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visualization.py
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visualization.py
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# Class that encapsulates the visualization of the data.
# Author: Albert Sanchez
# May 2018
import matplotlib.pyplot as plt
from datetime import datetime
class Data_Visualizer:
def __init__(self):
pass
def plot_support_resistance(self, data, levels):
"""
:param data: dataframe with all the data to plot
:param levels: list with the levels of support and resistance
:return: returns nothing. Shows a plot of the price and the supports and resistances.
Create a chart with the price data and the found supports and resistance for the given ticker
"""
ax = plt.axes()
self._plot_price_ax(data,ax)
for level in levels:
ax.axhline(y=level)
plt.show()
def plot_support_resistance_volume(self, data, levels):
"""
:param data: dataframe with all the data to plot
:param levels: list with the levels of support and resistance
:return: returns nothing. Shows a plot of the price and the supports and resistances.
Create a chart with the price data and the found supports and resistance for the given ticker
"""
fig, axs = self._plot_price_volume_axs(data)
for level in levels:
axs[0].axhline(y=level)
plt.show()
def plot_price(self, data):
"""
:param data: dataframe with all the data to plot
:return: returns nothing. Shows a plot of the price and the supports and resistances.
Create a chart with the price data for the given tickerself.
Close price - Black
High price - Green
Low price - Red
Open price - Dark grey
"""
self._plot_price_volume_axs(data)
plt.show()
def compare_time_series(self, series1, series2):
"""
:param series1: data for series1 (Pandas Series format)
:param series2: data for series2 (Pandas Series format)
:return: returns nothing. Shows a plot of the two time series.
Create a chart with both time series.
"""
fig, axs = plt.subplots(2, 1, sharex=True)
# Remove horizontal space between axes
fig.subplots_adjust(hspace=0)
axs[0].grid(color='silver')
axs[1].grid(color='silver')
axs[0].plot(series1)
axs[1].plot(series2)
plt.show()
def _plot_price_ax(self, data, ax):
ax.grid(color='silver')
ax.plot(data['Close'],'k')
ax.plot(data['High'], 'g')
ax.plot(data['Low'], 'r')
ax.plot(data['Open'], '#404040')
return ax
def _plot_price_volume_axs(self, data):
"""
:param data: dataframe with all the data to plot
:return: returns nothing. Shows a plot of the price and the supports and resistances.
Create a chart with the price data for the given tickerself.
Close price - Black
High price - Green
Low price - Red
Open price - Dark grey
"""
fig, axs = plt.subplots(2, 1, sharex=True)
# Remove horizontal space between axes
fig.subplots_adjust(hspace=0)
self._plot_price_ax(data,axs[0])
axs[1].grid(color='silver')
axs[1].bar(x=range(len(data)),height=data['Volume'])
return fig, axs
def _get_test_data(self):
start_year = 2017
start_month = 5
start_day = 20
end_year = 2018
end_month = 5
end_day = 20
start_date = datetime(year = start_year, month = start_month, day = start_day)
end_date = datetime(year = end_year, month = end_month, day = end_day)
dg = Data_Gatherer()
return dg.get_data('GLW','USAstocks', start_date,end_date,1,True)
def test(self):
data = self._get_test_data()
self.compare_time_series(data['High'], data['Low'])
self.plot_price(data)
levels = [29.46, 29.1, 33.89, 28.8]
self.plot_support_resistance_volume(data, levels)
self.plot_support_resistance(data, levels)
if __name__ == "__main__":
from data_gathering import Data_Gatherer
dv = Data_Visualizer()
dv.test()