National Phenology Network (NPN)¶

This page demonstrates how to retrieve data from the National Phenology Network (NPN) using springtime.

Species: Syringa vulgaris
Phenophase (fb): 483 (?)

In [4]:

from springtime.datasets.insitu.npn.rnpn import RNPN, npn_species, npn_phenophases

from springtime.datasets.insitu.npn.rnpn import RNPN, npn_species, npn_phenophases

Data from all the locations¶

In [5]:

# List IDs and names for available species, phenophases
species = npn_species()
phenophases = npn_phenophases()

# List IDs and names for available species, phenophases species = npn_species() phenophases = npn_phenophases()

In [6]:

phenophases

phenophases

Out[6]:

	phenophase_id	phenophase_name	phenophase_category	color	pheno_class_id
0	56	First leaf	Leaves	NaN	1
1	57	75% leaf elongation	Leaves	NaN	2
2	58	First flower	Flowers	NaN	7
3	59	Last flower	Flowers	NaN	9
4	60	First fruit ripe	Fruits	NaN	12
...	...	...	...	...	...
194	545	Post-dormant nymphs	Development	Brown3	113
195	546	Crawlers	Development	Brown3	112
196	547	Egg laying	Reproduction	Brown2	136
197	548	Egg laying	Reproduction	Brown2	136
198	549	Mating	Reproduction	Brown2	82

199 rows × 5 columns

In [13]:

species[species.species_id==36]

species[species.species_id==36]

Out[13]:

	species_id	common_name	genus	genus_id	genus_common_name	species	kingdom	itis_taxonomic_sn	functional_type	class_id	class_common_name	class_name	order_id	order_common_name	order_name	family_id	family_name	family_common_name
421	36	common lilac	Syringa	1035	Lilacs (Syringa)	vulgaris	Plantae	32996.0	Deciduous broadleaf	15	Flowering Plants	Magnoliopsida	83	Mint, Olive and Plantain Families	Lamiales	305	Oleaceae	Olive Family

In [12]:

phenophases[phenophases.phenophase_id==483]

phenophases[phenophases.phenophase_id==483]

Out[12]:

	phenophase_id	phenophase_name	phenophase_category	color	pheno_class_id
138	483	Leaves	Leaves	Green1	3

In [8]:

# Create a data instance
dataset = RNPN(species_ids={"name": "Syringa", "items":[36]}, 
               phenophase_ids={"name": "leaves", "items":[483]}, 
               years=[2010, 2011])
dataset

# Create a data instance dataset = RNPN(species_ids={"name": "Syringa", "items":[36]}, phenophase_ids={"name": "leaves", "items":[483]}, years=[2010, 2011]) dataset

Out[8]:

RNPN(dataset='RNPN', years=YearRange(start=2010, end=2011), species_ids=NamedIdentifiers(name='Syringa', items=[36]), phenophase_ids=NamedIdentifiers(name='leaves', items=[483]), area=None, use_first=True, aggregation_operator='min')

In [9]:

# Download data
dataset.download()

# Download data dataset.download()

/tmp/data/rnpn/rnpn_npn_data_y_2010_Syringa_leaves.csv already exists, skipping
/tmp/data/rnpn/rnpn_npn_data_y_2011_Syringa_leaves.csv already exists, skipping

In [10]:

# Load downloded data as a dataframe
df = dataset.load()
df

# Load downloded data as a dataframe df = dataset.load() df

Out[10]:

	geometry	datetime	leaves_doy
0	POINT (-91.37602 38.38862)	2010-03-01	60
1	POINT (-79.97169 39.53892)	2010-05-05	125
2	POINT (-85.60993 39.79147)	2010-04-12	102
3	POINT (-76.62881 40.94780)	2010-04-05	95
4	POINT (-91.69318 41.29201)	2010-04-12	102
5	POINT (-91.48378 41.88856)	2010-04-04	94
6	POINT (-74.29987 42.10105)	2010-04-09	99
7	POINT (-77.43737 42.89832)	2010-04-08	98
8	POINT (-83.05326 35.59232)	2011-04-13	103
9	POINT (-80.53153 35.59463)	2011-03-14	73
10	POINT (-84.17097 35.65687)	2011-03-10	69
11	POINT (-86.96690 36.39927)	2011-02-25	56
12	POINT (-91.78845 36.65863)	2011-03-21	80
13	POINT (-90.15485 38.71774)	2011-03-19	78
14	POINT (-83.82374 38.82653)	2011-03-23	82
15	POINT (-84.52015 38.88288)	2011-03-21	80
16	POINT (-85.24599 38.99372)	2011-04-11	101
17	POINT (-81.54738 39.24728)	2011-03-18	77
18	POINT (-77.48402 39.72047)	2011-04-11	101
19	POINT (-79.89363 40.66472)	2011-04-04	94
20	POINT (-73.11993 40.85247)	2011-03-22	81
21	POINT (-77.44374 40.98488)	2011-04-14	104
22	POINT (-80.29738 41.04120)	2011-04-13	103
23	POINT (-74.59502 41.12333)	2011-04-30	120
24	POINT (-80.81221 41.13425)	2011-05-01	121
25	POINT (-85.12750 41.21440)	2011-04-15	105
26	POINT (-72.63346 41.91122)	2011-04-27	117
27	POINT (-80.33588 42.01947)	2011-04-29	119
28	POINT (-79.26913 42.09705)	2011-04-23	113
29	POINT (-80.01417 42.13030)	2011-04-20	110
30	POINT (-73.65140 42.33499)	2011-04-18	108
31	POINT (-83.21512 42.49105)	2011-04-23	113
32	POINT (-88.16408 42.98386)	2011-05-12	132

In [ ]: