add assertion testing

code/exploratory_data_analysis.py

@@ -1,3 +1,4 @@
+import os
 import pandas as pd
 import matplotlib.pyplot as plt
 import seaborn as sns
@@ -5,6 +6,10 @@ import seaborn as sns
 # Set seaborn style
 sns.set(style="whitegrid")
 
+# Ensure the 'assets' directory exists
+if not os.path.exists('assets'):
+    os.makedirs('assets')
+
 # Function to plot age distribution
 def plot_age_distribution(df):
     plt.figure(figsize=(8, 5))
@@ -12,7 +17,11 @@ def plot_age_distribution(df):
     plt.title('Age Distribution')
     plt.xlabel('Age')
     plt.ylabel('Count')
-    plt.show()
+    plot_filename = 'assets/age_distribution.png'
+    plt.savefig(plot_filename)
+    plt.show() 
+    plt.close()
+    return plot_filename
 
 # Function to plot gender distribution (Donut Chart)
 def plot_gender_distribution(df):
@@ -22,32 +31,48 @@ def plot_gender_distribution(df):
             colors=sns.color_palette("pastel"))
     plt.title('Gender Distribution')
     plt.gca().set_aspect('equal')
-    plt.show()
+    plot_filename = 'assets/gender_distribution.png'
+    plt.savefig(plot_filename)
+    plt.show() 
+    plt.close()
+    return plot_filename
 
 # Function to plot nationality distribution
 def plot_nationality_distribution(df):
     plt.figure(figsize=(8, 5))
-    sns.countplot(y=df['Nationality'], palette='coolwarm')
+    sns.countplot(y=df['Nationality'], hue=df['Nationality'], palette='coolwarm', legend=False)
     plt.title('Nationality Distribution')
     plt.gca().set_aspect('equal')
-    plt.show()
+    plot_filename = 'assets/nationality_distribution.png'
+    plt.savefig(plot_filename)
+    plt.show()  
+    plt.close()
+    return plot_filename
 
 # Function to plot native language distribution
 def plot_native_language_distribution(df):
     plt.figure(figsize=(8, 5))
-    sns.countplot(y=df['Native Language'], palette='coolwarm')
+    sns.countplot(y=df['Native Language'], hue=df['Native Language'], palette='coolwarm', legend=False)
     plt.title('Native Language Distribution')
     plt.gca().set_aspect('equal')
-    plt.show()
+    plot_filename = 'assets/native_language_distribution.png'
+    plt.savefig(plot_filename)
+    plt.show() 
+    plt.close()
+    return plot_filename
 
 # Function to plot familiarity with English distribution
 def plot_familiarity_with_english(df):
     plt.figure(figsize=(8, 5))
-    sns.countplot(y=df['Familiarity with English'], palette='coolwarm')
+    sns.countplot(y=df['Familiarity with English'], hue=df['Familiarity with English'], palette='coolwarm', legend=False)
     plt.title('Familiarity with English')
     plt.xlabel('Count')
     plt.ylabel('Familiarity Level')
-    plt.show()
+    plot_filename = 'assets/familiarity_with_eng.png'
+    plt.savefig(plot_filename)
+    plt.show() 
+    plt.close()
+    return plot_filename
 
 # Function to plot recording duration distribution
 def plot_duration_distribution(df):
@@ -56,20 +81,31 @@ def plot_duration_distribution(df):
     plt.title('Recording Duration Distribution')
     plt.xlabel('Duration (seconds)')
     plt.ylabel('Count')
-    plt.show()
+    plot_filename = 'assets/recording_duration_distribution.png'
+    plt.savefig(plot_filename)
+    plt.show() 
+    plt.close()
+    return plot_filename
 
 
 def main():
     # Load the dataset
     df = pd.read_csv("metadata.csv")
     
-    # Plot the distributions
-    plot_age_distribution(df)
-    plot_gender_distribution(df)
-    plot_nationality_distribution(df)
-    plot_native_language_distribution(df)
-    plot_familiarity_with_english(df)
-    plot_duration_distribution(df)
+    # Plot the distributions and save files
+    plot_files = [
+        plot_age_distribution(df),
+        plot_gender_distribution(df),
+        plot_nationality_distribution(df),
+        plot_native_language_distribution(df),
+        plot_familiarity_with_english(df),
+        plot_duration_distribution(df)
+    ]
+    
+    # Testing
+    for plot_file in plot_files:
+        assert os.path.exists(plot_file), f"Plot {plot_file} was not saved."
+        print(f"Assertion passed for {plot_file}")
 
 
 if __name__ == "__main__":