MAINT: updated pandas frequency

Update the format of the pandas frequency to address FutureWarnings.
pysat · Aug 13, 2024 · c13247c · c13247c
1 parent 1bf5775
commit c13247c
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Showing 3 changed files with 6 additions and 6 deletions.
diff --git a/pysatSpaceWeather/instruments/methods/f107.py b/pysatSpaceWeather/instruments/methods/f107.py
@@ -373,9 +373,9 @@ def calc_f107a(f107_inst, f107_name='f107', f107a_name='f107a', min_pnts=41):
 
     # Resample to the original frequency, if it is not equal to 1 day
     freq = pysat.utils.time.calc_freq(f107_inst.index)
-    if freq != "86400S":
+    if freq != "86400s":
         # Resample to the desired frequency
-        if pds.to_timedelta(freq) < pds.to_timedelta("86400S"):
+        if pds.to_timedelta(freq) < pds.to_timedelta("86400s"):
             f107_fill = f107_fill.resample(freq).ffill()
         else:
             f107_fill = f107_fill.resample(freq).asfreq()

diff --git a/pysatSpaceWeather/instruments/methods/kp_ap.py b/pysatSpaceWeather/instruments/methods/kp_ap.py
@@ -311,7 +311,7 @@ def calc_daily_Ap(ap_inst, ap_name='3hr_ap', daily_name='Ap',
                                                 if tt.hour == 21]])
 
     # Backfill this data
-    ap_data = ap_sel.resample('3H').bfill()
+    ap_data = ap_sel.resample('3h').bfill()
 
     # Save the output for the original time range
     ap_inst[daily_name] = pds.Series(ap_data[1:], index=ap_data.index[1:])

diff --git a/pysatSpaceWeather/instruments/methods/swpc.py b/pysatSpaceWeather/instruments/methods/swpc.py
@@ -479,7 +479,7 @@ def solar_geomag_predictions_download(name, date_array, data_path,
         # Process the Kp data
         hr_strs = ['00-03UT', '03-06UT', '06-09UT', '09-12UT', '12-15UT',
                    '15-18UT', '18-21UT', '21-00UT']
-        data_times['kp'] = pds.date_range(pred_times[0], periods=24, freq='3H')
+        data_times['kp'] = pds.date_range(pred_times[0], periods=24, freq='3h')
 
         for line in kp_raw.split('\n'):
             if line.find("Prob_Mid") >= 0:
@@ -644,7 +644,7 @@ def geomag_forecast_download(name, date_array, data_path,
             kp_day2.append(float(cols[-2]))
             kp_day3.append(float(cols[-1]))
 
-        kp_times = pds.date_range(forecast_date, periods=24, freq='3H')
+        kp_times = pds.date_range(forecast_date, periods=24, freq='3h')
         kp_day = []
         for dd in [kp_day1, kp_day2, kp_day3]:
             kp_day.extend(dd)
@@ -785,7 +785,7 @@ def kp_ap_recent_download(name, date_array, data_path, mock_download_dir=None):
                 sub_aps[i].append(np.int64(ap_sub_lines[i]))
 
         # Create times on 3 hour cadence
-        kp_times = pds.date_range(times[0], periods=(8 * 30), freq='3H')
+        kp_times = pds.date_range(times[0], periods=(8 * 30), freq='3h')
 
         # Put both data sets into DataFrames
         data = {'kp': pds.DataFrame({'mid_lat_Kp': sub_kps[0],