Update app.py

app.py

@@ -25,7 +25,7 @@ According to the features you have and the data structure given below, determine
 Then list 5 interesting questions that could be asked on this data, for instance about specific correlations with target variable.
 Then answer these questions one by one, by finding the relevant numbers.
 Meanwhile, plot some figures using matplotlib/seaborn and save them to the (already existing) folder './figures/': take care to clear each figure with plt.clf() before doing another plot.
-
+Generate a summary of each of the plot generated.
 In your final answer: summarize these correlations and trends
 After each number derive real worlds insights, for instance: "Correlation between is_december and boredness is 1.3453, which suggest people are more bored in winter".
 Your final answer should be a long string with at least 3 numbered and detailed parts.
@@ -39,20 +39,7 @@ The data file is passed to you as the variable data_file, it is a pandas datafra
 DO NOT try to load data_file, it is already a dataframe pre-loaded in your python interpreter!
 """
 
-example_notes="""This data is about the Titanic wreck in 1912.
-The target figure is the survival of passengers, notes by 'Survived'
-pclass: A proxy for socio-economic status (SES)
-1st = Upper
-2nd = Middle
-3rd = Lower
-age: Age is fractional if less than 1. If the age is estimated, is it in the form of xx.5
-sibsp: The dataset defines family relations in this way...
-Sibling = brother, sister, stepbrother, stepsister
-Spouse = husband, wife (mistresses and fiancés were ignored)
-parch: The dataset defines family relations in this way...
-Parent = mother, father
-Child = daughter, son, stepdaughter, stepson
-Some children travelled only with a nanny, therefore parch=0 for them."""
+example_notes="""This data is about the Titanic wreck in 1912. I am interested in the survival statistics."""
 
 def get_images_in_directory(directory):
     image_extensions = {'.png', '.jpg', '.jpeg', '.gif', '.bmp', '.tiff'}