import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
class My_data_timers_transform:
def __init__(self,input_file='data_timeseries.txt'):
self.input_file=input_file
def load_init_data(self):
self.data = np.loadtxt(self.input_file, delimiter=',')
def extract_start_end_date(self):
self.start_date = str(int(self.data[0,0])) + '-' + str(int(self.data[0,1]))
self.end_date = str(int(self.data[-1,0] + 1)) + '-' + str(int(self.data[-1,1] % 12 + 1))
return self.start_date,self.end_date
def extract_column_data_totimeseries(self,column=2):
import pandas as pd
dates = pd.date_range(self.start_date, self.end_date, freq='M')
# Convert the data into
import pandas as pd
import matplotlib.pyplot as plt
class My_data_timers_transform:
def __init__(self,input_file='data_timeseries.txt'):
self.input_file=input_file
def load_init_data(self):
self.data = np.loadtxt(self.input_file, delimiter=',')
def extract_start_end_date(self):
self.start_date = str(int(self.data[0,0])) + '-' + str(int(self.data[0,1]))
self.end_date = str(int(self.data[-1,0] + 1)) + '-' + str(int(self.data[-1,1] % 12 + 1))
return self.start_date,self.end_date
def extract_column_data_totimeseries(self,column=2):
import pandas as pd
dates = pd.date_range(self.start_date, self.end_date, freq='M')
# Convert the data into