In [0]:
import pandas as pd
from fbprophet import Prophet 
df = pd.read_csv('https://raw.githubusercontent.com/danielcaraway/data/master/Zip_Zhvi_SingleFamilyResidence.csv', encoding='latin')
# df.head()
In [0]:
columns = df.columns[:7].values
region_reference = pd.DataFrame(data=df, columns=columns)
# region_reference.head()
In [0]:
to_drop = ['RegionID',
 'City',
 'State',
 'Metro',
 'CountyName',
 'SizeRank']
just_numbers = df.drop(to_drop, axis=1)
In [0]:
df_t = just_numbers.set_index('RegionName').T
In [0]:
df_t.reset_index(inplace=True)
In [0]:
df_t['year'] = df_t.apply(lambda x: x['index'].split('-')[0], axis=1)
In [45]:
df_t.head()
Out[45]:
RegionName index 10025 60657 10023 77494 60614 77449 10002 77084 79936 60640 11226 10467 78660 94109 10016 37013 32162 60647 11201 11235 11375 90250 78130 37211 10029 10009 77573 60618 77584 10011 20002 10128 28269 78613 77433 78572 30349 79912 75052 ... 56030 501 7703 10020 10979 50137 84316 84408 73019 83281 4033 4109 830 86343 2714 2872 99104 89405 40404 82310 82938 544 820 821 822 95721 31421 95375 1063 1097 62059 75599 36872 93282 20052 21759 22649 6230 43738 year
0 1996-04 NaN 355664.0 NaN 197907.0 537402.0 97337.0 NaN 97318.0 82436.0 244560.0 215949.0 233362.0 142708.0 547676.0 NaN 111580.0 114090.0 165184.0 515214.0 228908.0 286114.0 174520.0 NaN 111136.0 NaN NaN NaN 212656.0 138762.0 NaN 140355.0 NaN 130993.0 160722.0 163056.0 NaN 95687.0 123875.0 97549.0 ... NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN 298904.0 NaN NaN 70659.0 NaN 142896.0 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN 1996
1 1996-05 NaN 354736.0 NaN 196854.0 536919.0 97145.0 NaN 97177.0 82406.0 244663.0 215494.0 231848.0 142715.0 547569.0 NaN 112190.0 113879.0 165105.0 510121.0 230004.0 285161.0 174451.0 NaN 111666.0 NaN NaN NaN 212797.0 139376.0 NaN 139228.0 NaN 131559.0 160373.0 162894.0 NaN 96288.0 123815.0 97541.0 ... NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN 298977.0 NaN NaN 72780.0 NaN 142141.0 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN 1996
2 1996-06 NaN 355404.0 NaN 195911.0 539044.0 96967.0 NaN 97052.0 82350.0 246601.0 216281.0 230539.0 142832.0 536539.0 NaN 112943.0 112845.0 165876.0 504884.0 229929.0 284662.0 174208.0 NaN 112164.0 NaN NaN NaN 212897.0 139277.0 NaN 138072.0 NaN 132346.0 160177.0 163253.0 NaN 97009.0 123574.0 97528.0 ... NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN 299260.0 NaN NaN 74538.0 NaN 140385.0 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN 1996
3 1996-07 NaN 355863.0 NaN 197300.0 540137.0 96645.0 NaN 96719.0 82301.0 248032.0 215954.0 230632.0 143012.0 536211.0 NaN 113853.0 111769.0 166797.0 505134.0 229400.0 284759.0 174168.0 NaN 112734.0 NaN NaN NaN 212300.0 139221.0 NaN 137244.0 NaN 133091.0 159982.0 163367.0 NaN 97411.0 123431.0 97604.0 ... NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN 296621.0 NaN NaN 75273.0 NaN 139381.0 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN 1996
4 1996-08 NaN 357309.0 NaN 197320.0 542594.0 96671.0 NaN 96609.0 82242.0 250914.0 216436.0 230275.0 143201.0 536288.0 NaN 114655.0 110567.0 168084.0 514560.0 230332.0 284361.0 174272.0 NaN 113264.0 NaN NaN NaN 212398.0 139633.0 NaN 136714.0 NaN 133707.0 160245.0 164164.0 NaN 97823.0 123261.0 97825.0 ... NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN 297102.0 NaN NaN 75638.0 NaN 138956.0 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN 1996

