df['station'] = station
# Set index
df = df.set_index(['station', 'time'])
# Round decimals
df = df.round(1)
# Append data to full DataFrame
if df_station is None:
df_station = df
else:
df_station = df_station.join(df)
except BaseException:
pass
# Append data to full DataFrame
if df_full is None:
df_full = df_station
else:
df_full = df_full.append(df_station)
except BaseException:
pass
# Write DataFrame into Meteostat database
task.write(df_full, hourly_national)
'wspd':
obs.wind_speed.value('KMH') if obs.wind_speed is not None
and obs.wind_speed.value('KMH') > 0 else None,
'pres':
obs.press.value('HPA') if obs.press is not None else None,
'coco':
get_condicode(obs.weather) if obs.weather is not None else None
})
except BaseException:
pass
# List -> DataFrame
df = pd.DataFrame.from_records(data)
# Calculate humidity data
df['rhum'] = df.apply(lambda row: temp_dwpt_to_rhum(row), axis=1)
# Drop dew point column
df = df.drop('dwpt', axis=1)
# Set index
df = df.set_index(['station', 'time'])
# Round decimals
df = df.round(1)
# Write DataFrame into Meteostat database
task.write(df, hourly_metar)
'rhum': record['data']['instant']['details']['relative_humidity'] if 'relative_humidity' in record['data']['instant']['details'] else None,
'prcp': record['data']['next_1_hours']['details']['precipitation_amount'] if 'next_1_hours' in record['data'] and 'precipitation_amount' in record['data']['next_1_hours']['details'] else None,
'wspd': record['data']['instant']['details']['wind_speed'] * 3.6 if 'wind_speed' in record['data']['instant']['details'] else None,
'wpgt': record['data']['instant']['details']['wind_speed_of_gust'] * 3.6 if 'wind_speed_of_gust' in record['data']['instant']['details'] else None,
'wdir': int(round(record['data']['instant']['details']['wind_from_direction'])) if 'wind_from_direction' in record['data']['instant']['details'] else None,
'pres': record['data']['instant']['details']['air_pressure_at_sea_level'] if 'air_pressure_at_sea_level' in record['data']['instant']['details'] else None
}
# Create DataFrame
df = pd.DataFrame(map(map_data, data['properties']['timeseries']))
# Set index
df['station'] = station[0]
df = df.set_index(['station', 'time'])
# Shift prcp column by 1 (as it refers to the next hour)
df['prcp'] = df['prcp'].shift(1)
# Append data to full DataFrame
if df_full is None:
df_full = df
else:
df_full = df_full.append(df)
except error.HTTPError:
pass
# Write DataFrame into Meteostat database
task.write(df_full, hourly_model)
'WG km/h': 'wspd',
'WSG km/h': 'wpgt',
'N l/m²': 'prcp',
'LDred hPa': 'pres',
'SO %': 'tsun'
}
# Read CSV data
df = pd.read_csv(
'http://www.zamg.ac.at/ogd/',
';',
parse_dates=parse_dates,
usecols=usecols,
decimal=',')
# Rename columns
df = df.rename(columns=names)
# Set index
df = df.set_index(['station', 'time'])
# Convert time zone to UTC
df = df.tz_localize('Europe/Vienna', level='time')
df = df.tz_convert(None, level='time')
# Convert sunshine from percent to minutes
df['tsun'] = round(60 * (df['tsun'] / 100))
# Write DataFrame into Meteostat database
task.write(df, hourly_synop)
decimal=',',
parse_dates=parse_dates)
# Rename columns
df = df.rename(columns=names)
# Snow cm -> mm
df['snow'] = df['snow'].multiply(10)
# Change coco
df['coco'] = df['coco'].apply(get_condicode)
# Add station column
df['station'] = station['id']
# Set index
df = df.set_index(['station', 'time'])
# Append data to full DataFrame
if df_full is None:
df_full = df
else:
df_full = df_full.append(df)
except BaseException:
pass
# Write DataFrame into Meteostat database
task.write(df_full, hourly_synop)
df['dwpt'] = df['dwpt'].div(10)
df['pres'] = df['pres'].div(10)
df['wspd'] = df['wspd'].div(10).apply(ms_to_kmh)
df['prcp'] = df['prcp'].div(10)
# Calculate humidity data
df['rhum'] = df.apply(lambda row: temp_dwpt_to_rhum(row),
axis=1)
# Drop dew point column
df = df.drop('dwpt', axis=1)
# Add station column
df['station'] = station['id']
# Set index
df = df.set_index(['station', 'time'])
# Round decimals
df = df.round(1)
# Write data into Meteostat database
task.write(df, hourly_global)
except BaseException:
pass
# Quit FTP connection
ftp.quit()
# Adapt columns
df['tavg'] = df['tavg'].div(10)
df['tmin'] = df['tmin'].div(10)
df['tmax'] = df['tmax'].div(10)
df['prcp'] = df['prcp'].div(10)
df['wspd'] = df['wspd'].div(10).apply(ms_to_kmh)
df['wpgt'] = df['wpgt'].div(10).apply(ms_to_kmh)
# Add station column
df['station'] = station['id']
# Set index
df = df.set_index(['station', 'time'])
# Append data to full DataFrame
if df_full is None:
df_full = df
else:
df_full = df_full.append(df)
except BaseException:
pass
# Write DataFrame into Meteostat database
task.write(df_full, daily_global)
# Quit FTP connection
ftp.quit()
df = df.rename(columns=NAMES)
# Convert PRES to MSL
df['pres'] = df.apply(lambda row: pres_to_msl(row, altitude), axis=1)
df['wpgt'] = df['wpgt'].apply(ms_to_kmh)
df['wspd'] = df['wspd'].apply(ms_to_kmh)
df['tsun'] = df['tsun'] * 60
df['snow'] = df['snow'] * 10
# Add weather station ID
df['station'] = station
# Set index
df = df.set_index(['station', 'time'])
# Round decimals
df = df.round(1)
# Append data to full DataFrame
if df_full is None:
df_full = df
else:
df_full = df_full.append(df)
except BaseException:
pass
# Write DataFrame into Meteostat database
task.write(df_full, daily_national)
