Format plot code and update authors

xCDAT · Apr 16, 2024 · 3775c0d · 3775c0d
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diff --git a/docs/examples/climatology-and-departures.ipynb b/docs/examples/climatology-and-departures.ipynb
@@ -7,11 +7,9 @@
    "source": [
     "# Calculating Climatology and Departures from Time Series Data\n",
     "\n",
-    "Author: [Tom Vo](https://github.com/tomvothecoder/)\n",
+    "Author: [Tom Vo](https://github.com/tomvothecoder/) & [Jiwoo Lee](https://github.com/lee1043/)\n",
     "\n",
-    "Date: 05/27/22\n",
-    "\n",
-    "Last Updated: 2/27/23\n",
+    "Updated: 04/01/24 (v0.6.1)\n",
     "\n",
     "Related APIs:\n",
     "\n",
@@ -4486,7 +4484,7 @@
     "    freq=\"season\",\n",
     "    weighted=True,\n",
     "    season_config={\"dec_mode\": \"DJF\", \"drop_incomplete_djf\": True},\n",
-    ")\n"
+    ")"
    ]
   },
   {

diff --git a/docs/examples/temporal-average.ipynb b/docs/examples/temporal-average.ipynb
@@ -3659,7 +3659,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### Visualize averages derived from monthly data on a specific point"
+    "### Visualize averages derived from monthly data on a specific point\n"
    ]
   },
   {
@@ -3683,15 +3683,21 @@
     "lat_point = 30\n",
     "lon_point = 30\n",
     "\n",
-    "start_year = '2005-01-01'\n",
-    "end_year = '2014-12-31'\n",
+    "start_year = \"2005-01-01\"\n",
+    "end_year = \"2014-12-31\"\n",
     "\n",
     "plt.figure(figsize=(10, 3))\n",
     "ax = plt.subplot()\n",
     "\n",
-    "ds.tas.sel(lat=lat_point, lon=lon_point, time=slice(start_year, end_year)).plot(ax=ax, label=\"monthly (RAW DATA)\", alpha=0.5)\n",
-    "ds_season.tas.sel(lat=lat_point, lon=lon_point, time=slice(start_year, end_year)).plot(ax=ax, label=\"season\", alpha=0.5)\n",
-    "ds_yearly.tas.sel(lat=lat_point, lon=lon_point, time=slice(start_year, end_year)).plot(ax=ax, label=\"yearly\", alpha=0.5)\n",
+    "ds.tas.sel(lat=lat_point, lon=lon_point, time=slice(start_year, end_year)).plot(\n",
+    "    ax=ax, label=\"monthly (RAW DATA)\", alpha=0.5\n",
+    ")\n",
+    "ds_season.tas.sel(lat=lat_point, lon=lon_point, time=slice(start_year, end_year)).plot(\n",
+    "    ax=ax, label=\"season\", alpha=0.5\n",
+    ")\n",
+    "ds_yearly.tas.sel(lat=lat_point, lon=lon_point, time=slice(start_year, end_year)).plot(\n",
+    "    ax=ax, label=\"yearly\", alpha=0.5\n",
+    ")\n",
     "\n",
     "plt.title(\"Seasonal and yearly averages derived from monthly time series\")\n",
     "\n",
@@ -4469,7 +4475,7 @@
     "ds2 = xcdat.open_dataset(\n",
     "    \"https://esgf-data1.llnl.gov/thredds/dodsC/css03_data/CMIP6/CMIP/CSIRO/ACCESS-ESM1-5/historical/r10i1p1f1/3hr/tas/gn/v20200605/tas_3hr_ACCESS-ESM1-5_historical_r10i1p1f1_gn_201001010300-201501010000.nc\",\n",
     "    chunks={\"time\": \"auto\"},\n",
-    "    add_bounds=[\"T\"]\n",
+    "    add_bounds=[\"T\"],\n",
     ")\n",
     "\n",
     "# Unit adjust (-273.15, K to C)\n",
@@ -5166,7 +5172,7 @@
     "ds3 = xcdat.open_dataset(\n",
     "    \"https://esgf-data1.llnl.gov/thredds/dodsC/css03_data/CMIP6/CMIP/CSIRO/ACCESS-ESM1-5/historical/r10i1p1f1/3hr/tas/gn/v20200605/tas_3hr_ACCESS-ESM1-5_historical_r10i1p1f1_gn_201001010300-201501010000.nc\",\n",
     "    chunks={\"time\": \"auto\"},\n",
-    "    add_bounds=[\"T\"]\n",
+    "    add_bounds=[\"T\"],\n",
     ")\n",
     "\n",
     "# Unit adjust (-273.15, K to C)\n",
@@ -6344,7 +6350,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### Visualize averages derived from 3-hourly data on a specific point"
+    "### Visualize averages derived from 3-hourly data on a specific point\n"
    ]
   },
   {
@@ -6368,15 +6374,21 @@
     "lat_point = 30\n",
     "lon_point = 30\n",
     "\n",
-    "start_year = '2010-01-01'\n",
-    "end_year = '2014-12-31'\n",
+    "start_year = \"2010-01-01\"\n",
+    "end_year = \"2014-12-31\"\n",
     "\n",
     "plt.figure(figsize=(10, 3))\n",
     "ax = plt.subplot()\n",
     "\n",
-    "ds2.tas.sel(lat=lat_point, lon=lon_point, time=slice(start_year, end_year)).plot(ax=ax, label=\"3-hourly (RAW DATA)\", alpha=0.5)\n",
-    "ds3_day_avg.tas.sel(lat=lat_point, lon=lon_point, time=slice(start_year, end_year)).plot(ax=ax, label=\"daily\", alpha=0.5)\n",
-    "ds2_monthly_avg.tas.sel(lat=lat_point, lon=lon_point, time=slice(start_year, end_year)).plot(ax=ax, label=\"monthly\", alpha=0.5)\n",
+    "ds2.tas.sel(lat=lat_point, lon=lon_point, time=slice(start_year, end_year)).plot(\n",
+    "    ax=ax, label=\"3-hourly (RAW DATA)\", alpha=0.5\n",
+    ")\n",
+    "ds3_day_avg.tas.sel(\n",
+    "    lat=lat_point, lon=lon_point, time=slice(start_year, end_year)\n",
+    ").plot(ax=ax, label=\"daily\", alpha=0.5)\n",
+    "ds2_monthly_avg.tas.sel(\n",
+    "    lat=lat_point, lon=lon_point, time=slice(start_year, end_year)\n",
+    ").plot(ax=ax, label=\"monthly\", alpha=0.5)\n",
     "\n",
     "plt.title(\"Daily and monthly averages derived from 3-hourly time series\")\n",
     "plt.legend()\n",