def bfs_population_xls(usecols=None):
"""Return the municipality Excel file as a pandas.DataFrame."""
url = 'https://www.bfs.admin.ch/bfsstatic/dam/assets/9635941/master'
path = DATA_DOWNLOADS_DIR / 'bfs_municipality_population.xlsx'
download_and_save(url, path, load=False)
print(f"Loading {path}...", flush=True)
sheet = pd.read_excel(path,
sheet_name='2018',
header=1,
skipfooter=5,
usecols=usecols)
return sheet
def bfs_residence_work_xls(header=(3, 4), usecols=None):
"""Return the residence-workplace commute Excel file as a pandas.DataFrame."""
url = 'https://www.bfs.admin.ch/bfsstatic/dam/assets/8507281/master'
path = DATA_DOWNLOADS_DIR / 'bfs_residence_work.xlsx'
download_and_save(url, path, load=False)
print(f"Loading {path}...", flush=True)
sheet = pd.read_excel(path,
sheet_name='Commune of residence perspect.',
header=header,
skipfooter=4,
usecols=usecols)
return sheet
def download_matrix_mtx():
"""
Downloads and returns path to .mtx traffic matrix.
"""
from zipfile import ZipFile
zippath = DATA_DOWNLOADS_DIR / "DWV_2017_OeV_Wegematrizen_bin.zip"
download_and_save(
"https://zenodo.org/record/3716134/files/DWV_2017_OeV_Wegematrizen_bin%C3%A4r.zip",
zippath)
mtx_path, = extract_zip(zippath, "_CH_", DATA_DOWNLOADS_DIR)
return mtx_path
def get_shape_file():
"""
Downloads and returns path to shape file with cantons.
"""
zippath = DATA_DOWNLOADS_DIR / "swissBOUNDARIES3D.zip"
download_and_save(
"https://shop.swisstopo.admin.ch/shop-server/resources/products/swissBOUNDARIES3D/download",
zippath)
shapefile = "BOUNDARIES_2020/DATEN/swissBOUNDARIES3D/SHAPEFILE_LV95_LN02/swissBOUNDARIES3D_1_3_TLM_KANTONSGEBIET"
DATA_MAP_DIR = DATA_DOWNLOADS_DIR / "map"
paths = extract_zip(zippath, shapefile, DATA_MAP_DIR)
return os.path.splitext(paths[0])[0]
def download_zones_gpkg():
"""
Downloads and returns path to .gpkg database with zone info.
"""
from zipfile import ZipFile
zippath = DATA_DOWNLOADS_DIR / "Verkehrszonen_Schweiz_NPVM_2017.zip"
download_and_save(
"https://zenodo.org/record/3716134/files/Verkehrszonen_Schweiz_NPVM_2017.zip",
zippath)
gpkgzip = "Verkehrszonen_Schweiz_NPVM_2017_gpkg.zip"
gpkgzip_path, = extract_zip(zippath, gpkgzip, DATA_DOWNLOADS_DIR)
DATA_MAP_DIR = DATA_DOWNLOADS_DIR / "map"
gpkg_path, = extract_zip(gpkgzip_path,
"Verkehrszonen_Schweiz_NPVM_2017.gpkg",
DATA_MAP_DIR)
return gpkg_path
def fetch_openzh_covid_data(*, cache_duration=3600):
"""
Returns a dictionary of lists {canton abbreviation: number of cases per day}.
"""
url = 'https://raw.githubusercontent.com/daenuprobst/covid19-cases-switzerland/master/covid19_cases_switzerland_openzh.csv'
path = DATA_DOWNLOADS_DIR / 'covid19_cases_switzerland_openzh.csv'
raw = download_and_save(url, path, cache_duration=cache_duration)
rows = raw.decode('utf8').split()
cantons = rows[0].split(',')[1:-1] # Skip the "Date" and "CH" cell.
data = {canton: [] for canton in cantons}
for day in rows[1:]: # Skip the header.
cells = day.split(',')[1:-1] # Skip "Date" and "CH".
assert len(cells) == len(cantons), (len(cells), len(cantons))
for canton, cell in zip(cantons, cells):
data[canton].append(float(cell or 'nan'))
return data
def get_field_data_all_cantons(field, cache_duration=1e9):
url = 'https://raw.githubusercontent.com/daenuprobst/covid19-cases-switzerland/master/covid19_' + field + '_switzerland_openzh.csv'
file_path = 'covid19_' + field + '_switzerland_openzh.csv'
path = DATA_DOWNLOADS_DIR / file_path
raw = download_and_save(url, path, cache_duration=cache_duration)
rows = raw.decode('utf8').split()
cantons = rows[0].split(',')[1:-1] # Skip the "Date" and "CH" cell.
data = {canton: [] for canton in cantons}
date = []
for day in rows[1:]: # Skip the header.
cells = day.split(',')[1:-1] # Skip "Date" and "CH".
date.append(date_fromisoformat(day.split(',')[0]))
assert len(cells) == len(cantons), (len(cells), len(cantons))
for canton, cell in zip(cantons, cells):
data[canton].append(float(cell or 'nan'))
data['date'] = date
return data