PR by nikhilmborkar

build.py

@@ -1,26 +1,58 @@
+import numpy as np
+import pandas as pd
+from pandas import Series, DataFrame
+import operator
+import matplotlib.pyplot as plt
+
+df = pd.read_csv('data/conversion_data.csv')
+
 def get_categorical_variables(df):
-    return []
+    return df[['country','source','new_user','converted']]
 
 
 def get_numerical_variables(df):
-    return []
+    return df._get_numeric_data()
 
 
 def get_numerical_variables_percentile(df):
-    pass
+    df_temp = get_numerical_variables(df)
+    return df_temp.describe().T
 
 
 def get_categorical_variables_modes(df):
-    pass
-
+    dic = {'converted':0, 'country':'', 'new_user':0, 'source':''}
+    for col in df.mode().columns:
+        dic[col] = df.mode()[col][0]
+    return pd.DataFrame(dic.items(), columns=['var_name', 'mode'])
 
 def get_missing_values_count(df):
-    pass
+    my_missing_value = pd.DataFrame(df.isnull().sum(), columns=['missing_value_count'])
+    my_missing_value.index.name = 'var_name'
+    return my_missing_value
 
 
 def plot_histogram_with_numerical_values(df):
+    fig, axes = plt.subplots(2, 2)
+    df1 = get_numerical_variables(df)
+    list_of_cols = df1.columns
+    axes[0,0].hist(df[list_of_cols[0]])
+    axes[0,0].set_title(list_of_cols[0])
+    axes[0,1].hist(df[list_of_cols[1]])
+    axes[0,1].set_title(list_of_cols[1])
+    axes[1,0].hist(df[list_of_cols[2]])
+    axes[1,0].set_title(list_of_cols[2])
+    axes[1,1].hist(df[list_of_cols[3]])
+    axes[1,1].set_title(list_of_cols[3])
+    plt.tight_layout()
+    plt.show()
     pass
 
 
 def plot_facet_box(df):
+    def plot_facet_box(df):
+        list_of_cols = df.columns
+        for col in list_of_cols:
+            plt.boxplot(df[col], 1)
+            plt.title(col)
+            plt.show()
     pass