concatenating precipitation and pressure

precipitation.py

@@ -1,9 +1,10 @@
+from datetime import datetime
+
+import pandas as pd
+import plotly.graph_objects as go
 import requests
 from discord_webhook import DiscordEmbed, DiscordWebhook  # Connect to discord
 from environs import Env  # For environment variables
-import pandas as pd
-import plotly.graph_objects as go
-
 
 env = Env()
 env.read_env()  # read .env file, if it exists
@@ -16,9 +17,24 @@ def embed_to_discord():
     # Elevation
     embed.add_embed_field(name='⛰️ Elevation', value=f"{data['elevation']} m")
 
-    # Precip Total
-    embed.add_embed_field(
-        name='🌧️ Total', value=f"{data['daily']['precipitation_sum'][0]} {data['daily_units']['precipitation_sum']}")
+    # Precip Total but only if precipitation_sum > 0
+    if any(elem != 0 for elem in df['precipitation']):
+        embed.add_embed_field(
+            name='🌧️ Total', value=f"{data['daily']['precipitation_sum'][0]} {data['daily_units']['precipitation_sum']}")
+
+    # Pressure High
+    surface_pressure_high = df.loc[df["surface_pressure"].idxmax()]
+    surface_pressure_high_time = datetime.fromisoformat(
+        surface_pressure_high["time"]).strftime("%H:%M")
+    embed.add_embed_field(name='☁️ Pressure ⬆️ High',
+                          value=f"{surface_pressure_high['surface_pressure']} hPa at {surface_pressure_high_time}", inline=True)
+
+    # Pressure Low
+    surface_pressure_low = df.loc[df["surface_pressure"].idxmin()]
+    surface_pressure_low_time = datetime.fromisoformat(
+        surface_pressure_low["time"]).strftime("%H:%M")
+    embed.add_embed_field(name='☁️ Pressure ⬇️ Low',
+                          value=f"{surface_pressure_low['surface_pressure']} hPa at {surface_pressure_low_time}", inline=True)
 
     # set image
     embed.set_image(url='attachment://fig1.png')
@@ -41,56 +57,76 @@ def embed_to_discord():
 lat = env('LATITUDE')
 long = env('LONGITUDE')
 
+# baseline to measure the difference in on the graph in hPa
+STANDARD_PRESSURE = 1013.25
+
 data = requests.get(
-    f"https://api.open-meteo.com/v1/forecast?latitude={lat}&longitude={long}&daily=precipitation_sum&hourly=rain,showers,snowfall&models=best_match&forecast_days=1&timezone=EST").json()
+    f"https://api.open-meteo.com/v1/forecast?latitude={lat}&longitude={long}&daily=precipitation_sum&hourly=surface_pressure,precipitation&models=best_match&forecast_days=1&timezone=EST").json()
 
 all_categories = {}
 for categories in data["hourly"]:
     all_categories[categories] = data["hourly"][categories]
 df = pd.DataFrame(all_categories)
 
-if data["daily"]["precipitation_sum"][0] > 0:
-    fig = go.Figure()
+fig = go.Figure()
 
-    fig.add_trace(go.Scatter(
-        x=df["time"],
-        y=df["rain"],
-        fill='tozeroy',
-        mode='lines',
-        name="rain"
-    ))
-    fig.add_trace(go.Scatter(
-        x=df["time"],
-        y=df["showers"],
-        fill='tozeroy',
-        mode='lines',
-        name="showers"
-    ))
-    fig.add_trace(go.Scatter(
-        x=df["time"],
-        y=df["snowfall"],
-        fill='tozeroy',
-        mode='lines',
-        name="snowfall"
-    ))
 
-    fig.update_yaxes(ticklabelstep=2)
+fig.add_trace(go.Scatter(
+    x=df['time'],
+    y=df['surface_pressure'] - STANDARD_PRESSURE,
+    name="Relative Pressure (STP)",
+    fill='tozeroy',
+))
 
-    # Labels
-    fig.update_layout(title={'text': 'Precipitation vs. Time', 'x': 0.5, 'xanchor': 'center'},
-                      yaxis_zeroline=True,
-                      xaxis_zeroline=True,
-                      xaxis_title="Time",
-                      yaxis_title="Millimeters of Precipitation")
-
-    # Attribution
-    fig.add_annotation(text="By: Ibrahim Mudassar",
-                       xref="paper", yref="paper",
-                       x=1, y=-0.14,
-                       showarrow=False,
-                       align="center",
-                       font=dict(size=9))
-
-    fig.write_image("fig1.png", width=1080, height=720)
+if any(elem != 0 for elem in df['precipitation']):
+    fig.add_trace(go.Scatter(
+        x=df['time'],
+        y=df['precipitation'],
+        name="Precipitation",
+        yaxis="y2"
+    ))
 
-    embed_to_discord()
+# Create axis objects
+fig.update_layout(
+    yaxis=dict(
+        title="yaxis title",
+        titlefont=dict(
+            color="#1f77b4"
+        ),
+        tickfont=dict(
+            color="#1f77b4"
+        )
+    ),
+    yaxis2=dict(
+        title="yaxis2 title",
+        titlefont=dict(
+            color="#ff7f0e"
+        ),
+        tickfont=dict(
+            color="#ff7f0e"
+        ),
+        anchor="x",
+        overlaying="y",
+        side="right",
+    ),
+)
+
+# Labels
+fig.update_layout(title={'text': 'Pressure vs. Time', 'x': 0.5, 'xanchor': 'center'},
+                  yaxis2_zeroline=True,
+                  xaxis_zeroline=True,
+                  xaxis_title="Time",
+                  yaxis_title="Difference from STP (In hPa)")
+
+
+# Attribution
+fig.add_annotation(text="By: Ibrahim Mudassar",
+                   xref="paper", yref="paper",
+                   x=1, y=-0.14,
+                   showarrow=False,
+                   align="center",
+                   font=dict(size=9))
+
+fig.write_image("fig1.png", width=1080, height=720)
+
+embed_to_discord()