PR by Rohan2015

build.py

@@ -1,26 +1,60 @@
+import pandas as pd
+
 def get_categorical_variables(df):
-    return []
+    #returning for now based on visual analysis
+    return df[['country','new_user','source','converted']]
 
 
 def get_numerical_variables(df):
-    return []
+    return pd.DataFrame._get_numeric_data(df)
 
 
 def get_numerical_variables_percentile(df):
-    pass
+    df = pd.DataFrame._get_numeric_data(df)
+    df = df.groupby('converted').describe()
+    return df
 
 
 def get_categorical_variables_modes(df):
-    pass
-
+    dfn = df[['country','new_user','source','converted']]
+    df_mode =  dfn.mode()
+    return df_mode
 
 def get_missing_values_count(df):
-    pass
+    ndf = df.isnull().sum()
+    ndf = pd.DataFrame(ndf)
+    ndf2 = ndf.reset_index()
+    ndf2 = ndf2.rename(columns={'index':'var_name',0:'missing_value_count'})
+    return ndf2
 
 
 def plot_histogram_with_numerical_values(df):
-    pass
+    age = df['age'].tolist()
+    new_user = df['new_user'].tolist()
+    total_pages_visited = df['total_pages_visited'].tolist()
+    converted = df['converted'].tolist()
+
+    fig, axes = plt.subplots(2, 2)
+
+    axes[0,0].hist(age)
+    axes[0,0].set_title('age')
+
+    axes[0,1].hist(new_user)
+    axes[0,1].set_title('new_user')
+
+    axes[1,0].hist(total_pages_visited)
+    axes[1,0].set_title('total_pages_visited')
+
+    axes[1,1].hist(converted)
+    axes[1,1].set_title('converted')
+
+    plt.tight_layout()
+    plt.show()
 
 
 def plot_facet_box(df):
-    pass
+    list_of_columns = df.columns.values
+    for col in list_of_columns:
+        plt.boxplot(df[col])
+        plt.title(col)
+        plt.show()