5 rows × 30436 columns

In [0]:
by_year = pd.DataFrame(df_t.groupby('year').mean())
In [0]:
by_year_t = by_year.reset_index()
by_year_t['year'] = by_year_t['year'].astype('datetime64[ns]') 
In [0]:
by_year_t.set_index('year', inplace=True)
In [0]:
by_year_t2 = by_year_t.T
In [0]:
by_year_t2.to_csv('zips_by_year.csv')
In [0]:
by_year_t2.reset_index(inplace=True)
In [52]:
# by_year_t2['year2'] = by_year_t2['year'].astype('datetime64[ns]') 
by_year_t2
Out[52]:
year RegionName 1996-01-01 00:00:00 1997-01-01 00:00:00 1998-01-01 00:00:00 1999-01-01 00:00:00 2000-01-01 00:00:00 2001-01-01 00:00:00 2002-01-01 00:00:00 2003-01-01 00:00:00 2004-01-01 00:00:00 2005-01-01 00:00:00 2006-01-01 00:00:00 2007-01-01 00:00:00 2008-01-01 00:00:00 2009-01-01 00:00:00 2010-01-01 00:00:00 2011-01-01 00:00:00 2012-01-01 00:00:00 2013-01-01 00:00:00 2014-01-01 00:00:00 2015-01-01 00:00:00 2016-01-01 00:00:00 2017-01-01 00:00:00 2018-01-01 00:00:00 2019-01-01 00:00:00
0 10025 NaN NaN NaN NaN NaN NaN NaN 1.524024e+06 1.622857e+06 1.740413e+06 1.880199e+06 1.776032e+06 1.673746e+06 1.426824e+06 1.425603e+06 1.430720e+06 1.369437e+06 1.314699e+06 1.347533e+06 1.354015e+06 1.468749e+06 1.506797e+06 1.445712e+06 1.383775e+06
1 60657 359727.333333 378192.833333 389723.833333 453431.50 521798.916667 586183.833333 628344.916667 6.691198e+05 7.073292e+05 7.562488e+05 8.070008e+05 8.102088e+05 8.231563e+05 7.720613e+05 7.460868e+05 7.097424e+05 7.105657e+05 7.915682e+05 8.466048e+05 8.935743e+05 9.266148e+05 9.397620e+05 9.536783e+05 9.566285e+05
2 10023 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN 1.158906e+06 1.177896e+06 1.263354e+06 1.257324e+06 1.286307e+06 1.431668e+06 1.487505e+06 1.625684e+06 1.592752e+06 1.564584e+06 1.498365e+06
3 77494 197676.777778 209368.250000 206195.250000 212468.75 223155.583333 226383.916667 226765.000000 2.311428e+05 2.401042e+05 2.466654e+05 2.498909e+05 2.580278e+05 2.607339e+05 2.610133e+05 2.674436e+05 2.601717e+05 2.648112e+05 2.834968e+05 3.155041e+05 3.351682e+05 3.324876e+05 3.300152e+05 3.334704e+05 3.347144e+05
4 60614 544883.444444 573575.666667 616168.166667 706178.75 804170.666667 905689.416667 983081.333333 1.042087e+06 1.086231e+06 1.164892e+06 1.234957e+06 1.246696e+06 1.179971e+06 1.070229e+06 9.843876e+05 9.093856e+05 8.680966e+05 9.592943e+05 1.032766e+06 1.095943e+06 1.142199e+06 1.175260e+06 1.194322e+06 1.190550e+06
... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...
30429 20052 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN 7.944576e+05 8.113819e+05 7.966302e+05 8.477740e+05 9.229986e+05 9.932791e+05 1.023301e+06 1.056330e+06 1.158182e+06 1.272855e+06 1.338094e+06
30430 21759 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN 2.792929e+05 2.671424e+05 2.685321e+05 2.635818e+05 2.583762e+05 2.651046e+05 2.834632e+05 2.879907e+05 2.831099e+05 2.543791e+05 2.405582e+05 2.132769e+05
30431 22649 NaN NaN NaN 166094.00 174561.416667 181176.333333 187060.583333 1.998489e+05 2.226023e+05 2.559476e+05 2.691606e+05 2.653517e+05 2.515810e+05 2.367340e+05 2.269193e+05 2.060190e+05 1.997838e+05 1.948958e+05 1.905518e+05 1.881821e+05 1.910163e+05 1.957183e+05 2.069102e+05 2.265459e+05
30432 6230 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN 2.968482e+05 2.687641e+05 2.522892e+05 2.332192e+05 2.237026e+05 2.360420e+05 2.427438e+05 2.539362e+05 2.449571e+05 2.589315e+05 2.661801e+05 2.646891e+05
30433 43738 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN 5.162758e+04 5.331575e+04 5.223608e+04 5.192567e+04 5.303408e+04 5.388642e+04 5.306958e+04 5.532767e+04 5.731758e+04 5.596150e+04 5.712958e+04

30434 rows × 25 columns

In [0]:
mine = by_year_t2[by_year_t2['RegionName'] == 90039]
In [0]:
# mine['2019']
In [0]:
df = by_year_t2.copy()
In [0]:
def get_dream_spreadsheet(row):
  print(row)

  # return { "region": row['RegionName'], 
  #                   "return": 'PROPHET TBD', 
  #                   "prediction_2018": 'PROPHET TBD',
  #                   "actual_2018": row.contains(2018),
  #                   "prediction_2019": 'PROPHET TBD',
  #                   "actual_2019": row['2019']
  #                   }
In [0]:
# df['dream'] = df.apply(lambda x: get_dream_spreadsheet, axis=1)
In [58]:
df
Out[58]:
year RegionName 1996-01-01 00:00:00 1997-01-01 00:00:00 1998-01-01 00:00:00 1999-01-01 00:00:00 2000-01-01 00:00:00 2001-01-01 00:00:00 2002-01-01 00:00:00 2003-01-01 00:00:00 2004-01-01 00:00:00 2005-01-01 00:00:00 2006-01-01 00:00:00 2007-01-01 00:00:00 2008-01-01 00:00:00 2009-01-01 00:00:00 2010-01-01 00:00:00 2011-01-01 00:00:00 2012-01-01 00:00:00 2013-01-01 00:00:00 2014-01-01 00:00:00 2015-01-01 00:00:00 2016-01-01 00:00:00 2017-01-01 00:00:00 2018-01-01 00:00:00 2019-01-01 00:00:00
0 10025 NaN NaN NaN NaN NaN NaN NaN 1.524024e+06 1.622857e+06 1.740413e+06 1.880199e+06 1.776032e+06 1.673746e+06 1.426824e+06 1.425603e+06 1.430720e+06 1.369437e+06 1.314699e+06 1.347533e+06 1.354015e+06 1.468749e+06 1.506797e+06 1.445712e+06 1.383775e+06
1 60657 359727.333333 378192.833333 389723.833333 453431.50 521798.916667 586183.833333 628344.916667 6.691198e+05 7.073292e+05 7.562488e+05 8.070008e+05 8.102088e+05 8.231563e+05 7.720613e+05 7.460868e+05 7.097424e+05 7.105657e+05 7.915682e+05 8.466048e+05 8.935743e+05 9.266148e+05 9.397620e+05 9.536783e+05 9.566285e+05
2 10023 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN 1.158906e+06 1.177896e+06 1.263354e+06 1.257324e+06 1.286307e+06 1.431668e+06 1.487505e+06 1.625684e+06 1.592752e+06 1.564584e+06 1.498365e+06
3 77494 197676.777778 209368.250000 206195.250000 212468.75 223155.583333 226383.916667 226765.000000 2.311428e+05 2.401042e+05 2.466654e+05 2.498909e+05 2.580278e+05 2.607339e+05 2.610133e+05 2.674436e+05 2.601717e+05 2.648112e+05 2.834968e+05 3.155041e+05 3.351682e+05 3.324876e+05 3.300152e+05 3.334704e+05 3.347144e+05
4 60614 544883.444444 573575.666667 616168.166667 706178.75 804170.666667 905689.416667 983081.333333 1.042087e+06 1.086231e+06 1.164892e+06 1.234957e+06 1.246696e+06 1.179971e+06 1.070229e+06 9.843876e+05 9.093856e+05 8.680966e+05 9.592943e+05 1.032766e+06 1.095943e+06 1.142199e+06 1.175260e+06 1.194322e+06 1.190550e+06
... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...
30429 20052 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN 7.944576e+05 8.113819e+05 7.966302e+05 8.477740e+05 9.229986e+05 9.932791e+05 1.023301e+06 1.056330e+06 1.158182e+06 1.272855e+06 1.338094e+06
30430 21759 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN 2.792929e+05 2.671424e+05 2.685321e+05 2.635818e+05 2.583762e+05 2.651046e+05 2.834632e+05 2.879907e+05 2.831099e+05 2.543791e+05 2.405582e+05 2.132769e+05
30431 22649 NaN NaN NaN 166094.00 174561.416667 181176.333333 187060.583333 1.998489e+05 2.226023e+05 2.559476e+05 2.691606e+05 2.653517e+05 2.515810e+05 2.367340e+05 2.269193e+05 2.060190e+05 1.997838e+05 1.948958e+05 1.905518e+05 1.881821e+05 1.910163e+05 1.957183e+05 2.069102e+05 2.265459e+05
30432 6230 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN 2.968482e+05 2.687641e+05 2.522892e+05 2.332192e+05 2.237026e+05 2.360420e+05 2.427438e+05 2.539362e+05 2.449571e+05 2.589315e+05 2.661801e+05 2.646891e+05
30433 43738 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN 5.162758e+04 5.331575e+04 5.223608e+04 5.192567e+04 5.303408e+04 5.388642e+04 5.306958e+04 5.532767e+04 5.731758e+04 5.596150e+04 5.712958e+04

30434 rows × 25 columns

In [0]:
test = df.copy()
test_sm = test[:100]
zip_table = []
def get_prophet_predictions(row):
  mini = pd.DataFrame(row)
  mini['ds'] = row.index
  mini['y'] = row.values
  df = mini.iloc[1:]

  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)

  roi = sell_price['trend'].values[0] - invest_price['y'].values[0]
  return pd.Series((fcst, roi))
  # fig = m.plot(fcst)
  # zip_table.append({ "zipcode": zip_name, "return": roi })  
In [82]:
test_sm[['forecast','roi']] = test_sm.apply(lambda x: get_prophet_predictions(x), axis=1)
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:n_changepoints greater than number of observations.Using 12.
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:n_changepoints greater than number of observations.Using 12.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 7.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 12.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 10.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 12.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 9.
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:n_changepoints greater than number of observations.Using 9.
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:n_changepoints greater than number of observations.Using 17.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 11.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 11.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 12.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 7.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 15.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 8.
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:n_changepoints greater than number of observations.Using 17.
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:n_changepoints greater than number of observations.Using 14.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 15.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 12.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 17.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 18.
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:n_changepoints greater than number of observations.Using 18.
/usr/local/lib/python3.6/dist-packages/pandas/core/frame.py:3509: SettingWithCopyWarning:


