uploading class code

Author: Algorithmica

2018-jan/1.python/5.dataframes2.py

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+import pandas as pd
+
+#create custom dataframe
+passengers = { 'passenger_id': [10,11,12], 'fare':[123.4,12.6,30] }
+df1 = pd.DataFrame(passengers)
+df1.shape
+df1.info()
+
+print(df1['passenger_id'])
+print(df1['fare'])
+
+print(df1.loc[2,'fare'])
+
+#adding new column to existing data frame
+df1['pclass'] = 1

2018-jan/1.python/6.dictionary.py

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+parameters =  { 'depth':10, 'leaf_nodes':10}
+print(type(parameters))
+
+#access elements by key
+print(parameters['depth'])
+print(parameters['depth1'])
+print(parameters.get('depth'))
+print(parameters.get('depth1'))
+
+a = None
+print(type(a))
+
+#add new key-value pair
+parameters['depth1'] = 50
+parameters['a'] = 10
+parameters['a'] = 20
+
+#enumerate over keys/values/items
+print(parameters.keys())
+print(parameters.values())
+print(parameters.items())

2018-jan/3.machine learning basics/firstML.py

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+import pandas as pd
+import os
+from sklearn import tree
+import pydot
+import io
+
+print(os.getcwd())
+os.chdir('C:/Users/Algorithmica/Downloads')
+
+titanic_train = pd.read_csv('titanic_train.csv')
+titanic_train.shape
+titanic_train.info()
+
+#separeate features from target column
+features = ['Pclass']
+X_train = titanic_train[features]
+y_train = titanic_train[['Survived']]
+
+#create an instance of machine learning class 
+dt_estimator = tree.DecisionTreeClassifier()
+#build model by invoking fit method
+dt_estimator.fit(X_train, y_train)
+
+#visualize the deciion tree
+dot_data = io.StringIO() 
+tree.export_graphviz(dt_estimator, out_file = dot_data, feature_names = X_train.columns)
+graph = pydot.graph_from_dot_data(dot_data.getvalue())[0] 
+graph.write_pdf("decision-tree.pdf")
+
+titanic_test = pd.read_csv('titanic_test.csv')
+titanic_test.shape
+titanic_test.info()
+
+X_test = titanic_test[features]
+titanic_test['Survived'] = dt_estimator.predict(X_test)