Access historical weather data in Australia
Project description
ausweather
Very very very alpha - built for daily/monthly/annual rainfall initially.
Download weather data from BoM via SILO, for now.
E.g. for Kent Town annual rainfall. Find the station number using the BoM Weather Station Directory:
>>> import ausweather
>>> data = ausweather.fetch_bom_station_from_silo(23090, 'kinverarity@hotmail.com')
station #: 23090 name: ADELAIDE (KENT TOWN) title: 23090 ADELAIDE (KENT TOWN) (fetched from SILO on 2020-03-04 16:23:26.395696)
>>> data.keys()
dict_keys(['silo_returned', 'station_no', 'station_name', 'title', 'df', 'annual', 'srn'])
>>> data['df'].info()
RangeIndex: 25630 entries, 1 to 25630
Data columns (total 28 columns):
Date 25630 non-null datetime64[ns]
Day 25630 non-null int32
Date2 25630 non-null object
T.Max 25630 non-null float64
Smx 25630 non-null int32
T.Min 25630 non-null float64
Smn 25630 non-null int32
Rain 25630 non-null float64
Srn 25630 non-null int32
Evap 25630 non-null float64
Sev 25630 non-null object
Radn 25630 non-null float64
Ssl 25630 non-null int32
VP 25630 non-null float64
Svp 25630 non-null int32
RHmaxT 25630 non-null float64
RHminT 25630 non-null float64
FAO56 25630 non-null float64
Mlake 25630 non-null float64
Mpot 25630 non-null float64
Mact 25630 non-null float64
Mwet 25630 non-null float64
Span 25630 non-null float64
Ssp 25630 non-null int32
EvSp 25630 non-null float64
Ses 25630 non-null int32
MSLPres 25630 non-null float64
Sp 25630 non-null int32
dtypes: datetime64[ns](1), float64(16), int32(9), object(2)
memory usage: 4.6+ MB
>>> data['annual'].head()
Date
1950 426.9
1951 677.9
1952 584.9
1953 601.0
1954 439.6
Name: Rain, dtype: float64
>>> ausweather.plot_silo_station(data['annual'], data['annual'].mean(), data['srn'])
List of changes
Version 0.2.1 (3 Mar 2020)
- Fix bug for whitespace in BoM station name
Version 0.2.0 (3 Mar 2020)
- Update, many changes.
Version 0.1.0 (11 Feb 2020)
- Initial release
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