A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy

In [0]:
# from datetime import datetime
# datestring = '1996'
# dt = datetime.strptime(datestring, '%Y')
In [67]:
test_sm
Out[67]:
year RegionName 1996-01-01 00:00:00 1997-01-01 00:00:00 1998-01-01 00:00:00 1999-01-01 00:00:00 2000-01-01 00:00:00 2001-01-01 00:00:00 2002-01-01 00:00:00 2003-01-01 00:00:00 2004-01-01 00:00:00 2005-01-01 00:00:00 2006-01-01 00:00:00 2007-01-01 00:00:00 2008-01-01 00:00:00 2009-01-01 00:00:00 2010-01-01 00:00:00 2011-01-01 00:00:00 2012-01-01 00:00:00 2013-01-01 00:00:00 2014-01-01 00:00:00 2015-01-01 00:00:00 2016-01-01 00:00:00 2017-01-01 00:00:00 2018-01-01 00:00:00 2019-01-01 00:00:00 prophet
0 10025 NaN NaN NaN NaN NaN NaN NaN 1.524024e+06 1.622857e+06 1.740413e+06 1.880199e+06 1.776032e+06 1.673746e+06 1.426824e+06 1.425603e+06 1.430720e+06 1.369437e+06 1.314699e+06 1.347533e+06 1.354015e+06 1.468749e+06 1.506797e+06 1.445712e+06 1.383775e+06 -1.934741e+06
1 60657 359727.333333 378192.833333 389723.833333 453431.50 521798.916667 586183.833333 628344.916667 6.691198e+05 7.073292e+05 7.562488e+05 8.070008e+05 8.102088e+05 8.231563e+05 7.720613e+05 7.460868e+05 7.097424e+05 7.105657e+05 7.915682e+05 8.466048e+05 8.935743e+05 9.266148e+05 9.397620e+05 9.536783e+05 9.566285e+05 -2.851431e+05
2 10023 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN 1.158906e+06 1.177896e+06 1.263354e+06 1.257324e+06 1.286307e+06 1.431668e+06 1.487505e+06 1.625684e+06 1.592752e+06 1.564584e+06 1.498365e+06 -1.210629e+05
3 77494 197676.777778 209368.250000 206195.250000 212468.75 223155.583333 226383.916667 226765.000000 2.311428e+05 2.401042e+05 2.466654e+05 2.498909e+05 2.580278e+05 2.607339e+05 2.610133e+05 2.674436e+05 2.601717e+05 2.648112e+05 2.834968e+05 3.155041e+05 3.351682e+05 3.324876e+05 3.300152e+05 3.334704e+05 3.347144e+05 -1.493322e+05
4 60614 544883.444444 573575.666667 616168.166667 706178.75 804170.666667 905689.416667 983081.333333 1.042087e+06 1.086231e+06 1.164892e+06 1.234957e+06 1.246696e+06 1.179971e+06 1.070229e+06 9.843876e+05 9.093856e+05 8.680966e+05 9.592943e+05 1.032766e+06 1.095943e+06 1.142199e+06 1.175260e+06 1.194322e+06 1.190550e+06 -7.385802e+05
In [0]:
test = df.copy()
test_sm = test[:5]
zip_table = []
def get_ds_y(ds, y):
  print(ds)
  print(y)
In [0]:
# test_sm['prophet'] = test_sm.apply(lambda x: get_ds_y(x, x['RegionName']), axis=1)
In [38]:
test_sm.columns
Out[38]:
Index([       'RegionName', 1996-01-01 00:00:00, 1997-01-01 00:00:00,
       1998-01-01 00:00:00, 1999-01-01 00:00:00, 2000-01-01 00:00:00,
       2001-01-01 00:00:00, 2002-01-01 00:00:00, 2003-01-01 00:00:00,
       2004-01-01 00:00:00, 2005-01-01 00:00:00, 2006-01-01 00:00:00,
       2007-01-01 00:00:00, 2008-01-01 00:00:00, 2009-01-01 00:00:00,
       2010-01-01 00:00:00, 2011-01-01 00:00:00, 2012-01-01 00:00:00,
       2013-01-01 00:00:00, 2014-01-01 00:00:00, 2015-01-01 00:00:00,
       2016-01-01 00:00:00, 2017-01-01 00:00:00, 2018-01-01 00:00:00,
       2019-01-01 00:00:00,             'dream'],
      dtype='object', name='year')
In [80]:
test_sm['forecast'][0]
Out[80]:
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 1996-01-01 54797.173399 1.668473e+06 1.984566e+06 54797.173399 54797.173399 1.777107e+06 1.777107e+06 1.777107e+06 1.777107e+06 1.777107e+06 1.777107e+06 0.0 0.0 0.0 1.831904e+06
1 1997-01-01 33114.677559 1.648501e+06 1.971987e+06 33114.677559 33114.677559 1.780916e+06 1.780916e+06 1.780916e+06 1.780916e+06 1.780916e+06 1.780916e+06 0.0 0.0 0.0 1.814030e+06
2 1998-01-01 11491.423511 1.648667e+06 1.953012e+06 11491.423511 11491.423511 1.783806e+06 1.783806e+06 1.783806e+06 1.783806e+06 1.783806e+06 1.783806e+06 0.0 0.0 0.0 1.795297e+06
3 1999-01-01 -10131.830537 1.621309e+06 1.945657e+06 -10131.830537 -10131.830537 1.782535e+06 1.782535e+06 1.782535e+06 1.782535e+06 1.782535e+06 1.782535e+06 0.0 0.0 0.0 1.772403e+06
4 2000-01-01 -31755.084585 1.588174e+06 1.897493e+06 -31755.084585 -31755.084585 1.777107e+06 1.777107e+06 1.777107e+06 1.777107e+06 1.777107e+06 1.777107e+06 0.0 0.0 0.0 1.745352e+06
... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...
79 2023-08-31 -543740.172555 -7.772837e+05 -4.685001e+05 -543742.773628 -543737.647811 -7.668381e+04 -7.668381e+04 -7.668381e+04 -7.668381e+04 -7.668381e+04 -7.668381e+04 0.0 0.0 0.0 -6.204240e+05
80 2023-09-30 -545517.113333 -1.332335e+06 -1.020407e+06 -545519.759906 -545514.503983 -6.355799e+05 -6.355799e+05 -6.355799e+05 -6.355799e+05 -6.355799e+05 -6.355799e+05 0.0 0.0 0.0 -1.181097e+06
81 2023-10-31 -547353.285470 -1.552874e+06 -1.243726e+06 -547355.978142 -547350.594548 -8.601640e+05 -8.601640e+05 -8.601640e+05 -8.601640e+05 -8.601640e+05 -8.601640e+05 0.0 0.0 0.0 -1.407517e+06
82 2023-11-30 -549130.226247 -4.229907e+05 -1.109694e+05 -549132.971062 -549127.466991 2.815769e+05 2.815769e+05 2.815769e+05 2.815769e+05 2.815769e+05 2.815769e+05 0.0 0.0 0.0 -2.675533e+05
83 2023-12-31 -550966.398384 1.004054e+06 1.325258e+06 -550969.230555 -550963.583029 1.714119e+06 1.714119e+06 1.714119e+06 1.714119e+06 1.714119e+06 1.714119e+06 0.0 0.0 0.0 1.163152e+06

