PR by saahil1292

build.py

@@ -1,26 +1,53 @@
+import pandas as pd
+
 def get_categorical_variables(df):
-    return []
+    categorical_data = list(df[['country', 'new_user', 'source', 'converted']])
+    return categorical_data
 
 
 def get_numerical_variables(df):
-    return []
+    numerical_data = list(df[['age', 'total_pages_visited']])
+    return numerical_data
 
 
 def get_numerical_variables_percentile(df):
-    pass
+    return df.describe()
 
 
 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
+    fig, ax = plt.subplots(nrows=1, ncols=2, figsize=(10,5))
+    # Histogram
+    ax[0].hist(df['age'],color='yellow',bins=10,align='mid',normed=True)
+    ax[1].hist(df['total_pages_visited'],color='yellow',bins=10,align='mid',normed=True)
+    ax[0].set_xlabel('age')
+    ax[1].set_xlabel('total_pages_visited')
+    plt.tight_layout()
+    # Normal Curve for age
+    mu, std = norm.fit(df['age'])
+    xmin, xmax = plt.xlim()
+    x = np.linspace(xmin, xmax, 20)
+    p = norm.pdf(x, mu, std)
+    ax[0].plot(x, p, 'k', linewidth=2)
+    # Normal Curve for total_pages_visited
+    mu, std = norm.fit(df['total_pages_visited'])
+    xmin, xmax = plt.xlim()
+    x = np.linspace(xmin, xmax, 70)
+    p = norm.pdf(x, mu, std)
+    ax[1].plot(x, p, 'k', linewidth=2)
+    plt.show()
 
 
 def plot_facet_box(df):
-    pass
+    plt.figure(figsize=(10,5))
+    plt.subplot(121)
+    sns.boxplot('converted', 'age', data=df)
+    plt.subplot(122)
+    sns.boxplot('converted', 'total_pages_visited', data=df)
+    plt.tight_layout()