Null timestamps example#

This notebook shows how to retrieve timestamps where the requested metrics return null values.

API-24SEA endpoint: https://api.24sea.eu/routes/v1/datasignals/null_timestamps

[1]:

# **Package Imports**
# - From the Python Standard Library
import logging
import os
import sys

# - API-24SEA
from api_24sea.version import __version__, parse_version
from api_24sea.datasignals.core import AsyncAPI

[2]:

# **Package Version**
print(f"Package {parse_version(__version__)}")

# **Notebook Configuration**
logger = logging.getLogger()
logger.setLevel(logging.WARNING)

Package Version(major=2, minor=1, patch=6, release=None, num=None)

Login Credentials

Do not store API credentials in plain text in your notebook. Rather use the python-dotenv package to load environment variables from a .env file.

[3]:

# **Set Sample API Credentials**
os.environ["API_24SEA_USERNAME"] = "Sample.User"
os.environ["API_24SEA_PASSWORD"] = "CheckOutSomeData!"

[4]:

# **Package Versions**
print(f"Package {parse_version(__version__)}")
# **Notebook Configuration**
logger = logging.getLogger()
logger.setLevel(logging.WARNING)

Package Version(major=2, minor=1, patch=6, release=None, num=None)

[5]:

# **API Initialization**
# API initialization can happen either explicitly via the API class, or
# implicitly when using the pandas `datasignals` accessor.
# In this example we will use the Pandas accessor.
api = AsyncAPI()
# The Metrics Overview is a table containing all the locations and metrics
# available in the API, together with their metadata. It is useful to query it
# before getting data, to check which locations and metrics are available for
# the site you want to query.
m_o = api.metrics_overview

# site is the wind farm name you want to query. The parameter can also be
# a list of site names, e.g. ["windfarm", "windfarm2"]. Matching is
# case-insensitive and passing the "site-id" is also accepted, e.g. "windfarm"
# will match "WindFarm", but also "WF", "wf", etc.
site = "windfarm"
# Matching locations from Metrics Overview for the specified site
# Also partial names of locations are accepted, e.g. "a01" will match
# all locations containing "a01" in their name, such as "A01", "a01". Matching
# is case-insensitive.
locations = m_o[m_o["site"].str.lower() == site]["location"].unique().tolist()
# Metrics: partial matches and regexes are accepted.
# Spaces are interpreted as .* in the name.
# If you want to query all metrics, pass "all" or ["all"].
metrics = ["mean windspeed", "mean power", "mean yaw", "mean rpm",
           "mean pitch", "mean winddirection", "mean inc"]
# Start and end timestamp in ISO 8601 format. The API accepts also other
# formats, such as the one provided by
# https://www.elastic.co/docs/reference/elasticsearch/rest-apis/common-options#date-math
start_timestamp = "2020-03-01T00:00:00Z"
end_timestamp = "2020-06-01T00:00:00Z"

data = await api.get_null_timestamps(site, locations, metrics,
                                     start_timestamp, end_timestamp)
data

Getting chunk: [1-1]: 100%|██████████| 1/1 [00:04<00:00,  4.72s/it]

[5]:

	metric	timestampsnotfound	site	location	data_group	statistic	short_hand	print_str
0	mean_WF_A01_pitch	[2020-03-04T10:00:00+00:00, 2020-03-05T09:10:0...	WindFarm	WFA01	scada	mean	pitch	Pitch
1	mean_WF_A01_power	[2020-03-04T10:00:00+00:00, 2020-03-05T09:10:0...	WindFarm	WFA01	scada	mean	power	Power
2	mean_WF_A01_rpm	[2020-03-04T10:00:00+00:00, 2020-03-05T09:10:0...	WindFarm	WFA01	scada	mean	rpm	Rotor speed
3	mean_WF_A01_TP_INC_LAT015_DEG240_X_nr1	[2020-03-22T14:20:00+00:00, 2020-03-22T14:30:0...	WindFarm	WFA01	inclination	mean	TP_INC_LAT015_DEG240_X_nr1	TP INC LAT015 DEG240 X nr1
4	mean_WF_A01_TP_INC_LAT015_DEG240_Y_nr2	[2020-03-22T14:20:00+00:00, 2020-03-22T14:30:0...	WindFarm	WFA01	inclination	mean	TP_INC_LAT015_DEG240_Y_nr2	TP INC LAT015 DEG240 Y nr2
5	mean_WF_A01_winddirection	[2020-03-04T10:00:00+00:00, 2020-03-05T09:10:0...	WindFarm	WFA01	scada	mean	winddirection	Wind direction
6	mean_WF_A01_windspeed	[2020-03-04T10:00:00+00:00, 2020-03-05T09:10:0...	WindFarm	WFA01	scada	mean	windspeed	Wind speed
7	mean_WF_A01_yaw	[2020-03-04T10:00:00+00:00, 2020-03-05T09:10:0...	WindFarm	WFA01	scada	mean	yaw	Yaw
8	mean_WF_A02_pitch	[2020-03-04T10:00:00+00:00, 2020-03-05T09:10:0...	WindFarm	WFA02	scada	mean	pitch	Pitch
9	mean_WF_A02_power	[2020-03-04T10:00:00+00:00, 2020-03-05T09:10:0...	WindFarm	WFA02	scada	mean	power	Power
10	mean_WF_A02_rpm	[2020-03-04T10:00:00+00:00, 2020-03-05T09:10:0...	WindFarm	WFA02	scada	mean	rpm	Rotor speed
11	mean_WF_A02_TP_INC_LAT015_DEG240_X_nr1	[2020-03-12T04:00:00+00:00, 2020-03-12T04:10:0...	WindFarm	WFA02	inclination	mean	TP_INC_LAT015_DEG240_X_nr1	TP INC LAT015 DEG240 X nr1
12	mean_WF_A02_TP_INC_LAT015_DEG240_Y_nr2	[2020-03-12T04:00:00+00:00, 2020-03-12T04:10:0...	WindFarm	WFA02	inclination	mean	TP_INC_LAT015_DEG240_Y_nr2	TP INC LAT015 DEG240 Y nr2
13	mean_WF_A02_winddirection	[2020-03-04T10:00:00+00:00, 2020-03-05T09:10:0...	WindFarm	WFA02	scada	mean	winddirection	Wind direction
14	mean_WF_A02_windspeed	[2020-03-04T10:00:00+00:00, 2020-03-05T09:10:0...	WindFarm	WFA02	scada	mean	windspeed	Wind speed
15	mean_WF_A02_yaw	[2020-03-04T10:00:00+00:00, 2020-03-05T09:10:0...	WindFarm	WFA02	scada	mean	yaw	Yaw