84 rows × 16 columns

In [0]:
def predictions(df):
  df['forecast'] = 'XXX'
  df['sell_price'] = 'XXX'
  df['roi'] = 'XXX'
  return df
In [0]:
test_sm = test_sm.apply(predictions, axis=1)
In [70]:
test_sm
Out[70]:
year RegionName 1996-01-01 00:00:00 1997-01-01 00:00:00 1998-01-01 00:00:00 1999-01-01 00:00:00 2000-01-01 00:00:00 2001-01-01 00:00:00 2002-01-01 00:00:00 2003-01-01 00:00:00 2004-01-01 00:00:00 2005-01-01 00:00:00 2006-01-01 00:00:00 2007-01-01 00:00:00 2008-01-01 00:00:00 2009-01-01 00:00:00 2010-01-01 00:00:00 2011-01-01 00:00:00 2012-01-01 00:00:00 2013-01-01 00:00:00 2014-01-01 00:00:00 2015-01-01 00:00:00 2016-01-01 00:00:00 2017-01-01 00:00:00 2018-01-01 00:00:00 2019-01-01 00:00:00 prophet 2018 2019 2020
0 10025.0 NaN NaN NaN NaN NaN NaN NaN 1.524024e+06 1.622857e+06 1.740413e+06 1.880199e+06 1.776032e+06 1.673746e+06 1.426824e+06 1.425603e+06 1.430720e+06 1.369437e+06 1.314699e+06 1.347533e+06 1.354015e+06 1.468749e+06 1.506797e+06 1.445712e+06 1.383775e+06 -1.934741e+06 XXX XXX XXX
1 60657.0 359727.333333 378192.833333 389723.833333 453431.50 521798.916667 586183.833333 628344.916667 6.691198e+05 7.073292e+05 7.562488e+05 8.070008e+05 8.102088e+05 8.231563e+05 7.720613e+05 7.460868e+05 7.097424e+05 7.105657e+05 7.915682e+05 8.466048e+05 8.935743e+05 9.266148e+05 9.397620e+05 9.536783e+05 9.566285e+05 -2.851431e+05 XXX XXX XXX
2 10023.0 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN 1.158906e+06 1.177896e+06 1.263354e+06 1.257324e+06 1.286307e+06 1.431668e+06 1.487505e+06 1.625684e+06 1.592752e+06 1.564584e+06 1.498365e+06 -1.210629e+05 XXX XXX XXX
3 77494.0 197676.777778 209368.250000 206195.250000 212468.75 223155.583333 226383.916667 226765.000000 2.311428e+05 2.401042e+05 2.466654e+05 2.498909e+05 2.580278e+05 2.607339e+05 2.610133e+05 2.674436e+05 2.601717e+05 2.648112e+05 2.834968e+05 3.155041e+05 3.351682e+05 3.324876e+05 3.300152e+05 3.334704e+05 3.347144e+05 -1.493322e+05 XXX XXX XXX
4 60614.0 544883.444444 573575.666667 616168.166667 706178.75 804170.666667 905689.416667 983081.333333 1.042087e+06 1.086231e+06 1.164892e+06 1.234957e+06 1.246696e+06 1.179971e+06 1.070229e+06 9.843876e+05 9.093856e+05 8.680966e+05 9.592943e+05 1.032766e+06 1.095943e+06 1.142199e+06 1.175260e+06 1.194322e+06 1.190550e+06 -7.385802e+05 XXX XXX XXX
In [90]:
len(set(df.RegionName))
Out[90]:
30434
In [0]:
len_test = df.copy()
In [0]:
df = pd.read_csv('https://raw.githubusercontent.com/danielcaraway/data/master/Zip_Zhvi_SingleFamilyResidence.csv', encoding='latin')
In [93]:
df
Out[93]:
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
0 61639 10025 New York NY New York-Newark-Jersey City New York County 1 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 ... 1486790.0 1490909.0 1493113.0 1500163.0 1497306.0 1496223.0 1498588.0 1504899.0 1511536.0 1509462.0 1518963.0 1518670.0 1526823.0 1512395.0 1503332 1483368 1468482 1461572 1454050 1454111 1451781 1449835 1450723 1440314 1433973 1429073 1428637 1425987 1407384 1391270 1380332 1386270 1394397 1404225 1406599 1399918 1380178 1358401 1350481 1345845
1 84654 60657 Chicago IL Chicago-Naperville-Elgin Cook County 2 355664.0 354736.0 355404.0 355863.0 357309.0 359906.0 362935.0 366493.0 369236.0 371964.0 374364.0 376322.0 377455.0 380637.0 381917.0 384322.0 383195.0 381889.0 378162.0 374642.0 373445.0 370798.0 369891.0 367735.0 369673.0 371771.0 378334.0 386284.0 395034.0 403790.0 412949.0 421560.0 428867.0 ... 926166.0 926066.0 929987.0 931155.0 933542.0 935872.0 945765.0 950893.0 950923.0 945971.0 940106.0 937789.0 937761.0 935120.0 931248 932154 941705 953981 959260 960954 959673 959082 954912 950660 948543 948906 951721 954743 957441 961651 966123 967557 965155 960225 956709 953095 950684 948136 946838 945928
