text_plain_output_1.png
from sklearn.ensemble import RandomForestRegressor

import numpy as np

import pandas as pd

import pandas as pd
features = pd.read_csv('../input/tempscsv/temps.csv')

features = pd.get_dummies(features)

import numpy as np
labels = np.array(features['actual'])
features = features.drop('actual', axis=1)
feature_list = list(features.columns)
features = np.array(features)

from sklearn.ensemble import RandomForestRegressor
rf = RandomForestRegressor(n_estimators=1000, random_state=42)
rf.fit(train_features, train_labels)

predictions = rf.predict(test_features)
errors = abs(predictions - test_labels)
print('Mean Absolute Error:', round(np.mean(errors), 2), 'degrees.')