def get_df_simple(): df20 = ebu.get_dataframe_2020() df19 = ebu.open_combine_2019() df = pd.merge(df19, df20, left_index=True, right_index=True, suffixes=['_19', '_20'], how='inner') return df
MAX_WITH = 800 PATH_OUT = 'docs/Ejemplos/z050_panel.html' FILE_OUT = os.path.join(os.path.dirname(ebu.DIR), PATH_OUT) COL_LLEGO = '#aaaaaa' COL_FALTA = '#db2879' # bokeh.plotting.output_file(os.path.join(os.path.dirname(ebu.DIR), # PATH_OUT)) # bokeh.plotting.output_notebook() # %% [markdown] # ## code # %% df2 = ebu.get_dataframe_2020() # %% # %% # %% bokeh.plotting.output_notebook() df2 = ebu.add_jitter(df2) cols = ['yj', 'xj', 'PAIS', 'MUN', 'REC', 'HAB', 'COU'] df2['COU'] = 'No' df2.loc[df2['COUNT'], 'COU'] = 'Sí' s1 = df2[df2['COUNT']][cols]
import sys sys.path.append(".") #from elec_bol20 import * import elec_bol20 as eb import elec_bol20.util as ebu import elec_bol20.tools as ebt import os import datetime #df0 = ebu.open_combine_2019() df0 = ebu.get_dataframe_2020() z = ebt.CartoPlots() y = z.load_file(df0, _mean=['X', 'Y', 'LAT', 'LON', 'DEN', ], _sum=['HAB', 'CC', 'MAS','CREEMOS', 'FPV','PAN_BOL','VV'], _first=['PAIS', 'REC', 'MUN', 'BOL']) # stamp Bolivian time at the moment of plotting bot_time = ebu.get_bolivian_time(-3)["str_val"] #print(bot_time) # goal_dir = os.path.join(ebu.DIR) #par dir ya esta en elec-bol20 # par_dir = os.path.pardir(goal_dir) # print(os.path.join(par_dir,"asdf")) #path_cart_maps=os.path.join(os.getcwd().,"../../carto_maps") #print(path_cart_maps) # # x1 = z.plot_carto_single(y, 'diff', ebu.P_DIF,path=path_cart_maps, name_file=bot_time, low=0, high=100, show_plot=False) # x2 = z.plot_carto_single(y, 'mas', ebu.P_GRAD_MAS,path=path_cart_maps, name_file=bot_time, low=0, high=100, show_plot=False) # x3 = z.plot_carto_single(y, 'cc', ebu.P_GRAD_CC, path=path_cart_maps, name_file=bot_time, low=0, high=100, show_plot=False) # x4 = z.plot_carto_single(y, 'creemos', ebu.P_GRAD_CREEMOS, path=path_cart_maps, name_file=bot_time, low=0, high=100, show_plot=False) # x5 = z.plot_carto_single(y, 'pan_bol', ebu.P_GRAD_PANBOL, path=path_cart_maps, name_file=bot_time, low=0, high=100, show_plot=False)
def process_data(df2): ll = len(df2) np.random.seed(100) df2['xj'] = df2['X'] + np.random.rand(ll) * .5 np.random.seed(200) df2['yj'] = df2['Y'] + np.random.rand(ll) * .5 df2['COU'] = 'No' df2.loc[df2['COUNT'], 'COU'] = 'Sí' return df2 df2 = ebu.get_dataframe_2020(path=ebu.FULL_COMP_CONCAT_CSV, col2keep=[ 'VV', 'BL', 'NU', 'VOTO_EMITIDO', 'CREEMOS', 'MAS', 'FPV', 'PAN_BOL', 'CC', 'NUA', 'HAB', 'TIMESTAMP', 'P_COMP' ]) main(df2) # %% _df['P_COMP'] # %% df2.columns # %% IS = 5 _df = df2[['xj', 'yj', 'P_COMP']].copy() _df = _df.dropna(how='any')