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Update app.py
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app.py
CHANGED
@@ -1,43 +1,43 @@
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import streamlit as st
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import pandas as pd
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import matplotlib.pyplot as plt
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import seaborn as sns
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# read the dataset
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df = pd.read_csv('diamonds.csv')
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st.title('Diamond APP sorting festivity
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df = df.drop(["Unnamed: 0"], axis=1)
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#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.
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df = df.drop(df[df["x"]==0].index)
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df = df.drop(df[df["y"]==0].index)
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df = df.drop(df[df["z"]==0].index)
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st.image('diamonds.jpg')
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st.write(f"the price range is {326} to {18823}")
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# users set the price range
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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()))
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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()))
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#users select
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selected_cuts = st.multiselect('choosing cut', df['cut'].unique())
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selected_cuts = st.multiselect('choosing color', df['color'].unique())
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selected_cuts = st.multiselect('choosing clarity', df['clarity'].unique())
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selected_cuts = st.multiselect('choosing carat', df['carat'].unique())
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# select the diamonds
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filtered_diamonds = df[(df['price'] >= min_price) & (df['price'] <= max_price)]
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# show the results
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if not filtered_diamonds.empty:
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st.write(f"find {len(filtered_diamonds)} diamonds for you.")
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st.dataframe(filtered_diamonds)
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# Create a scatterplot based on the selected criteria
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fig, ax = plt.subplots()
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sns.scatterplot(x='carat', y='price', data=filtered_diamonds, ax=ax)
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ax.set_title('Prices by Carat')
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st.pyplot(fig)
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else:
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st.write("No diamonds fit you")
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import streamlit as st
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import pandas as pd
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import matplotlib.pyplot as plt
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import seaborn as sns
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# read the dataset
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df = pd.read_csv('diamonds.csv')
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st.title('Diamond APP sorting festivity')
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df = df.drop(["Unnamed: 0"], axis=1)
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#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.
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df = df.drop(df[df["x"]==0].index)
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df = df.drop(df[df["y"]==0].index)
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df = df.drop(df[df["z"]==0].index)
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st.image('diamonds.jpg')
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st.write(f"the price range is {326} to {18823}")
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# users set the price range
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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()))
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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()))
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#users select
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selected_cuts = st.multiselect('choosing cut', df['cut'].unique())
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selected_cuts = st.multiselect('choosing color', df['color'].unique())
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selected_cuts = st.multiselect('choosing clarity', df['clarity'].unique())
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selected_cuts = st.multiselect('choosing carat', df['carat'].unique())
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# select the diamonds
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filtered_diamonds = df[(df['price'] >= min_price) & (df['price'] <= max_price)]
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# show the results
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if not filtered_diamonds.empty:
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st.write(f"find {len(filtered_diamonds)} diamonds for you.")
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st.dataframe(filtered_diamonds)
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# Create a scatterplot based on the selected criteria
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fig, ax = plt.subplots()
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sns.scatterplot(x='carat', y='price', data=filtered_diamonds, ax=ax)
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ax.set_title('Prices by Carat')
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st.pyplot(fig)
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else:
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st.write("No diamonds fit you")
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