def __init__(self):
data_obj = DataReader()
self.df = data_obj.get_pandas_df()
self.pk = "nagcode_1"
self.mode_map = {"active": "statesup", "defacto": "defacto"}
self.objective_map = OBJECTIVE_MAP
self.memory = {}
def __init__(self):
data_obj = DataReader()
self.df = data_obj.get_pandas_df()
self.pk = "NAGcode_1"
self.selected_columns = ['statesup', 'defacto']
self.write_columns = [
"{}_dep_score".format(column) for column in self.selected_columns
]
def __init__(self):
data_obj = DataReader()
self.pk = "nagcode_1"
self.df = data_obj.get_pandas_df()
self.mode_map = {
"active": "statesup",
"defacto": "defacto"
}
self.memory = {}
centralities = ["in-degree", "betweenness", "closeness"]
self.selected_columns = ["{}_{}_centrality".format(mode, c) for c in centralities for mode in self.mode_map ]
def get_aggregate_columns(self, columns):
data_obj = DataReader()
df = data_obj.get_pandas_df()
df = df.groupby(self.pk).agg(set).reset_index()
df = df[columns]
df['number_of_supporters'] = df['supporter'].apply(
lambda x: len([i for i in x if not pd.isna(i)]))
df['number_of_targets'] = df['target'].apply(
lambda x: len([i for i in x if not pd.isna(i)]))
df['support_target_ratio'] = df['number_of_supporters'] / df[
'number_of_targets']
return df
def __init__(self):
"""
Identity of NAG (Numeric): 1- NOID, 2-
Ethno-nationalist, 3- religious, 4- leftist, 5-
other
'nagid_2', 'nagid_3', 'nagid_4', 'nagid_5',
"""
data_obj = DataReader()
self.df = data_obj.get_pandas_df()
self.pk = "nagcode_1"
self.mode_map = {
"active": "statesup",
"defacto": "defacto"
}
self.ideology_map = IDEOLOGY_MAP
self.memory = {}
def __init__(self):
data_obj = DataReader()
self.pk = "nagcode_1"
self.df = data_obj.get_pandas_df()
def __init__(self):
data_obj = DataReader()
df = data_obj.get_pandas_df()
self.pk = "NAGcode_1"
self.df = df.groupby(self.pk).agg(set).reset_index()
def __init__(self):
data_obj = DataReader()
self.df = data_obj.get_pandas_df()
self.pk = "NAGcode_1"
self.var = 'Tar_DomSup'
self.var_pp = 'PolParDummy'
def get_non_duplictaes(self, columns):
data_obj = DataReader()
df = data_obj.get_pandas_df()
df = df.drop_duplicates(self.pk, keep='first').reset_index()
df = df[columns]
return df
def __init__(self):
data_obj = DataReader()
self.pk = "nagcode_1"
self.df = data_obj.get_pandas_df()
self.selected_columns = ["years_to_brd1", "years_to_brd2"]
def __init__(self):
data_obj = DataReader()
self.df = data_obj.get_pandas_df()
self.s_pk = "SupNum_COW"
self.pk = "NAGcode_1"
self.s_names = 'StateSupporter'
