonality=True to override this. INFO:fbprophet:Disabling daily seasonality. Run prophet with daily_seasonality=True to override this.
++++++++ 91205 259213.92290523078
INFO:fbprophet:Disabling weekly seasonality. Run prophet with weekly_seasonality=True to override this. INFO:fbprophet:Disabling daily seasonality. Run prophet with daily_seasonality=True to override this.
++++++++ 91206 287514.6916984883
INFO:fbprophet:Disabling weekly seasonality. Run prophet with weekly_seasonality=True to override this. INFO:fbprophet:Disabling daily seasonality. Run prophet with daily_seasonality=True to override this.
++++++++ 91207 359584.92270615813
INFO:fbprophet:Disabling weekly seasonality. Run prophet with weekly_seasonality=True to override this. INFO:fbprophet:Disabling daily seasonality. Run prophet with daily_seasonality=True to override this.
++++++++ 91208 251286.40563258925 ++++++++ 91214 245259.13723531668
In [0]: