Update app.py

app.py

@@ -11,13 +11,13 @@ df.drop(columns=["id"], inplace=True)
 
 def plot(df):
   plots = []
-  plt.scatter(df.measurement_13, df.measurement_15, c = df.loading,alpha=0.5)
+  plt.scatter(df.measurement_13, df.measurement_15, c = df.failure, alpha=0.5)
   plt.savefig("scatter.png")
-  plt.scatter(df.measurement_10, df.measurement_15, c = df.loading,alpha=0.5)
+  plt.scatter(df.measurement_10, df.measurement_15, c = df.failure, alpha=0.5)
   plt.savefig("scatter_2.png")
-  plt.scatter(df.measurement_14, df.measurement_15, c = df.loading,alpha=0.5)
+  plt.scatter(df.measurement_14, df.measurement_15, c = df.failure, alpha=0.5)
   plt.savefig("scatter_3.png")
-  plt.scatter(df.measurement_16, df.measurement_15, c = df.loading,alpha=0.5)
+  plt.scatter(df.measurement_16, df.measurement_15, c = df.failure, alpha=0.5)
   plt.savefig("scatter_4.png")
   df['failure'].value_counts().plot(kind='bar')
   plt.savefig("bar.png")
@@ -29,7 +29,7 @@ def plot(df):
   plt.savefig("swarmplot.png")
   sns.heatmap(df.select_dtypes(include="number").corr())
   plt.savefig("corr.png")
-  plots = ["corr.png","scatter.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", "swarmplot.png"]
   return plots
   
 inputs = [gr.Dataframe(label="Supersoaker Production Data")]