class PlotGraphs():

def plot(self):

import pandas as pd

import numpy as np

import matplotlib.pyplot as plt

import matplotlib.ticker as ticker

import datetime

# dummy data (Days)

dates_d = pd.date_range('2022-01-01', '2023-01-31', freq='D')

# Give random numbers to each month

df_year = pd.DataFrame(np.random.randint(100, 200, (dates_d.shape[0], 1)), columns=['Data'])

df_year.index = dates_d #set index

# Assign integer number to each month. 1..12

pt = pd.pivot_table(df_year, index=df_year.index.month, columns=df_year.index.year, aggfunc='sum')

# pt.columns = pt.columns.droplevel() # remove the double header (0) as pivot creates a multiindex.

ax = plt.figure().add_subplot(111)

# ax.plot(pt) # No need for this code cause it simply puts the pt df on the graph to show how data will look.

# Set month names on X-Axis

month_ticklabels = []

# month_ticklabels = [datetime.date(2022, item, 1).strftime('%b') for item in pt.index]

for item in pt.index:

# print(item)

year = datetime.date(2022, item, 1).strftime('%Y')

month = datetime.date(2022, item, 1).strftime('%b')

# print(month + ', '+ year)

month_label = month + ', '+ year

month_ticklabels.append(month_label)

ax.set_xticks(np.arange(1, 13))

ax.set_xticklabels(month_ticklabels, rotation=45) #add monthlabels to the xaxis

# -----

ax.legend(pt.columns.tolist(), loc='center left', bbox_to_anchor=(1, .5)) #add the column names as legend.

plt.tight_layout(rect=[0, 0, 0.85, 1])

# Set APY on Y-Axis

apy_tick_labels = [2, 5, 7, 9, 11, 13, 15] # in %age

plt.yticks(apy_tick_labels)

# Assign data to the grap

# example_data_apy_generated = pd.DataFrame([155, 1000, 2500, 3000, 4000, 155, 1000, 2500, 3000, 4000, 155, 1000])

# ax.plot(example_data_apy_generated)

# ------------

# Add horizontal grid lines

plt.grid(axis='y')

plt.show()

if __name__ == '__main__':

pg = PlotGraphs()

pg.plot()