Update app.py

app.py

@@ -1,3 +1,4 @@
+
 # 19feb2023
 #https://huggingface.co/spaces/keras-io/timeseries_forecasting_for_weather/
 
@@ -15,7 +16,7 @@ amonthday = int(today.strftime("%d"))
 
 st.write(type(ayear))
 st.write(("{}-{}-{}").format(ayear,amonth,amonthday))
-adf = pd.DataFrame(columns=[["Date Time","p (mbar)","T (degC)","Tpot (K)","Tdew (degC)","rh (%)","VPmax (mbar)","VPact (mbar)","VPdef (mbar)","sh (g/kg)","H2OC (mmol/mol)","rho (g/m**3)","wv (m/s)","max. wv (m/s)","wd (deg)"]])
+adf = pd.DataFrame(columns=["Date Time","p (mbar)","T (degC)","Tpot (K)","Tdew (degC)","rh (%)","VPmax (mbar)","VPact (mbar)","VPdef (mbar)","sh (g/kg)","H2OC (mmol/mol)","rho (g/m**3)","wv (m/s)","max. wv (m/s)","wd (deg)"])
 
 for i in range(ayear-backlogmax,ayear,1):
 	alink = ("https://data.weather.gov.hk/weatherAPI/opendata/opendata.php?dataType=CLMTEMP&year={}&rformat=csv&station=HKO").format(str(i))
@@ -29,8 +30,7 @@ for i in range(ayear-backlogmax,ayear,1):
 
 		st.write(row[0],row[1],row[2],row[3],row[4],amonth,amonthday)
 		adate = ("{}.{}.{} 00:00:00").format(row[2], row[1], row[0])
-		aarray = [[adate,"",row[4],"","","","","","","","","","","",""]]
-		adf = pd.concat([adf, pd.DataFrame(aarray)], axis=0)
+		adf.append({"Date Time":adate,"T (degC)":row[4],})
 		break
 
 st.dataframe(adf)