PR by sagarambalam

build.py

@@ -1,21 +1,43 @@
+import pandas as pd
 def get_categorical_variables(df):
-    return []
+
+    return ['country', 'new_user', 'source', 'converted']
 
 
 def get_numerical_variables(df):
-    return []
+    return ['age', 'total_pages_visited']
 
 
 def get_numerical_variables_percentile(df):
-    pass
+    a = df.describe()
+    new_a =  a.T
+    new_a.drop(['count', 'std', 'min', 'max'], inplace = True, axis=1)
+
+    new_a['variable name'] = new_a.index.values
+    new_a['median'] = new_a['50%']
+    new_a['25th percentile'] = new_a['25%']
+    new_a['50th percentile'] = new_a['50%']
+    new_a['75th percentile'] = new_a['75%']
+
+    variable_percentile = pd.DataFrame(new_a, columns = ['variable name','mean','median','25th percentile', '50th percentile', '75th percentile'])
+    return variable_percentile
 
 
 def get_categorical_variables_modes(df):
-    pass
+    a = df.mode(axis = 0)
+    return a
 
 
 def get_missing_values_count(df):
-    pass
+    vals= []
+    for cols in df.columns.values:
+        vals.append(df[cols].isnull().sum())
+
+    ndf = zip(df.columns.values,vals)
+
+    miss = pd.DataFrame(ndf)
+    missing = miss.rename(columns={"0":"var_name","1":"missing_value_count"})
+    return missing
 
 
 def plot_histogram_with_numerical_values(df):