diff --git a/build.py b/build.py
index c7d540b..461f473 100644
--- a/build.py
+++ b/build.py
@@ -1,22 +1,38 @@
+import pandas as pd
+import seaborn as sns
+from scipy.stats import norm
+
 def get_categorical_variables(df):
-    return []
+    columns = ['dept', 'join_date', 'quit_date']
+    for col in columns:
+        df[col] = df[col].astype('category')
+    return columns
 
 
 def get_numerical_variables(df):
-    return []
+    numerical_variables = list(df.select_dtypes(include=['float64', 'int64']))
+    return numerical_variables
 
 
 def get_numerical_variables_percentile(df):
-    pass
+    return df.describe().T
 
 
 def get_categorical_variables_modes(df):
-    pass
+    return df[get_categorical_variables(df)].mode()
 
 
 def get_missing_values_count(df):
-    pass
+    return pd.DataFrame(df.isnull().sum())
 
 
 def plot_histogram_with_numerical_values(df):
-    pass
+    plt.figure(figsize = (15,6))
+    plt.subplot(221)
+    sns.distplot(df[numerical_variables[0]], bins=10, color='yellow', fit=norm, kde=False)
+    plt.subplot(222)
+    sns.distplot(df[numerical_variables[1]], bins=10, color='yellow', fit=norm, kde=False)
+    plt.subplot(223)
+    sns.distplot(df[numerical_variables[2]], bins=10, color='yellow', fit=norm, kde=False)
+    plt.subplot(224)
+    sns.distplot(df[numerical_variables[3]], bins=10, color='yellow', fit=norm, kde=False)
diff --git a/build.pyc b/build.pyc
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index 0000000..33f3100
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diff --git a/tests/__init__.pyc b/tests/__init__.pyc
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index 0000000..dfe282b
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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..8a78b2b
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