2 61637 10023 New York NY New York-Newark-Jersey City New York County 3 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 ... 1627167.0 1630578.0 1630922.0 1629389.0 1620963.0 1608791.0 1600559.0 1600247.0 1598869.0 1595751.0 1595421.0 1597321.0 1600114.0 1584614.0 1566777 1543592 1531018 1537936 1551681 1568820 1573613 1578249 1582848 1583553 1580068 1573052 1563902 1550264 1531141 1521399 1520816 1526676 1525174 1516721 1504180 1492086 1480934 1468075 1454870 1438313
3 91982 77494 Katy TX Houston-The Woodlands-Sugar Land Harris County 4 197907.0 196854.0 195911.0 197300.0 197320.0 198443.0 197736.0 198462.0 199158.0 200824.0 201754.0 202558.0 205017.0 207485.0 208972.0 209013.0 211437.0 215407.0 217938.0 217189.0 214825.0 211272.0 209083.0 206815.0 206114.0 205047.0 204507.0 204444.0 203423.0 203923.0 204949.0 207069.0 207697.0 ... 329476.0 328831.0 328912.0 329142.0 329312.0 330345.0 331281.0 331534.0 330699.0 330184.0 330013.0 329488.0 329015.0 328902.0 329123 330287 331699 332214 332264 332737 333805 334293 333806 333609 333839 334129 334753 334497 335272 335363 335789 335035 334542 334176 334363 334127 334458 334460 334679 334309
4 84616 60614 Chicago IL Chicago-Naperville-Elgin Cook County 5 537402.0 536919.0 539044.0 540137.0 542594.0 546190.0 550015.0 554436.0 557214.0 560140.0 562389.0 565003.0 566844.0 574208.0 578552.0 583864.0 582314.0 581470.0 578402.0 575431.0 574291.0 575269.0 578602.0 583276.0 588869.0 596347.0 604371.0 615222.0 625944.0 640232.0 651765.0 662952.0 671169.0 ... 1141840.0 1140892.0 1144867.0 1147812.0 1153703.0 1159757.0 1174693.0 1185995.0 1191061.0 1187382.0 1179120.0 1174446.0 1174467.0 1173676.0 1172203 1176623 1186741 1197817 1201566 1204015 1204371 1201598 1195307 1189358 1186838 1185950 1187917 1190385 1191138 1193324 1198898 1203423 1204840 1199747 1194591 1188702 1183500 1179024 1175407 1174008
... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...
30429 66169 20052 Washington DC Washington-Arlington-Alexandria District of Columbia 30430 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 ... 1076561.0 1071322.0 1077667.0 1096350.0 1121943.0 1142288.0 1144938.0 1149801.0 1147083.0 1155332.0 1155738.0 1164120.0 1172086.0 1176373.0 1183704 1184773 1197905 1218637 1247840 1268481 1282430 1283908 1283874 1285549 1292009 1301660 1305474 1306492 1307271 1310802 1321676 1327971 1331519 1331204 1331762 1333679 1344030 1357142 1376132 1383939
30430 67023 21759 Keymar MD Washington-Arlington-Alexandria Frederick County 30431 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 ... 284661.0 287839.0 290238.0 287839.0 280391.0 275308.0 271331.0 267019.0 258368.0 248274.0 244407.0 240682.0 241395.0 240922.0 242355 242097 244675 249965 254996 256310 253785 249363 244538 239711 233729 224640 218518 216469 216721 216091 214518 214397 214373 215898 215491 216851 214608 212417 206543 201415
30431 67346 22649 Middletown VA Winchester Frederick County 30432 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 ... 191312.0 190999.0 191940.0 193127.0 193769.0 194017.0 194651.0 196098.0 196689.0 196379.0 195647.0 195180.0 195536.0 195927.0 196912 197815 197896 199539 201742 203837 205321 206864 209032 209598 210442 211698 213021 213932 216175 219277 222071 223628 225230 226814 227609 228817 230588 233229 233064 232049
30432 60206 6230 Pomfret Center CT Worcester Windham County 30433 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 ... 241058.0 238085.0 239948.0 243049.0 246911.0 249786.0 251893.0 254691.0 257886.0 262155.0 263728.0 264618.0 264671.0 264063.0 263250 263526 264764 266940 267460 267935 265830 264350 262716 263231 264923 267515 269397 269100 267918 266035 265994 265368 266017 266893 268598 267617 264139 260057 258609 259024
30433 76819 43738 Fultonham OH Zanesville Muskingum County 30434 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 ... 57517.0 58763.0 58735.0 57653.0 56505.0 56189.0 56694.0 57333.0 57504.0 57391.0 57092.0 57272.0 58129.0 58419.0 58162 57121 56585 55955 55493 55199 55537 55795 56285 56644 56644 56271 55730 55400 55802 56455 57575 57353 56948 56612 57089 56956 56759 56776 57995 59235

30434 rows × 292 columns

In [0]:
to_drop = "1996-04	1996-05	1996-06	1996-07	1996-08	1996-09	1996-10	1996-11	1996-12 2019-01	2019-02	2019-03	2019-04	2019-05	2019-06	2019-07	2019-08	2019-09	2019-10	2019-11	2019-12".split()
df_97_18 = df.drop(to_drop, axis=1)
In [99]:
df_97_18
Out[99]:
RegionID RegionName City State Metro CountyName SizeRank 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 1999-01 1999-02 1999-03 1999-04 1999-05 1999-06 1999-07 1999-08 1999-09 ... 2015-09 2015-10 2015-11 2015-12 2016-01 2016-02 2016-03 2016-04 2016-05 2016-06 2016-07 2016-08 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
0 61639 10025 New York NY New York-Newark-Jersey City New York County 1 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 ... 1359948.0 1366669.0 1380733.0 1398869.0 1416633.0 1427321.0 1441979.0 1458433.0 1470286.0 1475276.0 1480967.0 1483113.0 1486790.0 1490909.0 1493113.0 1500163.0 1497306.0 1496223.0 1498588.0 1504899.0 1511536.0 1509462.0 1518963.0 1518670.0 1526823.0 1512395.0 1503332 1483368 1468482 1461572 1454050 1454111 1451781 1449835 1450723 1440314 1433973 1429073 1428637 1425987
1 84654 60657 Chicago IL Chicago-Naperville-Elgin Cook County 2 371964.0 374364.0 376322.0 377455.0 380637.0 381917.0 384322.0 383195.0 381889.0 378162.0 374642.0 373445.0 370798.0 369891.0 367735.0 369673.0 371771.0 378334.0 386284.0 395034.0 403790.0 412949.0 421560.0 428867.0 432591.0 435328.0 436075.0 437380.0 439142.0 444487.0 452506.0 460445.0 466996.0 ... 902232.0 900170.0 897701.0 900732.0 907374.0 921322.0 930106.0 932259.0 929455.0 927464.0 929221.0 928802.0 926166.0 926066.0 929987.0 931155.0 933542.0 935872.0 945765.0 950893.0 950923.0 945971.0 940106.0 937789.0 937761.0 935120.0 931248 932154 941705 953981 959260 960954 959673 959082 954912 950660 948543 948906 951721 954743
2 61637 10023 New York NY New York-Newark-Jersey City New York County 3 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 ... 1488991.0 1489134.0 1498052.0 1518543.0 1556960.0 1598874.0 1627446.0 1646238.0 1648779.0 1646252.0 1635584.0 1630020.0 1627167.0 1630578.0 1630922.0 1629389.0 1620963.0 1608791.0 1600559.0 1600247.0 1598869.0 1595751.0 1595421.0 1597321.0 1600114.0 1584614.0 1566777 1543592 1531018 1537936 1551681 1568820 1573613 1578249 1582848 1583553 1580068 1573052 1563902 1550264
3 91982 77494 Katy TX Houston-The Woodlands-Sugar Land Harris County 4 200824.0 201754.0 202558.0 205017.0 207485.0 208972.0 209013.0 211437.0 215407.0 217938.0 217189.0 214825.0 211272.0 209083.0 206815.0 206114.0 205047.0 204507.0 204444.0 203423.0 203923.0 204949.0 207069.0 207697.0 207549.0 207531.0 208211.0 209158.0 210300.0 211477.0 213057.0 214438.0 215233.0 ... 337110.0 337166.0 336857.0 337243.0 336604.0 335648.0 334774.0 334665.0 335081.0 333881.0 332303.0 330534.0 329476.0 328831.0 328912.0 329142.0 329312.0 330345.0 331281.0 331534.0 330699.0 330184.0 330013.0 329488.0 329015.0 328902.0 329123 330287 331699 332214 332264 332737 333805 334293 333806 333609 333839 334129 334753 334497
