Update app.py

app.py

@@ -12,24 +12,37 @@ df.drop(columns=["id"], inplace=True)
 def plot(df):
   plots = []
   plt.scatter(df.measurement_13, df.measurement_15, c = df.failure, alpha=0.5)
+  plt.title("Measurement 13 vs 15 with Failure")
+  plt.xlabel("Measurement 13")
+  plt.ylabel("Measurement 15")
   plt.savefig("scatter.png")
   plt.scatter(df.measurement_10, df.measurement_15, c = df.failure, alpha=0.5)
+  plt.title("Measurement 10 vs 15 with Failure")
   plt.savefig("scatter_2.png")
   plt.scatter(df.measurement_14, df.measurement_15, c = df.failure, alpha=0.5)
+  plt.title("Measurement 13 vs 15 with Failure")
   plt.savefig("scatter_3.png")
   plt.scatter(df.measurement_16, df.measurement_15, c = df.failure, alpha=0.5)
+  plt.title("Measurement 16 vs 15 with Failure")
   plt.savefig("scatter_4.png")
   df['failure'].value_counts().plot(kind='bar')
+  plt.title("Number of failed vs successful products")
   plt.savefig("bar.png")
   sns.distplot(df["loading"])
+  plt.title("Distribution of Loading Variable")
   plt.savefig("loading_dist.png")
   sns.distplot(df["attribute_3"])
+  plt.title("Distribution of Attribute 3")
   plt.savefig("attribute_3.png")
   sns.catplot(x='measurement_3', y='measurement_4', hue='failure', data=df, kind='violin')
-  plt.savefig("swarmplot.png")
+  plt.title("Violin Plot of Measurement 3 vs Measurement 4 with Failures")
+  plt.xlabel("Measurement 3")
+  plt.ylabel("Measurement 4")
+  plt.savefig("violinplot.png")
   sns.heatmap(df.select_dtypes(include="number").corr())
+  plt.title("Correlation Between Numerical Variables")
   plt.savefig("corr.png")
-  plots = ["corr.png","scatter.png", "scatter_2.png", "scatter_3.png", "scatter_4.png", "bar.png", "loading_dist.png", "attribute_3.png", "swarmplot.png"]
+  plots = ["corr.png","scatter.png", "scatter_2.png", "scatter_3.png", "scatter_4.png", "bar.png", "loading_dist.png", "attribute_3.png", "violinplot.png"]
   return plots
   
 inputs = [gr.Dataframe(label="Supersoaker Production Data")]