I am trying to make a dataframe with RANDOM FOREST actual . prediction value and all the information from X_test
.
This is my code:
def makeDataframe(self):
self.df.index = self.X_test.reset_index()
self.df['type'] = self.y_test
self.df['prediction'] = self.y_pred
self.df['ax'] = self.X_test['ax']
self.df['ay'] = self.X_test['ay']
self.df['az'] = self.X_test['az']
print(self.df.head(10))
I want to make a dataframe like this:
type prediction. ax ay az
But I am stuck with this error:
ValueError: Index data must be 1-dimensional
Any idea to solve this error. Durther, I want to confirm that my prediction index and x_test dataset index are matched.
Can I get some help?
Thank you
CodePudding user response:
You are getting the above error because reset_index() will return a DataFrame and not a 1-dimensional data you can replace it with self.X_test.index.values
or To create a DataFrame you can use a Dictionary like this:
def makeDataframe(self):
data = {}
data.update({'index': self.X.index.values})
data.update({'type': self.y_test.values})
data.update({'prediction': self.y_pred})
data.update({'ax': self.X_test['ax']})
data.update({'ay': self.X_test['ay']})
data.update({'az': self.X_test['az']})
self.df = pd.DataFrame(data)
print(self.df.head(10))