def main(args):
# road_to_area = {}
# func_road_to_area(args, road_to_area)
df = pd.read_csv(env.get_full_path(read_dir_name, args),
names=env.get_col_names(),
encoding='Shift_JISx0213')
# df = df.dropna(how='all')
df = df.apply(lambda x: extract_only_area(x), axis=1)
# df.iloc[:, 3:] = df.iloc[:, 3:].applymap(lambda x: road_to_area[x])
# df = df[df.loc[:, 'c03'] >= 0]
# dfT = df.T
# dfT = dfT.apply(remove_and_fill_none_area)
# df = dfT.T
# df.reset_index(drop=True, inplace=True)
# # df = pd.concat([df_id, df], axis=1)
# df = df.rename(columns={'c00': 'id'})
# df = df.sort_values(['id'])
# df = df.drop(['c01', 'c02'], axis=1)
#
# df.replace(' ', np.NaN, inplace=True)
# df.dropna(how='all', axis=1, inplace=True)
df = df.applymap(lambda x: (x.split('(census)')[0]) if (type(x) is str) and ('(census)' in x) else x)
for _area in env.get_area_list():
df_area = create_next_move_area(df.copy(), _area)
df_area.to_csv(env.get_full_path(write_dir_name, args, any=_area), index=False)
def main(args):
df = pd.read_csv(env.get_full_path(read_dir_name, args),
encoding='Shift_JISx0213')
for _area in env.get_area_list():
df_area = create_next_move_area(df, _area)
df_area.to_csv(env.get_full_path(write_dir_name, args, any=_area),
index=False)
def main(args):
df = pd.read_csv(env.get_full_path(read_dir_name, args),
names=env.get_col_names(),
encoding='Shift_JISx0213')
df = df.apply(lambda x: extract_only_area(x), axis=1)
df = df.applymap(lambda x: (x.split('(census)')[0])
if (type(x) is str) and ('(census)' in x) else x)
for _area in env.get_area_list():
df_area = create_next_move_area(df.copy(), _area)
df_area.to_csv(env.get_full_path(write_dir_name, args, any=_area),
index=False)
def main(args):
start = time.time()
col_names = ['c{0:02d}'.format(i) for i in range(30)]
df = pd.read_csv(env.get_full_path('Origin', args),
names=col_names,
encoding='Shift_JISx0213')
df.replace(' ', np.NaN, inplace=True)
df.dropna(how='all', axis=1, inplace=True)
distribute(df.copy(), args)
df_base[args.dir][args.ratio][args.seed][args.csv].to_csv(
env.get_full_path('2D', args), index=False)
print(env.get_file_name(args))
elapsed_time = time.time() - start
print("elapsed_time:{0}".format(elapsed_time) + "[sec]")
def func_road_to_area(args):
df = pd.read_csv(env.get_full_path('include_area_-1', args),
encoding='Shift_JISx0213')
df = df.loc[:, ['road', 'area']]
for row in np.asanyarray(df):
create_road_to_area(row[0], row[1])
road_to_area[np.nan] = np.nan
def main(args, array):
df = pd.read_csv(env.get_full_path(read_dir_name, args),
encoding='Shift_JISx0213')
df = df.loc[:, ['id', 'time', 'area']]
group_list = df.groupby(['id'], sort=True)
for _id, _group in group_list:
_group = _group.sort_values(['time'])
# array[args.dir][args.ratio][args.seed][args.csv][_id] = []
array[args.dir][args.ratio][args.seed][args.csv][_id] = []
for area in np.asanyarray(_group.loc[:, 'area']):
array[args.dir][args.ratio][args.seed][args.csv][_id].append(area)
df = pd.DataFrame()
df_main = array[args.dir][args.ratio][args.seed][args.csv].copy()
for _id in df_main:
df_main[_id].insert(0, _id)
tmp = pd.DataFrame(df_main[_id]).T
df = pd.concat([df, tmp])
df.to_csv(env.get_full_path(write_dir_name, args), index=False)
