update app and functions

app.py

@@ -3,7 +3,7 @@ import hopsworks
 import joblib
 import pandas as pd
 import datetime
-from functions import get_weather_data_weekly, data_encoder, get_aplevel
+from functions import get_weather_data_weekly, data_encoder, get_aplevel, get_color
 from PIL import Image
 
 
@@ -45,19 +45,19 @@ model = joblib.load(model_dir + "/aqi_model.pkl")
 st.write("Succesfully loaded!✔️")
 st.sidebar.write("-" * 36)
 
-fancy_header("Making AQI pedictions for the next week..")
+fancy_header("Making AQI predictions for the next 7 days")
 
 preds = model.predict(data_encoder(weekly_data)).astype(int)
 
-poll_level = get_aplevel(preds.T.reshape(-1, 1))
+air_pollution_level = ['Good', 'Moderate', 'Unhealthy for sensitive Groups','Unhealthy' ,'Very Unhealthy', 'Hazardous']
+poll_level = get_aplevel(preds.T.reshape(-1, 1), air_pollution_level)
 
 next_week_datetime = [today + datetime.timedelta(days=d) for d in range(7)]
-
-next_week_str = [f"{days.strftime('%Y-%m-%d')}, {days.strftime('%A')}" for days in next_week_datetime]
+next_week_str = [f"{days.strftime('%A')}, {days.strftime('%Y-%m-%d')}" for days in next_week_datetime]
 
 df = pd.DataFrame(data=[preds, poll_level], index=["AQI", "Air pollution level"], columns=next_week_str)
 
 st.write("Here they are!")
-st.dataframe(df.style.apply) # ref to function color_aq
+st.dataframe(df.style.apply(get_color, subset=(["Air pollution level"], slice(None))))
 
 st.button("Re-run")

functions.py

@@ -163,12 +163,18 @@ def data_encoder(X):
     X['conditions'] = OrdinalEncoder().fit_transform(X[['conditions']])
     return X
 
-def get_aplevel(temps:np.ndarray) -> list:
+def get_aplevel(temps:np.ndarray, table:list):
     boundary_list = np.array([0, 50, 100, 150, 200, 300]) # assert temps.shape == [x, 1]
     redf = np.logical_not(temps<=boundary_list) # temps.shape[0] x boundary_list.shape[0] ndarray
     hift = np.concatenate((np.roll(redf, -1)[:, :-1], np.full((temps.shape[0], 1), False)), axis = 1)
     cat = np.nonzero(np.not_equal(redf,hift))
 
+    level = [table[el] for el in cat[1]]
+    return level
+
+def get_color(level:list):
     air_pollution_level = ['Good', 'Moderate', 'Unhealthy for sensitive Groups','Unhealthy' ,'Very Unhealthy', 'Hazardous']
-    level = [air_pollution_level[el] for el in cat[1]]
-    return level
+    color_list = ["Green", "Yellow", "DarkOrange", "Red", "Purple", "DarkRed"]
+    ind = [air_pollution_level.index(lel) for lel in level]
+    text = [f"color:{color_list[idex]};" for idex in ind]
+    return text