#!/usr/bin/env python
# coding: utf-8

# In[1]:


from datetime import datetime, timedelta
from matplotlib import pyplot as plt
from matplotlib import dates as mpl_dates
import pandas as pd


# In[2]:


plt.style.use('seaborn')
plt.rc('figure', figsize=(12, 10))


# In[3]:


dates = [
    datetime(2019, 5, 24),
    datetime(2019, 5, 25),
    datetime(2019, 5, 26),
    datetime(2019, 5, 27),
    datetime(2019, 5, 28),
    datetime(2019, 5, 29),
    datetime(2019, 5, 30)
]

# print(dates)
y = [0, 1, 3, 4, 6, 5, 7]

plt.plot_date(dates, y, linestyle='solid')

# to get current figure
plt.gcf().autofmt_xdate()

# change date format
dates = [x.strftime("%b, %d %Y") for x in dates]

# %b - month
# %d - day
# %Y - year

plt.gca().set_xticklabels(dates)
# plt.set_xticklabels(dates)

plt.show()


# In[4]:


# example


# In[5]:


data = pd.read_csv(r'examples/data_8.csv')
data.head()


# In[6]:


data['Date'] = pd.to_datetime(data['Date'])
data.sort_values('Date', inplace=True)


# In[7]:


price_date = data['Date']
price_close = data['Close']


# In[8]:


plt.plot_date(price_date, price_close, linestyle='solid')

plt.gcf().autofmt_xdate()

plt.title('Bitcoin Prices')
plt.xlabel('Date')
plt.ylabel('Closing Price')

plt.tight_layout()

plt.show()