def dataset_to_basic_sheets(abs_filepath):
dataset = get_dataset_df(abs_filepath)
def remove_useless_columns(df):
columns_to_remove = [x for x in df.columns if 'Unnamed:' in str(x)]
return df.drop(columns_to_remove, 1)
def remove_rows_with_no_type(df):
return df[df.type.notnull()]
dataset = remove_useless_columns(dataset)
dataset = remove_rows_with_no_type(dataset)
names = dataset[dataset.type.map(lambda x: x in ['data', 'param'])][['var', 'name']]
validate_variable_names(names['var'].tolist())
equations = dataset[dataset.type == 'eq'][['name']]
def get_data_years(df):
years = df[dataset.type == 'is_forecast'].iloc[0]
return [year for year, is_forecast in years.iteritems() if is_forecast == 0]
data = dataset[dataset.type == 'data'][['var'] + get_data_years(dataset)]
controls = dataset[dataset.type == 'param'].drop(['type', 'name'], 1)
def to_array_with_years_and_values(df):
result = np.concatenate(([np.array(df.columns)], df.as_matrix().astype(object)))
result[0][0] = ''
return result
write_array_to_xl_using_xlwings(to_array_with_years_and_values(data), abs_filepath, 'data')
write_array_to_xl_using_xlwings(to_array_with_years_and_values(controls), abs_filepath, 'controls')
write_array_to_xl_using_xlwings(names.as_matrix(), abs_filepath, 'names')
write_array_to_xl_using_xlwings(equations.as_matrix(), abs_filepath, 'equations')
def test_variable_names_validation():
from import_specification import validate_variable_names
validate_variable_names([])
validate_variable_names(['no_dots1', 'no_dots2'])
with pytest.raises(ValueError) as e:
validate_variable_names(['no_dots', 'with.dot'])
