Add us consumption example

Author: ZoranPandovski

others/us_consumption/data.csv

@@ -0,0 +1,213 @@
+T,Consumption,Income,Production,Savings,Unemployment
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others/us_consumption/mindsdb_acc.py

@@ -0,0 +1,26 @@
+import mindsdb
+import pandas as pd
+from sklearn.metrics import balanced_accuracy_score
+
+def run():
+
+    mdb = mindsdb.Predictor(name='cons')
+
+    timeseries_settings = {'timeseries_settings': {'order_by': ['T'], 
+                                        'window': 5,
+                                        'use_previous_target': True}}
+
+    mdb.learn(from_data='data.csv', to_predict='Consumption', timeseries_settings=timeseries_settings['timeseries_settings'])
+
+    predictions = mdb.predict(when_data='test.csv')
+
+    #show additional info for each transaction row
+    additional_info = [x.explanation for x in predictions]
+      
+    return {
+        'additional info': additional_info
+    }
+
+# Run as main
+if __name__ == '__main__':
+    print(run())

others/us_consumption/test.csv

@@ -0,0 +1,16 @@
+T,Consumption,Income,Production,Savings,Unemployment
+1960-1,0.947823637,1.182497938,5.854555956,3.183292657,0.1
+1960-4,1.260476386,0.625614814,-2.193660711,-4.81376356,0
+1960-7,-0.400781004,0.176703138,-1.658109394,5.334598071,0.1
+1960-10,0.126736036,-0.041822534,-2.440186134,-1.307208157,1.1
+1961-1,-0.026390099,0.966727388,-1.525516857,9.291496908,0.3
+1961-4,1.477627094,1.512169338,3.888044434,2.135312447,0
+1961-7,0.487729914,1.319749804,3.140823012,8.112554481,-0.2
+1961-10,1.983307379,1.91022273,3.446415379,1.503787736,-0.7
+1962-1,1.059973583,0.952471374,1.482779497,0.637621714,-0.4
+1962-4,1.217640674,1.046812916,0.964360906,0,-0.1
+1962-7,0.810161029,0.519325616,1.060926287,-1.92519315,0.1
+1962-10,1.407028928,0.877983733,0.840710754,-3.293382167,-0.1
+1963-1,0.672068286,0.853514287,1.831598558,2.20759517,0.2
+1963-4,0.954375035,0.925525379,2.602751704,0.435730537,-0.1
+1963-7,1.355856553,1.098616029,0.665059131,-1.092907053,-0.1