Add rolling average

plot_eclipse_data.py

@@ -11,8 +11,14 @@ from pandas.plotting import register_matplotlib_converters
 
 register_matplotlib_converters()
 
-df_23 = pd.read_csv("data1623310995.txt", parse_dates=[0], skiprows=1)
-df_70 = pd.read_csv("data1623311707.txt", parse_dates=[0], skiprows=1)
+df_23 = pd.read_csv("data1623310995.txt",
+                    parse_dates=[0],
+                    skiprows=1,
+                    index_col=0).rolling(10).mean()
+df_70 = pd.read_csv("data1623311707.txt",
+                    parse_dates=[0],
+                    skiprows=1,
+                    index_col=0).rolling(10).mean()
 
 eclipse_starttime = datetime(2021, 6, 10, 9, 21)
 eclipse_endtime = datetime(2021, 6, 10, 11, 34)
@@ -22,14 +28,12 @@ matplotlib.rcParams.update({'font.size': 16})
 plot_start = datetime(2021, 6, 10, 8, 30, 0)
 plot_end = datetime(2021, 6, 10, 12, 0, 0)
 
-df_70_selected = df_70[(df_70["time (UTC)"] > plot_start)
-                       & (df_70["time (UTC)"] < plot_end)]
-df_23_selected = df_23[(df_23["time (UTC)"] > plot_start)
-                       & (df_23["time (UTC)"] < plot_end)]
+df_70_selected = df_70[(df_70.index > plot_start) & (df_70.index < plot_end)]
+df_23_selected = df_23[(df_23.index > plot_start) & (df_23.index < plot_end)]
 
 fig, ax = plt.subplots(figsize=(16, 9))
 sc1 = ax.scatter(
-    df_23_selected["time (UTC)"],
+    df_23_selected.index,
     df_23_selected["signal"] / 5050,
     s=2,
     label="Signal at 1330MHz",
@@ -39,7 +43,7 @@ ax2 = ax.twinx()
 ax.xaxis.set_major_formatter(mdates.DateFormatter("%H:%M:%S"))
 ax2.xaxis.set_major_formatter(mdates.DateFormatter("%H:%M:%S"))
 sc2 = ax2.scatter(
-    df_70_selected["time (UTC)"],
+    df_70_selected.index,
     df_70_selected["signal"] / 8e6,
     s=2,
     color="red",