NearestTime#

Demonstrate synoptic.services.NearestTime

This is very similar to the Latest service, except you can specify the date/time you want the closest time to.

[2]:

from synoptic import NearestTime

import matplotlib.pyplot as plt
from datetime import datetime, timedelta

[3]:

df = NearestTime(
    attime=datetime(2024, 1, 1),
    within=timedelta(hours=1),
    bbox=[-120, 40, -119, 41],
    showemptystations=True,
    vars="air_temp",
    units="english",
).df()
df

🚚💨 Speedy delivery from Synoptic's nearesttime service.
📦 Received data from 12 stations (1.32 seconds).

[3]:

shape: (12, 22)

stid	variable	sensor_index	is_derived	value	date_time	units	id	name	elevation	latitude	longitude	mnet_id	state	timezone	elev_dem	period_of_record_start	period_of_record_end	qc_flagged	is_restricted	restricted_metadata	is_active
str	str	u32	bool	f64	datetime[μs, UTC]	str	u32	str	f64	f64	f64	u32	str	str	f64	datetime[μs, UTC]	datetime[μs, UTC]	bool	bool	bool	bool
"BLUN2"	"air_temp"	1	false	44.0	2023-12-31 23:37:00 UTC	"Fahrenheit"	2169	"BLUEWING MOUNTAIN"	4570.0	40.50147	-119.12161	2	"NV"	"America/Los_Angeles"	4655.5	1998-07-28 00:00:00 UTC	2024-12-19 05:37:00 UTC	false	false	false	true
"BUFN2"	"air_temp"	1	false	44.0	2023-12-31 23:59:00 UTC	"Fahrenheit"	2171	"BUFFALO CREEK"	3940.0	40.58058	-119.78881	2	"NV"	"America/Los_Angeles"	3917.3	1998-07-28 00:00:00 UTC	2024-12-19 05:59:00 UTC	false	false	false	true
"D1623"	null	null	null	null	null	null	24903	"DW1623 Gerlach"	3947.0	40.65133	-119.35517	65	"NV"	"America/Los_Angeles"	3950.1	2008-11-05 00:00:00 UTC	2012-11-22 12:44:00 UTC	null	false	false	false
"UP973"	null	null	null	null	null	null	35321	"PHIL"	3998.0	40.62174	-119.41384	64	"NV"	"America/Los_Angeles"	3930.4	2013-01-04 00:00:00 UTC	2024-12-19 05:40:00 UTC	null	false	false	true
"UP974"	null	null	null	null	null	null	35322	"TREGO"	4005.0	40.78996	-119.07088	64	"NV"	"America/Los_Angeles"	3937.0	2013-01-04 00:00:00 UTC	2024-12-19 04:29:00 UTC	false	false	false	true
…	…	…	…	…	…	…	…	…	…	…	…	…	…	…	…	…	…	…	…	…	…
"UP999"	"air_temp"	1	false	45.0	2023-12-31 23:21:00 UTC	"Fahrenheit"	35347	"REYNRD"	3880.0	40.53186	-119.61354	64	"NV"	"America/Los_Angeles"	3874.7	2013-01-04 00:00:00 UTC	2024-12-19 05:04:00 UTC	false	false	false	true
"NHUA"	"air_temp"	1	false	43.21	2024-01-01 00:00:00 UTC	"Fahrenheit"	41973	"Hualapai Flat"	4055.0	40.90111	-119.33306	62	"NV"	"America/Los_Angeles"	4081.4	2013-12-19 00:00:00 UTC	2024-01-01 07:20:00 UTC	false	false	false	false
"COOPGERN2"	null	null	null	null	null	null	57082	"GERLACH"	3954.0	40.6517	-119.3579	73	"NV"	"America/Los_Angeles"	3927.2	2016-07-18 18:18:00 UTC	2019-05-17 16:00:00 UTC	null	false	false	false
"F0371"	"air_temp"	1	false	44.0	2024-01-01 00:00:00 UTC	"Fahrenheit"	61916	"FW0371 Gerlach"	3953.0	40.65176	-119.35799	65	"NV"	"America/Los_Angeles"	3963.3	2017-02-12 08:19:00 UTC	2024-12-15 18:45:00 UTC	false	false	false	true
"G2749"	null	null	null	null	null	null	181031	"GW2749 Gerlach"	4028.0	40.85933	-119.34183	65	"NV"	"America/Los_Angeles"	4022.3	2023-01-03 22:09:00 UTC	2024-12-19 06:00:00 UTC	null	false	false	true

[4]:

fig, ax = plt.subplots(1, 1, figsize=(10, 10))

for i in df.iter_rows(named=True):
    ax.text(
        i["longitude"],
        i["latitude"] + 0.01,
        f'{i["stid"]}\n{i["value"]} F',
        va="bottom",
        ha="left",
    )
    if i["value"] is None:
        art = ax.scatter(
            i["longitude"],
            i["latitude"],
            color=None,
            ec="k",
            s=100,
        )
    else:
        art = ax.scatter(
            i["longitude"],
            i["latitude"],
            c=i["value"],
            ec="k",
            cmap="Spectral_r",
            vmin=20,
            vmax=80,
            s=100,
        )
plt.colorbar(art, ax=ax, location="bottom", pad=0.05, label="Air Temperature (F)")

[4]:

<matplotlib.colorbar.Colorbar at 0x7fcb9ccf0da0>

../../_images/user_guide_services_tutorials_NearestTime_3_1.png

NearestTime#

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