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

# <a href="https://colab.research.google.com/github/enzoampil/fastquant/blob/master/examples/fastquant_demo.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>

# # Installation

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# !pip install -e git+https://github.com/enzoampil/fastquant.git@master#egg=fastquant


# # Get stock data

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from fastquant import get_stock_data
df = get_stock_data('JFC', '2018-01-01', '2019-01-01')
df.head()


# # Plot daily closing prices

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from matplotlib import pyplot as plt
df.close.plot(figsize=(10, 6))
plt.title("Daily Closing Prices of JFC\nfrom 2018-01-01 to 2019-01-01", fontsize=20)


# # Analyze with a simple moving average (SMA) trading strategy

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import pandas as pd
ma30 = df.close.rolling(30).mean()
close_ma30 = pd.concat([df.close, ma30], axis=1).dropna()
close_ma30.columns = ['Closing Price', 'Simple Moving Average (30 day)']

close_ma30.plot(figsize=(10, 6))
plt.title("Daily Closing Prices vs 30 day SMA of JFC\nfrom 2018-01-01 to 2019-01-01", fontsize=20)


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