enhanced code of scatterPlot(refer issue sustainability-lab#43)

vayu/scatterPlot.py

@@ -19,48 +19,28 @@ def scatterPlot(df, x, y, **kwargs):
     import matplotlib.cm as cm
     from math import pi
 
-    pm10 = df.pm10
-    o3 = df.o3
-    ws = df.ws
-    wd = df.wd
-    nox = df.nox
-    no2 = df.no2
-
+
     #########################################
     # converts wind data to randians
-    df = pd.DataFrame({"speed": ws, "direction": wd})
-    df["speed_x"] = df["speed"] * np.sin(df["direction"] * pi / 180.0)
-    df["speed_y"] = df["speed"] * np.cos(df["direction"] * pi / 180.0)
+    #df1 = pd.DataFrame({"speed": ws, "direction": wd})
+    df["speed"+str(x)] = df['ws'] * np.sin(df['wd'] * pi / 180.0)
+    df["speed"+str(y)] = df['ws'] * np.cos(df['wd'] * pi / 180.0)   
     fig, ax = plt.subplots(figsize=(8, 8), dpi=80)
     x0, x1 = ax.get_xlim()
     y0, y1 = ax.get_ylim()
-    ax.set_aspect("equal")
-    _ = df.plot(kind="scatter", x="speed_x", y="speed_y", alpha=0.35, ax=ax)
+    #ax.set_aspect("equal")
+    _ = df.plot(kind="scatter", x="speed"+str(x), y="speed"+str(y), alpha=0.35, ax=ax)
+    plt.show()
+
 
     ####################################
     # simple seaborn plot that shows how given variables relate with one another
-    if x == "nox":
-        x = nox
-    elif x == "no2":
-        x = no2
-    elif x == "o3":
-        x = o3
-    elif x == "pm10":
-        x = pm10
-    if y == "nox":
-        y = nox
-    elif y == "no2":
-        y = no2
-    elif y == "o3":
-        y = o3
-    elif y == "pm10":
-        y = pm10
-
-    sns.jointplot(x=x, y=y, kind="hex")
-
+    sns.jointplot(x=df[x].values, y=df[y].values, kind="hex")
+    plt.xlabel(x)
+    plt.ylabel(y)
     plt.show()
-
-
+    
+    
 # =============================================================================
 # df = pd.read_csv("mydata.csv")
 # scatterPlot(df,'nox','no2')