Meteostat 1.4.3

examples/normals/simple.py

@@ -12,8 +12,8 @@
 from meteostat import Normals
 
 # Get normals
-data = Normals('10637')
-data = data.fetch()
+data = Normals('72407')
+data = data.normalize().fetch()
 
 # Plot chart
 data.plot(y=['tavg', 'tmin', 'tmax'])

meteostat/__init__.py

@@ -12,7 +12,7 @@
 """
 
 __appname__ = 'meteostat'
-__version__ = '1.4.2'
+__version__ = '1.4.3'
 
 from .interface.stations import Stations
 from .interface.point import Point

meteostat/interface/normals.py

@@ -15,6 +15,7 @@
 import pandas as pd
 from meteostat.core.cache import get_file_path, file_in_cache
 from meteostat.core.loader import processing_handler, load_handler
+from meteostat.core.warn import warn
 from meteostat.utilities.aggregations import weighted_average
 from meteostat.interface.base import Base
 from meteostat.interface.point import Point
@@ -249,6 +250,43 @@ def __init__(
  if self.max_age > 0:
  self.clear_cache()
 
+ def normalize(self):
+ """
+ Normalize the DataFrame
+ """
+
+ # Create temporal instance
+ temp = copy(self)
+
+ if self.count() == 0:
+ warn('Pointless normalization of empty DataFrame')
+
+ else:
+ # Go through list of weather stations
+ for station in temp._stations:
+ # Get periods
+ periods = temp._data[temp._data.index.get_level_values(
+ 'station') == station].index.unique('end')
+ # Go through all periods
+ for period in periods:
+ # Create DataFrame
+ df = pd.DataFrame(
+ columns=temp._columns[temp._first_met_col:])
+ # Populate index columns
+ df['month'] = range(1, 13)
+ df['station'] = station
+ df['start'] = period - 29
+ df['end'] = period
+ # Set index
+ df.set_index(
+ ['station', 'start', 'end', 'month'], inplace=True)
+ # Merge data
+ temp._data = pd.concat([temp._data, df], axis=0).groupby(
+ ['station', 'start', 'end', 'month'], as_index=True).first()
+
+ # Return class instance
+ return temp
+
  def fetch(self) -> pd.DataFrame:
  """
  Fetch DataFrame

setup.py

@@ -15,7 +15,7 @@
 # Setup
 setup(
  name='meteostat',
- version='1.4.2',
+ version='1.4.3',
  author='Meteostat',
  author_email='[email protected]',
  description='Access and analyze historical weather and climate data with Python.',