diff --git a/R/R/prophet.R b/R/R/prophet.R
index a8425a6..60e7612 100644
--- a/R/R/prophet.R
+++ b/R/R/prophet.R
@@ -357,6 +357,10 @@ setup_dataframe <- function(m, df, initialize_scales = FALSE) {
     if (!(name %in% colnames(df))) {
       stop('Regressor "', name, '" missing from dataframe')
     }
+    df[[name]] <- as.numeric(df[[name]])
+    if (anyNA(df[[name]])) {
+      stop('Found NaN in column ', name)
+    }
   }
 
   df <- df %>%
@@ -386,12 +390,8 @@ setup_dataframe <- function(m, df, initialize_scales = FALSE) {
   }
 
   for (name in names(m$extra_regressors)) {
-    df[[name]] <- as.numeric(df[[name]])
     props <- m$extra_regressors[[name]]
     df[[name]] <- (df[[name]] - props$mu) / props$std
-    if (anyNA(df[[name]])) {
-      stop('Found NaN in column ', name)
-    }
   }
   return(list("m" = m, "df" = df))
 }
diff --git a/python/fbprophet/forecaster.py b/python/fbprophet/forecaster.py
index d2092ba..e05f5fb 100644
--- a/python/fbprophet/forecaster.py
+++ b/python/fbprophet/forecaster.py
@@ -15,6 +15,7 @@ from datetime import timedelta
 import logging
 import numpy as np
 import pandas as pd
+import pystan  # noqa F401
 
 
 from fbprophet.diagnostics import prophet_copy
@@ -33,11 +34,6 @@ from fbprophet.plot import (
 logging.basicConfig()
 logger = logging.getLogger(__name__)
 
-try:
-    import pystan  # noqa F401
-except ImportError:
-    logger.exception('You cannot run fbprophet without pystan installed')
-
 
 class Prophet(object):
     """Prophet forecaster.
@@ -160,13 +156,13 @@ class Prophet(object):
             raise ValueError("Parameter 'changepoint_range' must be in [0, 1]")
         if self.holidays is not None:
             if not (
-                isinstance(holidays, pd.DataFrame)
-                and 'ds' in holidays  # noqa W503
-                and 'holiday' in holidays  # noqa W503
+                isinstance(self.holidays, pd.DataFrame)
+                and 'ds' in self.holidays  # noqa W503
+                and 'holiday' in self.holidays  # noqa W503
             ):
                 raise ValueError("holidays must be a DataFrame with 'ds' and "
                                  "'holiday' columns.")
-            holidays['ds'] = pd.to_datetime(holidays['ds'])
+            self.holidays['ds'] = pd.to_datetime(self.holidays['ds'])
             has_lower = 'lower_window' in self.holidays
             has_upper = 'upper_window' in self.holidays
             if has_lower + has_upper == 1:
@@ -253,6 +249,9 @@ class Prophet(object):
             if name not in df:
                 raise ValueError(
                     'Regressor "{}" missing from dataframe'.format(name))
+            df[name] = pd.to_numeric(df[name])
+            if df[name].isnull().any():
+                raise ValueError('Found NaN in column ' + name)
 
         df = df.sort_values('ds')
         df.reset_index(inplace=True, drop=True)
@@ -277,10 +276,7 @@ class Prophet(object):
             df['y_scaled'] = (df['y'] - df['floor']) / self.y_scale
 
         for name, props in self.extra_regressors.items():
-            df[name] = pd.to_numeric(df[name])
             df[name] = ((df[name] - props['mu']) / props['std'])
-            if df[name].isnull().any():
-                raise ValueError('Found NaN in column ' + name)
         return df
 
     def initialize_scales(self, initialize_scales, df):
@@ -1092,6 +1088,9 @@ class Prophet(object):
             )
             for par in stan_fit.model_pars:
                 self.params[par] = stan_fit[par]
+                # Shape vector parameters
+                if par in ['delta', 'beta'] and len(self.params[par].shape) < 2:
+                    self.params[par] = self.params[par].reshape((-1, 1))
         else:
             try:
                 params = model.optimizing(
@@ -1102,12 +1101,8 @@ class Prophet(object):
                     dat, init=stan_init, iter=1e4, algorithm='Newton',
                     **kwargs
                 )
-            self.params = params
-
-        # Reshape all parameters to matrix shape
-        for p, v in self.params.items():
-            if len(v.shape) == 1:
-                self.params[p] = v.reshape((-1, 1))
+            for par in params:
+                self.params[par] = params[par].reshape((1, -1))
 
         # If no changepoints were requested, replace delta with 0s
         if len(self.changepoints) == 0: