PR by nikhilmborkar

build.py

@@ -1,22 +1,39 @@
-def get_categorical_variables(df):
-    return []
+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/employee_retention_data.csv')
 
-def get_numerical_variables(df):
-    return []
+def get_categorical_variables(df):
+    return df[['dept','join_date','quit_date']]
 
+def get_numerical_variables(df):
+    return df.drop(['dept','join_date','quit_date'], axis=1)
 
 def get_numerical_variables_percentile(df):
-    pass
-
+    df_tp = get_numerical_variables(df)
+    return df_tp.describe().T
 
 def get_categorical_variables_modes(df):
-    pass
-
+    categorical_df = get_categorical_variables(df)
+    return categorical_df.mode()
 
 def get_missing_values_count(df):
-    pass
-
+    return pd.DataFrame(pd.isnull(df).sum().rename('NA_count'))
 
 def plot_histogram_with_numerical_values(df):
-    pass
+    numerical_df = get_numerical_variables(df)
+    plt.subplot(221)
+    plt.title(num_df.columns[0])
+    sns.distplot(num_df.iloc[:,0], color='yellow', fit=norm, kde=False)
+    plt.subplot(222)
+    plt.title(num_df.columns[1])
+    sns.distplot(num_df.iloc[:,1], color='yellow', fit=norm, kde=False)
+    plt.subplot(223)
+    plt.title(num_df.columns[2])
+    sns.distplot(num_df.iloc[:,2], color='yellow', fit=norm, kde=False)
+    plt.subplot(224)
+    plt.title(num_df.columns[3])
+    sns.distplot(num_df.iloc[:,3], color='yellow', fit=norm, kde=False)