diff --git a/build.py b/build.py
index 35cdd2a..310c43b 100644
--- a/build.py
+++ b/build.py
@@ -1,26 +1,53 @@
+import pandas as pd
+import matplotlib.pyplot as plt
 def get_categorical_variables(df):
-    return []
+    result = []
+    for i in df.columns:
+        if df.loc[:,i].nunique() < 20:
+            result.append(i)
+    return result
+
 
 
 def get_numerical_variables(df):
-    return []
+    cols = df._get_numeric_data().columns
+    res=list(cols)
+    return list((x for x in res if x not in get_categorical_variables(df)))
 
 
 def get_numerical_variables_percentile(df):
-    pass
+    final = pd.DataFrame(columns = ['variable name','mean','median','25th percentile','50th percentile','75th percentile'])
+    final = df[get_numerical_variables(df)]
+    return final.describe()
 
 
 def get_categorical_variables_modes(df):
-    pass
+    x = df[get_categorical_variables(df)].mode()
+    # return x.to_dict(orient='records')
+    return x
 
 
 def get_missing_values_count(df):
-    pass
+    return pd.DataFrame(len(df.index) - df.count())
 
 
 def plot_histogram_with_numerical_values(df):
-    pass
+    df_sub = df.loc[:,cols]
+    sub_cols = list(df_sub.columns)
+    col_length = len(sub_cols)
+    for i in range(0,col_length):
+        plt.figure(figsize=(30,10))
+        plt.subplot(col_length,1,i+1)
+        plt.hist(df_sub.loc[:,sub_cols[i]], bins=10)
+        plt.title(sub_cols[i])
+        plt.xlabel("Value")
+        plt.ylabel(sub_cols[i])
+        plt.show()
 
 
 def plot_facet_box(df):
-    pass
+    df_sub = df.loc[:,get_numerical_variables(df)]
+    sub_cols = list(df_sub.columns)
+    df_sub.groupby(sub_cols).agg('sum').unstack(1).plot(kind='bar',subplots=True)
+    plt.show()
+    
diff --git a/build.pyc b/build.pyc
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index 0000000..2157473
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diff --git a/tests/__init__.pyc b/tests/__init__.pyc
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index 0000000..3743001
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diff --git a/tests/test_get_categorical_variables.pyc b/tests/test_get_categorical_variables.pyc
new file mode 100644
index 0000000..970ec32
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