Upload app.py

app.py

@@ -3,47 +3,41 @@ import pandas as pd
 import matplotlib.pyplot as plt
 import seaborn as sns
 
-df_diamonds = pd.read_csv('diamonds.csv')
-df_diamonds = df_diamonds.drop(["Unnamed: 0"], axis=1)
-
-st.title('Diamond selecting APP')
-
-# Users set the price range
-min_price = st.number_input('Input minimum price', min_value=int(df_diamonds['price'].min()), max_value=int(df_diamonds['price'].max()), value=int(df_diamonds['price'].min()))
-max_price = st.number_input('Input maximum price', min_value=min_price, max_value=int(df_diamonds['price'].max()), value=int(df_diamonds['price'].max()))
-
-# Select the diamonds
-cuts = st.multiselect('Select cut', df_diamonds['cut'].unique())
-colors = st.multiselect('Select color', df_diamonds['color'].unique())
-clarities = st.multiselect('Select clarity', df_diamonds['clarity'].unique())
-
-if st.button('Reset'):
-    cuts = []
-    colors = []
-    clarities = []
-    min_price = int(df_diamonds['price'].min())
-    max_price = int(df_diamonds['price'].max())
-
-# Filter the diamonds
-filtered_diamonds = df_diamonds[(df_diamonds['price'] >= min_price) & (df_diamonds['price'] <= max_price)]
-
-if cuts:
-    filtered_diamonds = filtered_diamonds[filtered_diamonds['cut'].isin(cuts)]
-if colors:
-    filtered_diamonds = filtered_diamonds[filtered_diamonds['color'].isin(colors)]
-if clarities:
-    filtered_diamonds = filtered_diamonds[filtered_diamonds['clarity'].isin(clarities)]
-
-# Check if there is data to plot
+# read the dataset
+df = pd.read_csv('diamonds.csv')
+
+st.title('Diamond APP sorting festivity. Noted by Dimitri')
+
+df = df.drop(["Unnamed: 0"], axis=1)
+
+#Potential diamonds with a impossible dimensions are dropped, for example a diamond that has a 0 in x, y or z should not be possible.
+df = df.drop(df[df["x"]==0].index)
+df = df.drop(df[df["y"]==0].index)
+df = df.drop(df[df["z"]==0].index)
+st.image('diamonds.jpg')
+st.write(f"the price range is {326} to {18823}")
+# users set the price range
+min_price = st.number_input('Input minimum price', min_value=int(df['price'].min()), max_value=int(df['price'].max()), value=int(df['price'].min()))
+max_price = st.number_input('Input maximum price', min_value=int(df['price'].min()), max_value=int(df['price'].max()), value=int(df['price'].max()))
+
+#users select
+selected_cuts = st.multiselect('choosing cut', df['cut'].unique())
+selected_cuts = st.multiselect('choosing color', df['color'].unique())
+selected_cuts = st.multiselect('choosing clarity', df['clarity'].unique())
+selected_cuts = st.multiselect('choosing carat', df['carat'].unique())
+
+
+# select the diamonds
+filtered_diamonds = df[(df['price'] >= min_price) & (df['price'] <= max_price)]
+
+# show the results
 if not filtered_diamonds.empty:
-    # Create a scatterplot based on the selected criteria
+    st.write(f"find {len(filtered_diamonds)} diamonds for you.")
+    st.dataframe(filtered_diamonds)
+# Create a scatterplot based on the selected criteria
     fig, ax = plt.subplots()
     sns.scatterplot(x='carat', y='price', data=filtered_diamonds, ax=ax)
     ax.set_title('Prices by Carat')
     st.pyplot(fig)
 else:
-    st.write("No diamonds fit the selected criteria.")
-
-# Display a scrollable table with the total information based on the selected criteria
-st.write("Total Information:")
-st.dataframe(filtered_diamonds)
+    st.write("No diamonds fit you")