Initial commit

.gitattributes

@@ -29,3 +29,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+*.csv filter=lfs diff=lfs merge=lfs -text

app.py

@@ -0,0 +1,84 @@
+import streamlit as st
+st.set_page_config(layout="wide")
+import pandas as pd
+import plotly.express as px
+
+# titles
+
+st.sidebar.markdown("## HDB Resale Prices")
+st.sidebar.markdown("Flat Options")
+
+# read data
+
+@st.cache
+def load_data():
+    return pd.read_csv("data.csv")
+
+df = load_data()
+
+# setup UI
+
+town_options = list(df["town"].unique())
+town_options.sort()
+town_options = ["ALL"] + town_options
+town = st.sidebar.selectbox(label="Town",
+                            options=town_options)
+
+if town != "ALL":
+    df = df[df['town']==town]
+
+flat_type_options = list(df["flat_type"].unique())
+flat_type_options.sort()
+flat_type_options = ["ALL"] + flat_type_options
+flat_type = st.sidebar.selectbox(label="Flat Type",
+                                 options=flat_type_options)
+
+if flat_type != "ALL":
+    df = df[df['flat_type']==flat_type]
+
+flat_model_options = list(df["flat_model"].unique())
+flat_model_options.sort()
+flat_model_options = ["ALL"] + flat_model_options
+flat_model = st.sidebar.selectbox(label="Flat Model",
+                                 options=flat_model_options)
+
+if flat_model != "ALL":
+    df = df[df['flat_model']==flat_model]
+
+storey_options = list(df["storey_range"].unique())
+storey_options.sort()
+storey_options = ["ALL"] + storey_options
+storey_range = st.sidebar.selectbox(label="Storey Range",
+                                    options=storey_options)
+
+if storey_range != "ALL":
+    df = df[df['storey_range']==storey_range]
+
+floor_area_options = list(df["floor_area_sqm"].unique())
+floor_area_options.sort()
+floor_area_options = ["ALL"] + floor_area_options
+floor_area = st.sidebar.selectbox(label="Floor Area",
+                                    options=floor_area_options)
+
+if floor_area != "ALL":
+    df = df[df['floor_area_sqm']==floor_area]
+
+#df = df.drop(labels=["town", "flat_type", "storey_range", "floor_area_sqm"], axis="columns")
+
+df = df.drop(labels=["town", ], axis="columns")
+
+df = df.sort_values(by="month", ascending=False)
+#df["floor_area_sqm"] = df["floor_area_sqm"].astype("int")
+df["resale_price"] = df["resale_price"].astype("int")
+
+st.markdown("### Selected Data")
+
+st.dataframe(data=df)
+
+st.markdown("### Visualization of Selected Data")
+
+fig = px.box(df,
+              x="month", y="resale_price",
+              title='Resale Price over time')
+
+st.plotly_chart(fig, use_container_width=True)

data.csv

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:795f6fbb98a7edbc9bd644b095fe74d0a7d8c89dd1f95fdb3996b8490b291ec0
+size 13309175

requirements.txt

@@ -0,0 +1,4 @@
+streamlit
+pandas
+plotly
+