def concat(self, *argv):
n = 0
ls = []
while n < len(argv):
if isinstance(argv[n], pd.core.series.Series):
if len(ls) <= 1:
ls = argv[n].to_list()
else:
ls0 = argv[n].to_list()
ls1 = fn.aplist(ls, ls0)
ls = ls1
n = n + 1
nc = str(self.mdf.shape[1] + 1)
df1 = fn.add_col_df(self.mdf, nc)
df1[nc] = np.array(ls)
self.mdf = df1
def map_df_dic(self, dic, refcol):
nc = str(self.mdf.shape[1] + 1)
df = fn.add_col_df(self.mdf, nc)
df[nc] = df[refcol].map(dic)
self.mdf = df
def left(self, sdf, i):
df1 = fn.add_col_df(self.mdf, 'left_apply')
df1['left_apply'] = sdf.apply(lambda x: x[0:i])
self.mdf = df1
def right(self, sdf, i):
df1 = fn.add_col_df(self.mdf, 'right_apply')
df1['right_apply'] = sdf.apply(lambda x: x[-i:len(x)])
self.mdf = df1
n = n + 1
nc = str(self.mdf.shape[1] + 1)
df1 = fn.add_col_df(self.mdf, nc)
df1[nc] = np.array(ls)
self.mdf = df1
def conv_datatype(self, colname, typ):
if typ == 'date':
self.mdf[colname] = pd.to_datetime(self.mdf[colname],
errors='coerce')
elif typ == 'int':
print('x')
elif typ == 'str':
self.mdf[colname] = self.mdf[colname].applymap(str)
#ob = vbloop(df1)
#ob.left(df1['Item Type'],5)
#ob.right(df1['Item Type'],3)
#ob.concat(df1['Item Type'],df1['Unit Price'])
print(df0.columns)
df = fn.add_col_df(df0, 'OM')
list_of_cols_as_ref = ['Region', 'Country', 'Item Type']
df['OM'] = df[list_of_cols_as_ref].apply(lambda x: ''.join(map(str, x)),
axis=1)
print(df)
#df[st] = df[list_of_cols_as_ref].apply(lambda x: ''.join(map(str,x)),axis=1)
#print(ob.getdf())
## dL = fn.left (df1, df1['Item Type'], 3)
## dR = fn.right (df1, ddd = fn.right (df1, df1['Item Type'], 3)f1['Item Type'], 3)