conda env create --file environment.yml
python main.py
- Read the excel file
nl_fig = pd.read_excel('./input/nb_main_figures.xls') - Keep only Amsterdam Neigbhorhoods
ams_fig = nl_fig[np.isin(nl_fig['gwb_code_10'], ams_nb['BU_CODE'].unique())] - Join with the amsterdam neigbhorhoods dataframe
ams_nb = pd.merge(ams_nb, ams_fig, on='BU_CODE', how='left')
nb_main_figures_explainer.pdf is a guide for the labels of nb_main_figures. Some examples:
- a_inw: total number of inhabitants.
- a_hh: total number of households.
- p_hh_lkk: percentage of household with low income
- p_hh_li: percentage of households with the lowest 20% income.
- a_w_all: nr of people with western migration background.
- a_nw_all: nr of people with non-western migration background.