4 84616 60614 Chicago IL Chicago-Naperville-Elgin Cook County 5 560140.0 562389.0 565003.0 566844.0 574208.0 578552.0 583864.0 582314.0 581470.0 578402.0 575431.0 574291.0 575269.0 578602.0 583276.0 588869.0 596347.0 604371.0 615222.0 625944.0 640232.0 651765.0 662952.0 671169.0 676136.0 679232.0 681187.0 686043.0 689523.0 697088.0 705580.0 715431.0 723215.0 ... 1107490.0 1105375.0 1102707.0 1108665.0 1114867.0 1131654.0 1142148.0 1150378.0 1149627.0 1148597.0 1147756.0 1145955.0 1141840.0 1140892.0 1144867.0 1147812.0 1153703.0 1159757.0 1174693.0 1185995.0 1191061.0 1187382.0 1179120.0 1174446.0 1174467.0 1173676.0 1172203 1176623 1186741 1197817 1201566 1204015 1204371 1201598 1195307 1189358 1186838 1185950 1187917 1190385
... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...
30429 66169 20052 Washington DC Washington-Arlington-Alexandria District of Columbia 30430 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 ... 1046384.0 1057277.0 1051880.0 1039368.0 1023212.0 1023481.0 1027522.0 1033242.0 1044698.0 1056224.0 1071289.0 1074388.0 1076561.0 1071322.0 1077667.0 1096350.0 1121943.0 1142288.0 1144938.0 1149801.0 1147083.0 1155332.0 1155738.0 1164120.0 1172086.0 1176373.0 1183704 1184773 1197905 1218637 1247840 1268481 1282430 1283908 1283874 1285549 1292009 1301660 1305474 1306492
30430 67023 21759 Keymar MD Washington-Arlington-Alexandria Frederick County 30431 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 ... 278396.0 272574.0 271753.0 275995.0 280316.0 282253.0 281317.0 279398.0 279832.0 279984.0 281685.0 281957.0 284661.0 287839.0 290238.0 287839.0 280391.0 275308.0 271331.0 267019.0 258368.0 248274.0 244407.0 240682.0 241395.0 240922.0 242355 242097 244675 249965 254996 256310 253785 249363 244538 239711 233729 224640 218518 216469
30431 67346 22649 Middletown VA Winchester Frederick County 30432 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 166283.0 ... 185199.0 184795.0 185156.0 186652.0 187608.0 189502.0 189946.0 190427.0 190387.0 191961.0 192684.0 192303.0 191312.0 190999.0 191940.0 193127.0 193769.0 194017.0 194651.0 196098.0 196689.0 196379.0 195647.0 195180.0 195536.0 195927.0 196912 197815 197896 199539 201742 203837 205321 206864 209032 209598 210442 211698 213021 213932
30432 60206 6230 Pomfret Center CT Worcester Windham County 30433 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 ... 257604.0 258746.0 256767.0 253699.0 250935.0 249409.0 248470.0 247908.0 245794.0 245353.0 245206.0 244270.0 241058.0 238085.0 239948.0 243049.0 246911.0 249786.0 251893.0 254691.0 257886.0 262155.0 263728.0 264618.0 264671.0 264063.0 263250 263526 264764 266940 267460 267935 265830 264350 262716 263231 264923 267515 269397 269100
30433 76819 43738 Fultonham OH Zanesville Muskingum County 30434 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 ... 51566.0 51933.0 51853.0 52251.0 51747.0 51574.0 52041.0 53103.0 54348.0 55614.0 56053.0 56784.0 57517.0 58763.0 58735.0 57653.0 56505.0 56189.0 56694.0 57333.0 57504.0 57391.0 57092.0 57272.0 58129.0 58419.0 58162 57121 56585 55955 55493 55199 55537 55795 56285 56644 56644 56271 55730 55400

30434 rows × 271 columns

In [0]:
df_nona = df_97_18.dropna()
In [101]:
len(df_nona)
Out[101]:
12655
In [0]: