here we go!

requirements.txt

@@ -4,4 +4,6 @@ pandas
 streamlit
 scikit-learn
 numpy
-plotly
+plotly
+streamlit-drawable-canvas
+pillow

streamlit.py

@@ -1,96 +1,27 @@
-# %%
-# packages
 import streamlit as st
-import polars as pl
-import plotly.express as px
-import plotly.io as pio
-pio.templates.default = "simple_white"
-
-st.set_page_config(layout="wide")
-# %%
-# Data
-
-dat = pl.read_csv("dat_munged.csv")
-info = pl.read_csv("Metadata_Indicator_API_Download_DS2_en_csv_v2_5657328.csv").rename({"INDICATOR_CODE":"Indicator Code", "INDICATOR_NAME":"Indicator Name"})
-dat_vars = pl.read_csv("dat_vars.csv")
-
-# %%
-# Example Chart
-# drop_country =  ["ZAF"]
-# indicator_code = "NY.GDP.PCAP.PP.KD"
-list_name = dat_vars.select("Indicator Name").to_series().to_list()
-list_code = dat_vars.select("Indicator Code").to_series().to_list()
-list_country_code = ["ZAF", "ZWE", "KEN", "NGA", "GHA", "COD"]
-list_country_name = ["South Africa", "Zimbabwe", "Kenya", "Nigeria", "Ghana", "Congo, Dem. Rep."]
-
-
-drop_country = st.sidebar.multiselect("Remove Country (Country Code)", list_country_code)
-
-checked_var = st.sidebar.checkbox("Use Variable Name")
-
-
-if checked_var:
-    indicator_name = st.sidebar.selectbox("Select your variable", list_name)
-    indicator_code = dat_vars.filter(pl.col("Indicator Name") == indicator_name).select("Indicator Code").to_series()[0]
-else:
-    indicator_code = st.sidebar.selectbox("Select your variable", list_code)
-    indicator_name = dat_vars.filter(pl.col("Indicator Code") == indicator_code).select("Indicator Name").to_series()[0]
-
-title_text = indicator_name
-subtitle_text = info.filter(pl.col("Indicator Code") == indicator_code).select("SOURCE_NOTE").to_series()[0]
-
-y_axis_title = indicator_name[indicator_name.find("(")+1:indicator_name.find(")")]
-
-use_dat = dat.filter((pl.col("Indicator Code").is_in([str(indicator_code)])) & (~pl.col("Country Code").is_in(drop_country)) & (pl.col("value").is_not_null()))
-
-sp = px.line(use_dat.to_pandas(),
-    x="year", y="value", color="Country Name", markers=True,
-    labels = {"year":"Year", "value":y_axis_title},
-    title = title_text)
-
-st.markdown("## Country performance over time")
-
-st.markdown("_You can read about streamlit [here](slides.html)_")
-
-st.markdown("__" + title_text + "__")
-
-st.markdown(subtitle_text)
-
-st.markdown("### Chart")
-st.markdown("_Use the expand arrows visible when you hover over the upper right corner of the chart to see it in full screen._")
-
-sp
-
-st.markdown("### Table: " + title_text)
-
-display_dat = use_dat.select("Country Code", "Indicator Name", "year", "value")
-
-st.dataframe(
-  display_dat\
-    .pivot(index="year", on="Country Code", values="value", aggregate_function="first")\
-    .sort(pl.col("year"),descending=True), hide_index=True,
-    use_container_width=True,
-    column_config={
-        "value": y_axis_title,
-        "year": st.column_config.NumberColumn(
-            "Year",
-            help="Year of data",
-            format="%.0f"
-        )})
-
-
-def convert_df(df):
-    return df.write_csv().encode('utf-8')
-
-csv = convert_df(display_dat)
-
-st.download_button("Download Data", data = csv, file_name = "data.csv", mime="text/csv")
-
-st.markdown("## My presentation")
-
-# Read file and keep in variable
-with open('slides.html','r') as f: 
-    html_data = f.read()
-
-## Show in webpage
-st.components.v1.html(html_data,height=1500)
+from streamlit_drawable_canvas import st_canvas
+from PIL import Image
+
+# Create a camera input widget
+picture = st.camera_input("Take a picture")
+
+if picture:
+    # Convert the picture to an Image object
+    img = Image.open(picture)
+
+    # Display the drawable canvas with the image
+    canvas_result = st_canvas(
+        fill_color="rgba(255, 165, 0, 0.3)",  # Fixed fill color with some opacity
+        stroke_width=2,
+        stroke_color="black",
+        background_image=img,
+        update_streamlit=True,
+        height=img.height,
+        width=img.width,
+        drawing_mode="freedraw",
+        key="canvas",
+    )
+
+    # Display the resulting image with drawings
+    if canvas_result.image_data is not None:
+        st.image(canvas_result.image_data)