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')